JPH07101272A - Vehicle driving operating state estimating method and vehicle driving characteristic control method - Google Patents

Abstract

PURPOSE:To realize the driving of a vehicle conformed to the total vehicle driving state by obtaining the average value of plural vehicle driving parameters, estimating a road traffic state during the travel of the vehicle, and obtaining an output parameter on the basis of the weighted sum of plural input parameters. CONSTITUTION:During driving, the vehicle speed, accelerator opening, a steering wheel angle, and the like are detected in a specified cycle so as to compute longitudinal acceleration and lateral acceleration. The frequency distribution of each vehicle driving parameter is obtained, and the average value and dispersion value of each frequency distribution are obtained as input parameters characterizing each frequency distribution. Plural input parameters characterizing each frequency distribution are inputted to a neural network or the like to obtain the weighted sum of plural input parameters, and an output parameter indicating a vehicle driving operating state is obtained from the weighted sum. Second input parameters indicating an urban area degree and a congested road degree are also obtained on the basis of the compatibility of the combination of a travel time ratio and average frequency with plural fuzzy rules, and put to use for driving control.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an estimation method for estimating a vehicle driving operation state by a driver, and for controlling a vehicle driving characteristic to be suitable for the vehicle driving operation state estimated by this estimation method. Regarding control method.

[0002]

2. Description of the Related Art Various devices are mounted on a vehicle in order to improve the running stability, maneuverability, riding comfort and the like of the vehicle. For example, in a vehicle, an electronic fuel supply control device for optimally controlling the fuel supply amount to the engine according to the vehicle operating state represented by the vehicle speed, accelerator opening, etc. It is equipped with an automatic transmission for selecting and an anti-skid brake system for proper braking force. Further, the vehicle has a traction control system for optimizing the slip ratio of the driving wheels, a four-wheel steering device for steering the rear wheels when steering the front wheels, and an active suspension for variably adjusting the suspension characteristics. A system and an electric power steering device for variably adjusting the steering force are installed.

A vehicle equipped with the above-mentioned various devices has excellent steering stability and the like, and considerably satisfies various performances required for the vehicle. An example of a device for recognizing a vehicle operating state is already known in Japanese Patent Laid-Open No. 2-267030. This known invention is based on a plurality of operating parameters (throttle valve opening, engine speed, etc.)
By performing factor analysis, it is possible to recognize and judge driving states such as traffic jam driving, city driving, high speed driving, sports driving, etc., and perform optimal vehicle control according to this.

[0004]

However, the driving ability and the driving preference of the driver differ depending on the individual.
Therefore, the driving characteristics required for the vehicle differ depending on the individual driver. Further, the vehicle driving characteristics required by the driver are not always constant even for individual drivers, and for example, they may be different during urban driving and during mountain road traveling, or may change daily.

On the other hand, conventionally, the above-mentioned various devices mounted on a vehicle for controlling vehicle driving characteristics are operated according to a vehicle operating state represented by a physical quantity such as vehicle speed and accelerator opening degree. Therefore, it may be difficult to realize the vehicle driving characteristics required by each driver. In the above-described publicly known invention, the driver's state (sports traveling) is judged in the same row as the traffic condition, so it is difficult to judge an appropriate driving condition corresponding to the change of the traffic condition, that is, the driver's will. .

In view of this, the present invention estimates a vehicle driving operation state estimation method for estimating a vehicle driving operation state by a driver, which is difficult to be directly represented by a physical quantity such as vehicle speed, and a vehicle driving characteristic. The present invention aims to provide a vehicle driving characteristic control method for controlling to a vehicle driving operation state which is adapted to the above-mentioned vehicle driving operation state, and thereby adapted to a comprehensive vehicle driving state including a vehicle driving operation state by a driver and road traffic conditions. It is intended to enable the vehicle operation to be performed properly.

[0007]

A vehicle driving operation state estimating method according to the present invention detects a plurality of vehicle driving parameters,
While obtaining each average value of the plurality of vehicle driving parameters, estimating the road traffic situation when the vehicle is running, using the average value and road traffic situation as input parameters, the output parameter representing the vehicle driving operation state by the driver Obtained based on the weighted sum of a plurality of input parameters.

Preferably, the plurality of vehicle driving parameters are detected, the respective variance values of the plurality of vehicle driving parameters are obtained, the road traffic situation is estimated when the vehicle is running, and the respective variance values and the road traffic situation are input. As a parameter
An output parameter representing the vehicle driving operation state by the driver is obtained based on the weighted sum of the plurality of input parameters.

Preferably, the plurality of vehicle operating parameters include vehicle speed, accelerator opening, and longitudinal acceleration of the vehicle. More preferably, the vehicle speed is detected, and the longitudinal acceleration is calculated from the detected vehicle speed. Preferably, the plurality of vehicle driving parameters further include lateral acceleration. More preferably,
The vehicle speed and the steering wheel angle are detected, and the lateral acceleration is calculated from the detected vehicle speed and the steering wheel angle.

Preferably, the output parameter is obtained by inputting a plurality of input parameters to the neural network. More preferably, the weighted sum of the plurality of input parameters is obtained so that the output parameter represents the degree of the acne in the vehicle driving operation of the driver. More preferably, the frequency distribution is obtained by weighting a plurality of vehicle driving parameters.

Preferably, a plurality of second input parameters representing road traffic conditions are obtained based on a plurality of preset fuzzy rules or maps and the detected vehicle traveling condition parameters, and the plurality of input parameters and the plurality of input parameters are obtained. The output parameter is obtained based on the weighted sum of the second input parameters of More preferably, the road traffic condition includes an urban area degree and a congested road degree, and the vehicle traveling state parameter includes an average speed and a traveling time ratio. More preferably, the road traffic condition further includes a mountain road degree, and the vehicle driving state parameter further includes an average lateral acceleration.

The vehicle driving characteristic control method of the present invention drives and controls a device for variably controlling the vehicle driving characteristic which is mounted on a vehicle in accordance with an output parameter. Preferably, the vehicle driving characteristic control method includes a turning state detecting means for detecting a turning state of the vehicle, and a target driving torque setting means for setting a target driving torque of the vehicle based on the turning state detected by the previous state detecting means. A drive torque change amount limiting means for limiting the change amount to a limit change amount when the change amount of the target drive torque set by the target drive torque setting means exceeds a predetermined limit change amount; and the torque change amount limit. It is applied to an engine output control device having an engine output control means for controlling the output of the engine based on the target drive torque limited by the means, and the limit change amount of the drive torque change amount limiting means is set according to the output parameter. To change.

[0013] Preferably, the device for variably controlling the vehicle driving characteristics, which is mounted on the vehicle, is drive-controlled in accordance with the obtained output parameter and the road traffic condition. Preferably, it is applied to a rear wheel steering control device for controlling the steering of the rear wheels on the basis of the rear wheel steering angle by obtaining a rear wheel steering angle by multiplying the front wheel steering state and the vehicle operation parameter by the coefficient, It is variably set according to output parameters and road traffic conditions.

Preferably, it is applied to a power steering device in which a steering force of a steering wheel of a vehicle is variably controlled according to a vehicle speed, and the steering force is variably set according to the output parameter and road traffic conditions. Preferably, it is applied to a shift control device of an automatic transmission that performs shift control based on a shift map determined by a vehicle speed and a throttle opening, and the shift map is variably set according to the output parameter and road traffic conditions. .

Preferably, it is applied to a suspension device for variably controlling the damping force of a wheel suspension, and the damping force is variably set according to the output parameter and road traffic conditions.

[0016]

According to the estimating method of the present invention, for example, the vehicle speed, the accelerator opening, and the steering wheel angle are detected in a predetermined cycle while the vehicle is operating, and the longitudinal acceleration is calculated from the vehicle speed and the lateral acceleration is calculated from the vehicle speed and the steering wheel angle. To be done. As a result, the vehicle speed, the accelerator opening, the longitudinal acceleration, and the lateral acceleration are obtained as vehicle driving parameters.

Next, the frequency distribution of each vehicle driving parameter is obtained, and the average value and the variance value of each frequency distribution are obtained as the input parameters that characterize each frequency distribution. Then, a plurality of input parameters that characterize the respective frequency distributions are input to, for example, a neural network, and a weighted sum of the plurality of input parameters is obtained in this neural network. The output parameter that represents the degree of crispness in the vehicle driving operation is obtained.

In a particular aspect of the present invention, based on the vehicle speed and the lateral acceleration respectively detected in a predetermined cycle, the average speed, the running time ratio, and the vehicle running state parameters,
And the average lateral acceleration is determined. Next, a plurality of second input parameters representing road traffic conditions are obtained based on a plurality of fuzzy rules or maps respectively associated with a plurality of vehicle traveling modes and the detected vehicle traveling state parameters.

More specifically, the second degree representing the degree of urban area and the degree of congested road as the road traffic situation, respectively, based on the suitability of the combination of the detected traveling time ratio and the detected average speed to a plurality of fuzzy rules. Input parameters are required. Further, the second input parameter representing the mountain road degree as the road traffic condition is obtained from the average lateral acceleration and the map.

An input parameter characterizing the frequency distribution of vehicle driving parameters and a second parameter representing road traffic conditions.
The input parameters are input to the neural network, the weighted sum of these parameters is obtained in the neural network, and thereby the output parameter representing the vehicle driving operation state by the driver is obtained.

In the vehicle driving characteristic control method of the present invention, the device for variably controlling the vehicle driving characteristic mounted on the vehicle is drive-controlled in accordance with the thus-obtained output parameter, whereby each driver requests. Vehicle driving characteristics are realized. According to a specific mode in which the vehicle driving characteristic control method is applied to the engine output control device, the limit change amount of the drive torque change amount control means is variably controlled according to the output parameter.

According to a particular aspect of the vehicle driving characteristic control method of the present invention, the device for variably controlling the vehicle driving characteristic mounted on the vehicle is drive-controlled in accordance with the thus-obtained output parameter and road traffic condition. Thus, the vehicle driving characteristics required by the individual driver are realized. According to a specific mode in which the vehicle driving characteristic control method is applied to the rear wheel steering control device, the coefficient for obtaining the rear wheel steering angle is variably set according to the output parameter and road traffic conditions.

According to a specific mode in which the vehicle driving characteristic control method is applied to the power steering device, the steering force of the steering wheel is variably set according to the output parameter and road traffic conditions. According to a particular aspect in which the vehicle driving characteristic control method is applied to a shift control device for an automatic transmission, the shift map is variably set according to the output parameter and road traffic conditions.

According to a particular mode in which the vehicle driving characteristic control method is applied to the suspension device, the damping force of the suspension is variably set according to the output parameter and road traffic conditions.

[0025]

【Example】

[First Embodiment] An estimation method, which is an embodiment of the present invention, determines a vehicle driving operation state by a driver based on a road traffic state obtained based on a vehicle traveling state parameter and a physical quantity representing the vehicle driving state. I am trying to estimate.

More specifically, as shown in FIG. 1, from the vehicle speed and the steering wheel angle, the average speed as a vehicle traveling state parameter and the traveling time ratio (the ratio of the traveling time to the total time including the vehicle traveling time and the traveling stop time). ), And the average lateral acceleration. Then, by fuzzy inference based on these vehicle traveling state parameters, the degree of urban area, the degree of congested road, and the degree of mountain road are detected as parameters that represent road traffic conditions.

On the other hand, as shown in FIG. 2, a physical quantity representing a vehicle operating state, such as an accelerator opening, a vehicle speed and a steering wheel angle, is detected, and a longitudinal acceleration is calculated from the vehicle speed and a lateral acceleration is calculated from the vehicle speed and the steering wheel angle. Required by. Then, the frequency distribution of each of the vehicle speed, the accelerator opening, the longitudinal acceleration, and the lateral acceleration as vehicle driving parameters is obtained by frequency analysis. Then, the average value and variance of each frequency distribution are obtained as parameters that characterize the frequency distribution.

Further, parameters representing the road traffic condition (city level, congestion level and mountain level) and parameters characterizing the frequency distribution of the respective vehicle driving parameters (average value and variance) are input to the neural network. To be done. In the neural network, a weighted sum of these parameters is obtained, and thereby, an output parameter representing a vehicle driving operation state by the driver, for example, a degree of acne in the vehicle driving operation of the driver is obtained.

The vehicle to which the estimation method according to this embodiment is applied is equipped with a controller 15 as shown in FIG. Although not shown, this controller 15
Including a processor having a fuzzy inference function and a neural network function, a memory, and an input / output circuit,
Various control programs and various data are stored in the memory. A vehicle speed sensor 26, a steering wheel angle sensor 16 and a throttle opening sensor 104 are connected to the controller 15.

The processor of the controller 15 inputs the vehicle speed signal, the steering wheel angle signal and the throttle opening signal from the sensors 26, 16 and 104, and sequentially executes various routines described later to estimate the degree of acne of the driver. It has become. While the vehicle is in the driving state (including the traveling state and the traveling stopped state) after the engine is started, the processor of the controller 15 executes the traveling time ratio calculation routine shown in FIG. Repeat with.

In each calculation routine execution cycle, the processor inputs the vehicle speed signal vel from the vehicle speed sensor 26 representing the actual vehicle speed and determines whether or not the vehicle speed vel exceeds a predetermined vehicle speed (for example, 10 km / h). Yes (step S1). If this determination result is affirmative, the count value of the traveling time counter (not shown) built in the controller 15
"1" is added to rtime (step S2). on the other hand,
If the determination result in step S1 is negative, "1" is added to the count value stime of the traveling stop time counter (not shown) (step S3).

Step S4 following step S2 or S3
Then, it is determined whether or not the sum of the traveling time counter value rtime and the traveling stop time counter value stime is equal to the value “200”. If the determination result is negative, the running time counter value rtime is set to this value and the running stop time counter value s.
The value obtained by dividing by the sum with time is multiplied by the value “100” to calculate the traveling time ratio ratio (%) (step S
5).

On the other hand, if the determination in step S4 is affirmative, a value equal to the product of the running time counter value rtime and the value "0.95" is reset in the running time counter, and
A value equal to the product of the traveling stop time counter value stime and the value "0.95" is reset in the traveling stop time counter (step S6), and then the traveling time ratio ratio is calculated in step S5.

That is, both counter values are reset at the time when the vehicle is driven for 400 seconds corresponding to the value "200" from the engine start, and then 1
The counter value is reset every 0 seconds. As a result, it is possible to calculate the traveling time ratio that reflects the vehicle driving condition before the present time even if the counter having a relatively small capacity is used. "Average Speed Calculation Routine" The processor of the controller 15 repeatedly executes the average speed calculation routine shown in FIG. 5 in a cycle of, for example, 2 seconds.

In each routine execution cycle, the processor reads the vehicle speed data vx from the vehicle speed sensor 26 and stores each of the stored values vxsum [i] (i = 1 to 5) of the five accumulated speed registers built in the controller 10. Vehicle speed
vx is added (step S11). Next, the processor determines whether or not the value of the flag f 1m is “1” indicating the average speed calculation timing (step S12). This flag f 1m takes a value “1” in a 1-minute cycle. Then, if the determination result in step S12 is negative, the process in the current cycle ends.

If one minute has passed since the start of this routine and the result of the determination in step S12 is affirmative, the index jj
Update the index jj by adding the value "1" to
Set the cumulative speed register value vxsum [jj] corresponding to jj to "15.
Divide by 0 "to calculate the average speed vxave, and register this value v
xsum [jj] is reset to "0" (step S13).
Then, it is determined whether or not the updated index jj is "5" (step S14), and if the determination result is negative, the process in this cycle ends.

After that, the index jj is updated every one minute, and the accumulated speed register value corresponding to the updated index jj
The average speed vxave can be calculated from vxsum [jj]. And 5
The index jj is reset to "0" every time minutes elapse (step S15). As described above, the actual vehicle speed vx is added to each of the five cumulative speed register values vxsum [i] every 2 seconds, and the corresponding one of the five cumulative speed registers is performed 150 times (5 minutes). Based on the stored value vxsum [jj] representing the detected total vehicle speed, the average speed vxave is 1
Calculated every minute. “Average lateral acceleration calculation routine” The processor of the controller 15 repeatedly executes the average lateral acceleration calculation routine shown in FIG. 6 at a cycle of, for example, 2 seconds.

In each routine execution cycle, the processor reads the output signal from the vehicle speed sensor 26 representing the vehicle speed vx and the output signal from the steering wheel angle sensor 16 representing the steering wheel angle steera, and with reference to a map (not shown), A predetermined steering wheel angle gygain, which is expressed as a function of the vehicle speed vx and gives a lateral acceleration of 1 (G), is obtained based on the vehicle speed vx. Next, the processor calculates the lateral acceleration gy by dividing the steering wheel angle steera by the predetermined steering wheel angle gygain, and stores the stored values gysum [i] (i = 1 to 1) of the five cumulative lateral acceleration registers built in the controller 10. The lateral acceleration gy is added to each of 5) (step S21). Next, the processor determines whether or not the value of the flag f 8s is “1” indicating the average lateral acceleration calculation timing (step S22).
This flag f8g takes a value "1" in a cycle of 8 seconds. Then, if the determination result in step S22 is negative, the process in the current cycle ends.

When 8 seconds have passed since the start of this routine and the result of the determination in step S22 is affirmative, the index jj
Update the index jj by adding the value "1" to
Set the cumulative lateral acceleration register value gysum [jj] corresponding to jj to "2.
The average lateral acceleration gyave is calculated by dividing by 0 ", and this register value gysum [jj] is reset to" 0 "(step S2).
3). Then, it is determined whether or not the updated index jj is "5" (step S24), and if the determination result is negative, the process in this cycle ends.

After that, the index jj is updated every 8 seconds, and the average lateral acceleration gyave is obtained from the cumulative lateral acceleration register value gysum [jj] corresponding to the updated index jj. The index jj is reset to "0" every 40 seconds (step S25). As described above, the calculated lateral acceleration gy is added to each of the five cumulative lateral acceleration register values gysum [i] every 2 seconds, and the corresponding one of the five cumulative lateral acceleration registers, 20 times (40 times). The average lateral acceleration gyave is calculated every 8 seconds based on the stored value gysum [jj] that represents the total lateral acceleration calculated over (for 2 seconds). [Urban Area Degree, Congested Road Degree, and Mountain Road Degree Calculation Routine] In the present embodiment, the city traveling mode, the congested road traveling mode, and the mountain road traveling mode are determined as the vehicle traveling modes related to the vehicle driving operation state estimation by the driver. As a target, the degree of urban area, the degree of congested road, and the degree of mountain road are determined.

The degree of urban area and the degree of traffic jam are determined by fuzzy inference. In connection with this fuzzy inference, there are membership functions (Figs. 7 and 8) that represent fuzzy subsets in the entire space (base set) for the traveling time ratio and the average speed, and the nine fuzzy rules shown in the table below. It is set in advance and stored in the memory of the controller 15.

[0042]

[Table 1]

The fuzzy rule settings shown in the above table are based on the fact that the average speed is low and the traveling time ratio is medium in city driving, and the average speed is low and the traveling time ratio is low in congested road driving. I went there. Figure 7
Each of the symbols S, M and B is a label indicating a fuzzy set in the pedestal concerning the traveling time ratio. The membership function that defines the fuzzy set S has a goodness of fit of "1" when the running time ratio is from 0% to 20%, and a goodness of fit is "1" as the running time ratio increases from 20% to 40%. It is set to decrease from "1" to "0". Also, the membership function that defines the fuzzy set M increases the fitness from “0” to “1” as the running time ratio increases from 20% to 40%, and the running time ratio from 40% to 65%. The degree of conformity is "1" between the two, and the degree of conformity decreases from "1" to "0" as the traveling time ratio increases from 65% to 85%. The membership function that defines the fuzzy set B has a goodness of fit from "0" to "1" as the traveling time ratio increases from 65% to 85%.
It is determined that the compatibility is “1” when the traveling time ratio is 85% or more.

Referring to FIG. 8, the membership function that defines the fuzzy set S in the platform relating to the average speed has a goodness of fit of "1" between the average speed of 0 km / h and 10 km / h, and the average speed. Is determined to decrease from "1" to "0" as the value increases from 10 km / h to 20 km / h. The membership function that defines the fuzzy set M has an average speed of 10 km / h to 20 km.
The degree of conformity increases from "0" to "1" as it increases to / h, the degree of conformity is "1" between the average speed of 20 km / h and 40 km / h, and the average speed of 40 km / h 60 km
It is specified that the fitness decreases from "1" to "0" as it increases to / h. And the membership function that defines the fuzzy set B has an average speed of 40 km.
It is defined that the fitness increases from “0” to “1” as the speed increases from / h to 60 km / h, and that the fitness becomes “1” when the average speed is 60 km / h or higher.

The processor of the controller 10 determines whether the combination of the traveling time ratio (%) and the average speed (km / h) obtained by the calculation routines shown in FIGS.
The adaptability adapt [i] for each of the ninth rules is calculated, and then the degree of urban area and the degree of congested road are calculated according to the following formulas. City level [city] = Σ (adap [i] × r_city [i]) ÷ adapt [i] (i = 1-9) Congestion degree [jam] = Σ (adap [i] × r_jam [i]) ÷ adapt [i] (i = 1 to 9) Specifically, the processor obtains the adaptability of the actual traveling time ratio to one of the fuzzy sets S, M and B relating to the traveling time ratio, which corresponds to the i-th rule, and then , The i-th of the fuzzy sets S, M and B relating to the average speed
Find the fitness of the actual average speed to the one corresponding to the rule. Then, the smaller one of the two fitness values is the i-th
The adaptability [i] of the combination of the actual traveling time ratio and the actual average speed for the rule is adopted.

With respect to the first rule, as shown in FIGS. 9 and 10, when the actual traveling time ratio is 30% and the actual average speed is 10 km / h, for the traveling time ratio fuzzy set S, "0.5" is obtained as the goodness of fit of the actual traveling time ratio of 30%, and "1" is obtained as the goodness of fit of the actual average speed 10 km / h to the average speed fuzzy set S.
Is required. Therefore, the adaptability adapt [1] of the combination of the actual traveling time ratio of 30% and the actual average speed of 10 km / h to the first rule is “0.5”.

Next, the processor of the controller 15
Average lateral acceleration stored in the memory of the controller 15
Referring to the mountain road degree map, the mountain road degree is calculated based on the average lateral acceleration obtained by the routine of FIG. As illustrated in FIG. 11, in this map, the mountain road degree becomes “0” between the average lateral acceleration of 0 G and about 0.1 G, and the average lateral acceleration increases from about 0.1 G to 0.4 G. The mountain road degree is increased from "0" to "100" as it goes, and the mountain road degree is set to "100" if the average lateral acceleration is 0.4 G or more. This map setting is based on the fact that the lateral acceleration integrated value becomes large when traveling on a mountain road. "Frequency Analysis Routine" The processor of the controller 15 executes frequency analysis for each of the vehicle speed, longitudinal acceleration, lateral acceleration, and accelerator opening degree in a cycle of, for example, 200 milliseconds to obtain an average value and variance of each physical quantity. FIG. 12 shows a frequency analysis routine for the vehicle speed, and a frequency analysis routine (not shown) other than the vehicle speed is configured similarly to this routine.

The vehicle speed as the frequency analysis target parameter is
It is represented by an output signal from the vehicle speed sensor 26, and its input range is set to 0 to 100 km / h, for example.
The accelerator opening tps (%) is measured by the throttle opening sensor 10
It is calculated according to the following formula based on the output signal of No. 4, and its input range is 0 to 100%. tps = (tdata-tpsoff) ÷ (tpson-tpsoff) × 100 Here, the symbol tdata represents the current throttle opening sensor output, and the symbols tpsoff and tpson are the throttle opening sensor in the accelerator off state and the accelerator fully open state. Represents each output.

Further, the processor samples the output of the vehicle speed sensor 26 at a cycle of 100 milliseconds, for example, and calculates the longitudinal acceleration gx (unit G) according to the following equation. The input range of the longitudinal acceleration is, for example, 0 to 0.3G. gx = (vx-vx0) × 10 ÷ (3.6 × 9.8) where the symbol vx represents the current vehicle speed (km / h), and vx0 is 1
Indicates the vehicle speed (km / h) before 00 milliseconds.

Further, the output signal from the vehicle speed sensor 26 representing the vehicle speed vx and the output signal from the steering wheel angle sensor 16 representing the steering wheel angle steera are read and expressed as a function of the vehicle speed vx with reference to a map (not shown). A predetermined steering wheel angle gygain that gives the lateral acceleration of (G) is obtained based on the vehicle speed vx. Next, as shown in the following expression, the processor calculates the lateral acceleration gy (G) by dividing the steering wheel angle steera by the predetermined steering wheel angle gygain. The input range of lateral acceleration is, for example, 0 to 0.5G.

Gy = steera / gygain Referring to FIG. 12, the processor divides the vehicle speed signal vel as the frequency analysis target parameter (input data) into 10 equal parts within the input range 0 to 100 km / h "(vel / 1
0) ”is added to“ 1 ”to obtain the value dat (step S3
1) It is determined whether or not this value dat is larger than "10" (step S32). If the determination result is affirmative, the value dat is reset to "10" in step S33, and the process proceeds to step S34. On the other hand, step S3
If the determination result in 2 is negative, the process immediately shifts from step S32 to step S34. In step S34,
As shown in FIG. 13, 1 that constitutes the population of input data
"1" is added to the corresponding one element number hist [dat] of 0 arrays (the number of elements of the maximum value side array is 0 in FIG. 13).

In the next step S35, step S31
It is determined whether or not the value dat obtained in step 3 is smaller than "3". If this determination result is affirmative, in step S36, similar to step 34, of 10 arrays forming the population of the input data (in FIG. 13, the number of elements in the maximum value side array is 0). Corresponding one element number hist [dat]
"1" is added to, and the process proceeds to step S37. On the other hand, if the determination result in step S35 is negative, the process immediately shifts from step S35 to step S37.

In the next step S37, the first to the first
The sum num of the number of elements in the 0 array is obtained, and the sum sum of products of the number of elements obtained for each array (i-th array) and the value “i−1” is obtained. The processor sums the products s
The value obtained by dividing um by the total number num of elements, num, is further divided by the value “10” to obtain the average value ave of the input data (vehicle speed in this case) (step S38).

Next, the processor sets the average value ave to "10".
It is determined whether it is larger than "0" (step S39),
If this determination result is affirmative, the average value is calculated in step S40.
The ave is reset to "100" and the process proceeds to step S41. On the other hand, if the determination result in step S39 is negative, the process immediately shifts from step S39 to step S41.
That is, the average value ave of the input data is limited to a value up to “100”.

In step S41, the average value ave is set to "1".
The value obtained by subtracting the value divided by "0" from the value "i-1" ((i-
1)-(ave / 10)) squared and the number of array elements hist [i] are calculated for each array, and then the sum sum2 of the products is calculated. Next, the processor further divides the sum sum2 divided by the total number num of elements by the value "5" to calculate the variance var of the input data (step S42). Then, it is determined whether or not the variance var of the input data is larger than "100" (step S43). If the determination result is affirmative, the variance var is "10" in step S44.
After resetting to "0", the process proceeds to step S45, and if the determination result in step S43 is negative, step S41
To S45 immediately. That is, the variance var of the input data is limited to the value “100”.

In step S45, it is determined whether or not the total number num of elements is larger than "128". If the result of this determination is negative, the processing in this cycle is ended, while the result of determination is positive. For example, the number of elements hist [i] of each of the first to tenth arrays is reset to a value obtained by multiplying it by the value "15/16" (step S46), and the processing in the current cycle ends. That is, the number of elements num in the population is “128”
When it exceeds, the number of elements in each array is reduced by "15/16" times. After that, the processing of FIG. 12 is repeated, and the average value and the variance of the vehicle speed vel as the input data are periodically obtained.

Other input data, accelerator opening,
The average value and variance of each of the longitudinal acceleration and the lateral acceleration are similarly obtained. It should be noted that the average value and the variance of each input data increase as the driving method by the driver becomes sharper. However, the average vehicle speed is greatly affected by road traffic conditions. The processor of the "driving operation state calculation routine" controller 15 uses the neural network function to
Obtain the driving operation status by the driver. In this embodiment,
In addition to the average value and variance of each of the vehicle speed, accelerator opening, longitudinal acceleration and lateral acceleration obtained by the above frequency analysis, the degree of urban area, the degree of congested road and the degree of mountain road obtained by the above fuzzy inference are applied to a neural network. By inputting the data, the degree of crispness as a driving operation state by the driver is obtained.

Conceptually, the neural network is
The processing elements (PE) shown in FIG. 14 are intricately entwined with each other as shown in FIG. 15, and each PE has a large number of inputs x [i] and respective weights w [j].
The sum of the products multiplied by [i] is entered. And
In each PE, this sum is converted by a certain transfer function f, and the output y [i] is transmitted from each PE.

With reference to FIG. 14 and FIG.
The neural network used in this embodiment is the input layer 2
01 and the output layer 203, one hidden layer 202 is interposed, the input layer 201 is composed of 11 PEs,
The hidden layer 202 is composed of 6 PEs, and the output layer 203 is 1
It consists of two PEs. The transfer function f of PE is f
(X) = x. Further, the weight w [j] [i] at the joint between the PEs is determined through a learning process. An input 204 called a bias is additionally set in the neural network of this embodiment.

In this embodiment, the function of the neural network described above is achieved by the controller 15. In order to realize this neural network function, the processor of the controller 15 controls the average value and variance of each of vehicle speed, accelerator opening, longitudinal acceleration, and lateral acceleration, and the degree of urban area, the degree of congested road, and the degree of mountain road (both in their output ranges). Is used as input data, and the degree of acne degree calculation routine shown in FIG. 16 is periodically executed.

In the routine of FIG. 16, the processor subtracts "100" from the product of the input data dd [i] and "2" to obtain 11 input data dd [i] (i = 1 to 11). The range is converted from "0 to 100" to "-100 to 100", respectively.
Obtain n [i] (step S51). Then the processor
The sum dri of the products of the input data din [i] obtained for each range-converted input data din [i] and the weighting coefficient nmap [i + 1]
ve is calculated, and a similar product (nmap
[1] * 100) is calculated, and the product (nmap [1] * 100) related to the bias is added to the total drive related to the input data, and the output drive representing the degree of acne is calculated (step S52).

Then, the crispness output drive is set to "100.
"100" is added to the value divided by "00", the addition result is divided by "2", and the range of the acne degree output is "-1".
The conversion from "000000 to 1000000" is converted to "0 to 100" (step S53), whereby the calculation of the degree of acne in one calculation cycle is completed. As described above,
The output drive that represents the degree of acne as the vehicle driving operation state by the driver is obtained. Then, according to the test running results, the estimated value of the degree of acne of the driver represented by the output drive was in good agreement with the degree of acne evaluated and declared by the driver himself. This was evaluated based on the average value and variance of physical quantities that characterize the frequency distribution of various physical quantities, and in consideration of road traffic conditions, for the driver's driving operation status that is difficult to evaluate with physical quantities such as vehicle speed. It is understood that it is due to things. [Second Embodiment] In the present embodiment, a second estimation method which is a modification of the above estimation method will be described.

The second estimation method is similar to the estimation method of the first embodiment (first estimation method), and is based on the road traffic condition and the physical quantity representing the vehicle operating condition, which are obtained based on the vehicle traveling condition parameter. The driver's driving condition is estimated by the driver. The second estimation method is intended to be applicable to a vehicle that does not have a steering wheel angle sensor.

As shown in FIG. 17, from the vehicle speed, the average speed and the traveling time ratio as the vehicle traveling state parameters are obtained. In this estimation method, since there is no steering wheel angle sensor, the average lateral acceleration obtained from the steering wheel angle and the vehicle speed is not calculated. Then, by fuzzy inference based on these vehicle running state parameters, the degree of urban area and the degree of congestion are detected as parameters indicating road traffic conditions. In this method, since the average lateral acceleration is not calculated as the vehicle traveling state parameter, the mountain road degree as the parameter indicating the road traffic condition is not detected.

On the other hand, physical quantities representing the vehicle operating state, such as the accelerator opening and the vehicle speed, are detected, and the longitudinal acceleration is obtained from the vehicle speed. Then, the frequency distribution of each of the vehicle speed, the accelerator opening, and the longitudinal acceleration is obtained as a vehicle operating parameter by frequency analysis. Then, the average value and variance of each frequency distribution are obtained as parameters that characterize the frequency distribution. In this estimation method, the lateral acceleration obtained from the vehicle speed and each steering wheel is not calculated.

Further, parameters representing the road traffic condition (city level and congestion level) and parameters (average value and variance) characterizing the frequency distribution of each vehicle driving parameter are input to the neural network. In the neural network, a weighted sum of these parameters is obtained, and thereby, an output parameter representing the degree of cramping of the vehicle driving operation state by the driver, for example, the vehicle driving state of the driver is obtained.

The number of input data of the neural network in the second estimation method is eight, compared with 11 in the first estimation method. Also in the second estimation method, if the weighting of each parameter is reconstructed in the neural network, it is possible to obtain an output parameter equivalent to the degree of acne obtained in the first estimation method. Therefore, the method for estimating the vehicle driving state can be applied to a vehicle system that is not equipped with the steering wheel angle sensor. [Third Embodiment] A third embodiment of the vehicle driving characteristic control method according to the present invention will be described below.

This embodiment is intended to control the vehicle driving characteristics to be suitable for the vehicle driving operation state (acne degree) estimated by the estimation method of the above-mentioned embodiment, in order to estimate the acne degree. The procedure of is the same as that of the above estimation method, and the description of the device configuration and the like for this is omitted. In this embodiment, a vehicle equipped with a four-wheel steering device as a device for variably controlling vehicle driving characteristics will be described.

Referring to FIG. 18, the left and right front wheels 1L and 1R of the automobile are connected to the front wheel power steering device 2 via tie rods 3. The device 2 forms a four-wheel steering device in cooperation with various elements described later, and a front wheel steering device including a rack and pinion mechanism (not shown) operated by a steering handle 4 and a hydraulic cylinder connected to the rack and pinion mechanism. And an actuator (not shown).

The front wheel steering actuator is connected to one hydraulic pump 7 of the pump unit 6 via a front wheel steering valve 5 operated by a steering handle 4. The pump unit 6 is a double pump driven by the engine 8, and the other hydraulic pump 9 is provided with a rear wheel steering actuator 11 via a rear wheel steering valve 10.
It is connected to the.

The rear wheel steering actuator 11 also comprises a hydraulic cylinder, and the piston rod of the actuator 11 is connected to the left and right rear wheels 13L, 13R via a tie rod 12. In FIG. 18, reference numeral 14 indicates a reservoir tank. The front wheel steering actuator is operated according to the steering direction by the supply of hydraulic oil from the hydraulic pump 7 via the front wheel steering valve 5 during steering of the steering handle 4. On the other hand, the operation of the rear wheel steering actuator 11 is controlled by the controller 15. That is, when the steering wheel 4 is steered, the controller 15 supplies the rear wheel steering valve 10 with an operation control signal SR suitable for the vehicle traveling state, whereby the rear wheel steering from the hydraulic pump 9 via the valve 10 is performed. The hydraulic pressure supplied to the actuator 11 is controlled.

In connection with the above-mentioned rear wheel steering actuator operation control, the controller 15 is electrically connected to various sensors and meters. That is, the controller 15 receives a vehicle speed V from the meters (corresponding to the above-mentioned vehicle speed signal vx) and a sensor signal indicating the operating state of various devices, and a steering wheel angle θH from the steering wheel angle sensor 16 (in the above steering wheel angle steera). Sensor signal indicating that the power steering device (power steering device 2
As a result, a sensor signal indicating the operating pressure of the front wheel steering actuator) is supplied. In this embodiment,
Left and right pressure chambers (not shown) of the front wheel steering actuator detected by the pair of pressure sensors 18 and 19, respectively.
The difference between the pressures PL and PR is calculated as the power steering pressure. Further, the controller 15 is connected with a yaw rate sensor 60 for detecting an actual yaw rate of the vehicle (speed of rotation around the vehicle body weight center), and a signal indicating the actual yaw rate Y from the sensor 60 is sent to the controller 15. It is being supplied.

As shown in FIG. 19, the controller 15
Is functionally, the steering wheel angle sensor 16 and the vehicle speed sensor 2
6, the input unit 30 that receives data from the yaw rate sensor 60 and the meter, the A / D conversion unit 31 that receives signals from the pressure sensors 18 and 19, and the traveling mode of the vehicle based on the data from the input unit 30 And a road surface μ detection unit 33 that calculates a road surface friction coefficient, that is, a road surface μ based on data from the input unit 30 and the A / D conversion unit 31. Further, the controller 15 includes the input unit 30, the mode determination unit 32, and the road surface μ.
Based on the data from the detection unit 33, the rear wheel steering valve 10
Steering valve operation control unit 3 for calculating the operation control signal SR of
4 and an output section 35 for outputting the operation control signal SR calculated by the control section 34 to the rear wheel steering valve 10.

The mode determination unit 32 determines the rear wheel steering steering mode (for example, the suspension of the control, the large steering angle control of the rear wheels) based on the steering wheel angle θH, the vehicle speed V, and the data supplied from the meter to the input unit 30. , Rear wheel phase control). In addition, the road surface μ detection unit 33 has a function of detecting the road surface μ from the steering wheel angle θH, the vehicle speed V, and the pressures PL and PR.

As shown in FIG. 20, the road surface μ detector 33
Is provided with a subtraction unit 22 that calculates the difference between the pressures PL and PR from the pressure sensors 18 and 19 as the power steering pressure ΔP.
Then, the power steering pressure ΔP from the subtraction unit 22 passes through the phase compensating filter 21 and the road surface μ in order to remove noise and to compensate the phase lead of the power steering pressure ΔP with respect to the steering wheel angle θH in the steering transition period of the steering wheel 4. It is supplied to the calculation unit 20. The steering wheel angle θH and the vehicle speed V detected by the steering wheel angle sensor 16 and the vehicle speed sensor 26 are supplied to the calculation unit 20. Then, the road surface μ calculation unit 20 calculates the road surface μ from the power steering pressure ΔP, the steering wheel angle θH, and the vehicle speed V according to the following equation.

ΔP / θH = μ · C1 · V2 / (μ + C2 ·
V2) Here, C1 and C2 represent constants. Although detailed description is omitted, the above equation shows that the power steering pressure ΔP, which is substantially proportional to the cornering force, is proportional to the product of the sideslip angle and the road surface μ, and
It is derived from the fact that the sideslip angle is expressed as a function of the vehicle speed V, the steering wheel angle θH and the road surface μ.

Road surface μ calculated by the road surface μ computing unit 20
When the rate of change is within a predetermined range, is sent from the μ fluctuation limiting section 23 to the stabilization filter 24, and the value of the road surface μ is stabilized by the filter 24. Hereinafter, the operation of the controller 15 as the road surface μ detection unit 33 will be briefly described. First, the pressures PL and PR detected by the pressure sensors 18 and 19, the steering wheel angle sensor 16, the vehicle speed sensor 26 (meter) and the yaw rate sensor 60, and the steering wheel angle θ.
H, vehicle speed V, and actual yaw rate Y are controller 1
Read by 5.

Next, the power steering pressure ΔP (= PR-PL) is calculated and subjected to a filtering process, whereby the phase lead of the power steering pressure ΔP during the steering transition period of the steering wheel 4 is removed. And the steering wheel angle θH
It is determined whether the steering wheel 4 is cut or is being held, based on the size of the steering wheel and its change. If the steering wheel 4 is cut, the absolute value of the steering wheel angle θH is a predetermined value θ1 (for example, 1
It is further determined whether it is 0 ° or more. If the steering wheel 4 is being held or the steering wheel angle θH has not reached the predetermined value θ1, the procedure after reading the sensor output is repeated. If the steering wheel angle θH is equal to or greater than the predetermined value θ1 and the power steering pressure ΔP substantially rises, the ratio (ΔP / θH) between the power steering pressure ΔP and the steering wheel angle θH can be obtained.

Next, in order to accurately calculate the road surface μ by removing the influence of the inertia of the front wheels, it is necessary to determine whether the direction of the power steering pressure ΔP and the direction of the steering wheel angle θH are the same.
It is determined whether the sign of P / θH is positive. If the determination result is negative, the power steering pressure Δ
It is determined that a phase inversion has occurred between P and the steering wheel angle θH, and the procedure after reading the sensor output is repeated. On the other hand, if the sign of ΔP / θH is positive, the coefficient Kμ represented by the following equation is read from the map stored in the memory (not shown) of the road surface μ computing unit 20.

Kμ = 1 + C2 · V2 / (C1 · V2) Next, the road surface μ is calculated by multiplying the coefficient Kμ and the value ΔP / θH. Further, the calculated change rate (differential value) dμ / dt of the road surface μ is a predetermined value Δμ (for example,
0.2 μ / sec) or not. If the determination result is negative, the procedure after reading the sensor output is executed, while if the determination result is positive, the road surface μ
The road surface μ after filtering to stabilize the value of
The road surface μ is supplied to the steering valve actuation control unit 34 after the sudden change of the vehicle is prevented.

The steering valve actuation control unit 34 calculates the rear wheel steering valve actuation control signal SR based on the output data from the mode determination unit 32 and the road surface μ detection unit 33. When the control is selected, the rear wheel steering angle δR is calculated based on the road surface μ, the steering wheel angle θH, and the vehicle speed V. The control unit 34 is configured as shown in FIGS. 21 and 22 in relation to the rear wheel steering angle calculation function.

That is, the steering valve operation control section 34
Functionally, it is provided with a pseudo steering wheel angle calculator 40 and various elements described later. In the calculation unit 40, based on the steering wheel angle θH signal supplied from the steering wheel angle sensor 16,
Pseudo steering wheel angle θ'H that has a dead zone corresponding to the assembly error of the steering wheel angle sensor (eg ± 5 °) in the neutral part
Is calculated according to the map shown in FIG.

In the in-phase coefficient calculation unit 41, the filter unit 42
Based on the vehicle speed V signal supplied from the vehicle speed sensor 26 via the vehicle, and according to the map corresponding to the vehicle speed / common-mode coefficient characteristic stored in a memory (not shown) built in the control unit 34 and indicated by a solid line in FIG. In-phase coefficient K suitable for μ path
1 is calculated. The in-phase coefficient K1 represents the ratio between the front wheel steering angle and the rear wheel steering angle, and is a predetermined vehicle speed V1 (for example, 60 km /
h) In the above vehicle speed range, the value increases as the vehicle speed V increases.

In-phase coefficient K1 calculated by the arithmetic unit 41
Is corrected in the in-phase coefficient correction unit 43 according to the road surface μ detected by the road surface μ detection unit 33 as shown by the broken line in FIG. That is, the in-phase coefficient K1 is corrected so that the in-phase coefficient K1 takes a larger value as the road surface μ decreases. In other words, the vehicle speed V is corrected so that the rising start speed V1 of the in-phase coefficient K1 becomes smaller as the road surface μ decreases (FIG. 24). As a result, the in-phase coefficient K1 suitable for the actual road surface condition and vehicle speed is obtained.

Further, the in-phase coefficient correction section 43 is supplied with an output drive indicating the degree of acne of the driver from the controller 15 as a neural network. This output drive is calculated in the same manner as in the case of the first embodiment, and the description of the calculation procedure is omitted. The in-phase coefficient correction unit 43 corrects the in-phase coefficient K1 so that the in-phase coefficient K1 takes a small value especially on the mountain road as the degree of the driver's crispness represented by the output drive increases. As a result, as shown in FIG. 28, the in-phase steering amount decreases as the degree of pimples increases.

Further, in the multiplication unit 44, a value (K1 obtained by dividing the corrected in-phase coefficient K1 by the steering gear ratio ρ
/ Ρ) is multiplied by the pseudo steering wheel angle θ'H to obtain the in-phase steering angle δ1 as the first target rear wheel steering angle in the medium and high speed range.
(= K1 · θ'H / ρ) is calculated. On the other hand, in connection with the calculation of the anti-phase steering angle δ2 as the first target rear wheel steering angle in the low speed range, the vehicle speed V signal is supplied to the anti-phase coefficient calculation unit 45 via the filter unit 42, and the road surface μ The signal is supplied to the anti-phase coefficient correction unit 46, and the pseudo handle angle θ ′ is further supplied.
The H signal is supplied to the differential calculator 47.

The calculation section 45 calculates the anti-phase coefficient K2 suitable for the high μ road according to a map (not shown).
The antiphase coefficient K2 is a value at which the vehicle speed V is relatively low (for example, 30).
When the vehicle speed V is 30
It is set to take a smaller value as the distance from km / h increases. Then, in the correction unit 46, the antiphase coefficient K2 takes a large value as the road surface μ decreases,
The antiphase coefficient K2 is corrected. Further, the correction unit 46 is supplied from the controller 15 with a neural network output drive indicating the degree of the driver's crispness. Correction unit 4
6, the anti-phase coefficient K2 increases as the driver's degree of pimples represented by the output drive increases, especially on mountain roads.
The anti-phase coefficient K2 is corrected so that the value takes a large value.
As a result, as shown in FIG. 29, the anti-phase steering amount increases as the degree of pimples increases.

The pseudo handle angle θ'H is differentiated in the differential calculator 47. Then, in the multiplication unit 48, the value (K2 / ρ) obtained by dividing the anti-phase coefficient K2 by the steering gear ratio ρ is multiplied by the differential value Δθ′H of the pseudo steering wheel angle, whereby the anti-phase steering angle δ2. Is required. When the absolute value of the anti-phase steering angle δ2 is greater than or equal to a predetermined value (for example, 0.03 °), the limiting unit 49 that inputs the anti-phase steering angle δ2 outputs the input value, while the input value is less than the predetermined value. When is smaller than 0, a value of 0 ° is output.

In relation to the yaw rate feedback control, the steering valve actuation control section 34 includes a yaw rate gain calculation section 50 for inputting the vehicle speed V signal from the vehicle speed sensor 26 via the filter 42 and various elements described later ( FIG. 22). In the calculation unit 50, high μ depending on the vehicle speed V signal.
A yaw rate gain K4 suitable for the path (μ = 1) is calculated. The gain K4 is corrected by the yaw rate correction unit 51 so as to take a smaller value as the road surface μ decreases (FIG. 26). The correction unit 51 is supplied with the neural network output drive from the controller 15. The correction unit 51 corrects the gain K4 so that the yaw rate gain K4 increases as the degree of pimples represented by the output drive increases (see FIG. 30).

Further, the time constant calculating section 52 is arranged to filter the filter section 4 according to the vehicle speed / first-order lag time constant characteristics shown in FIG.
First-order delay time constant τ according to vehicle speed V signal supplied from 2
To calculate. The time constant τ has a value that gradually decreases as the vehicle speed V increases. The neural network output drive is also supplied from the controller 15 to the time constant calculation unit 52. In the time constant calculation unit 52, the time constant τ is set to a small value as the degree of prickiness of the driver represented by the output drive increases. As a result, as shown in FIG.
The yaw rate phase delay decreases as the degree of crunch increases, and the vehicle has driving characteristics as a sporty vehicle.

In the first-order delay calculation section 53, in order to approximate the response delay of the vehicle body to the operation of the steering wheel 4,
A “first-order lag” operation is performed on the pseudo handle angle θ′H using the first-order lag time constant τ. Then, the multiplication unit 54
Then, the value (K4 / ρ) obtained by dividing the corrected yaw rate gain K4 by the steering gear ratio ρ is multiplied by the pseudo steering wheel angle θ′H for which the first-order delay has been calculated, whereby the target yaw rate Y * (= K4 / (1 + τS) θ'H / ρ) is obtained.

Then, in the subtracting section 55, the target yaw rate Y * is subtracted from the actual yaw rate signal Y from the yaw rate sensor 60. Further, in the multiplication unit 56, the deviation (Y−Y *) between the actual yaw rate and the target yaw rate is multiplied by the feedback coefficient K3, and thereby the yaw rate feedback steering angle δ3 (= K3 · (Y−Y *)) is obtained.

Further, in the subtracting section 57, the anti-phase steering angle δ2 is subtracted from the sum of the in-phase steering angle δ1 and the yaw rate feedback steering angle δ3, whereby the rear wheel steering angle δR as the second target rear wheel steering angle. Is calculated. When the rear wheel steering angle δR is calculated in this way, the steering valve operation control unit 34 outputs the operation control signal SR calculated based on the rear wheel steering angle δR to the rear wheel steering valve 10 via the output unit 35.
Send to. As a result, the valve 10 and thus the rear wheel steering actuator 11 operate so that the actual steering angles of the rear wheels 13L and 13R coincide with the rear wheel steering angle δR.

As described above, according to the method of this embodiment, the in-phase steering amount and the anti-phase steering which are the control parameters of the four-wheel steering system are controlled in accordance with the neural network output drive indicating the degree of acne as the driving operation state by the driver. By variably controlling the amount, the yaw rate gain, and the yaw rate phase delay, the driving characteristics of the vehicle can be variably adjusted according to the degree of acne. As a result, the vehicle is given the characteristics of a sporty vehicle when the degree of acne on the driver's driving operation is increased, while the vehicle is given the characteristic of a luxury vehicle if the degree of acne is decreased and the vehicle is operated slowly. Will be given. [Fourth Embodiment] The fourth embodiment relates to the third embodiment.
A four-wheel steering system having different control methods will be described. The configuration of the four-wheel steering system according to the fourth embodiment is similar to that of the third embodiment, but the description thereof will be omitted if they overlap.

In the fourth embodiment, the steering valve operation control unit 34 calculates the rear wheel steering valve operation control signal SR based on the output data from the mode determination unit 32 and the road surface μ detection unit 33. When the rear wheel phase control is selected by the unit 32, the road surface μ and the steering wheel angle θ
The rear wheel steering angle δR is calculated based on H and the vehicle speed V. The control unit 34 calculates the rear wheel steering angle δR based on the following known arithmetic expression.

ΔR = K1δF + K3 (Y-Y *) The symbols in this equation are the in-phase coefficient K1,
The feedback coefficient K3, the front wheel steering angle δF, the actual yaw rate Y, and the target yaw rate Y *. In the above formula, if the in-phase coefficient K1 and the feedback coefficient K3 (FB coefficient in Table 2) are changed according to the control law shown in Table 2, the vehicle characteristics can be changed to a luxury vehicle or a sporty vehicle. That is, if the in-phase coefficient K1 is increased without changing the feedback coefficient K3, the vehicle characteristic becomes a luxury, while the in-phase coefficient K1 is increased.
Is decreased and the feedback coefficient K3 is increased,
It has sporty vehicle characteristics.

[0097]

[Table 2]

The controller 15 calculates the in-phase coefficient K1 corresponding to the vehicle speed V according to the map corresponding to the vehicle speed / in-phase coefficient characteristics shown by the solid line in FIG. The in-phase coefficient K1 represents the ratio of the front wheel steering angle and the rear wheel steering angle, and is a predetermined vehicle speed (for example, 60 km / h).
In the above vehicle speed range, the value increases as the vehicle speed increases.

A map shown in Table 3, for example, is stored in the memory of the controller 15 in advance. In this map, an optimum increase / decrease speed V1 and a feedback coefficient V1 according to the road traffic situation and the driving condition (acne degree) are stored. K3 is set for each. Although the degree of expressway cannot be obtained from the above-described estimation method, the degree of expressway is
It is defined as a value obtained by subtracting the urban road degree from “100”.

In the map of Table 3, the road traffic conditions are
The optimum traffic situation is selected for each of the highways, mountain roads, urban roads, and congested roads with the highest degree of conformity.
In addition, the driving condition is a crispness drive “0-100”
For example, when the degree is “0 to 29”, it is “loose”, when the degree is “30 to 79”, it is “normal”, and when the degree is “80 to 100”, it is “crisp”.
It was divided into three levels in advance.

[0101]

[Table 3]

The in-phase coefficient K1 is corrected as shown by the dotted line in FIG. 31 according to the increasing / decreasing speed V1 read according to the map. That is, the in-phase coefficient K1 is corrected so that the in-phase coefficient K1 takes a large value as the increasing / decreasing speed V1 takes a positive value. In other words, the characteristic line of the map is moved so that the rising start speed "60-V1" of the in-phase coefficient K1 becomes smaller as the increase / decrease coefficient takes a positive value. As a result, the in-phase coefficient K1 suitable for the road traffic condition, the driving condition, and the vehicle speed is obtained.

From the map, the feedback coefficient K3 adapted to the road traffic condition, the driving condition and the vehicle speed is obtained.
Is required. The steering valve operation control unit 34 is configured to detect the target rear wheel steering angle δR and the rear wheel steering angle sensor 17 calculated as described above.
The operation control signal SR corresponding to the deviation from the actual rear wheel steering angle δRa is output to the rear wheel steering valve 10 via the output unit 35, whereby the rear wheel steering actuator 11
Operates so that the actual steering angles of the rear wheels 13L and 13R coincide with the rear wheel steering angle δR.

According to the above-mentioned four-wheel steering system, as shown in Table 4, steering characteristics according to road traffic conditions and driving conditions can be realized, and the driving feeling at the time of steering the rear wheels is improved.

[0105]

[Table 4]

[Fifth Embodiment] In the fifth embodiment, a four-wheel steering system having a different control method will be described with reference to the third embodiment. The configuration of the four-wheel steering system of the fifth embodiment is also similar to that of the third embodiment, but does not necessarily require the same input / output as the third embodiment. Therefore, unnecessary input / output sensors and the like can be omitted.

In the fifth embodiment, the steering valve actuation control section 34 calculates the rear wheel steering valve actuation control signal SR on the basis of the output data from the input section 30 and the mode determination section 32 as in the third embodiment. However, when the rear wheel phase control is selected by the mode determination unit 32, the rear wheel steering angle δR is calculated based on the steering wheel angle θH and the like. The control unit 34 calculates the rear wheel steering angle δR based on the following known arithmetic expression.

ΔR = K1δF-K2 (dδF / dt) Regarding the symbols in this arithmetic expression, the in-phase coefficient K1,
Anti-phase coefficient K2, front wheel steering angle δF, front wheel steering angular velocity dδF
/ Dt. In the above formula, if the in-phase coefficient K1 and the anti-phase coefficient K2 are changed according to the control rule shown in Table 5, the vehicle characteristic can be changed to a luxury vehicle or a sporty vehicle. That is, if the in-phase coefficient K1 is increased and the anti-phase coefficient K2 is decreased, the vehicle characteristic becomes luxurious, while if the in-phase coefficient K1 is decreased and the anti-phase coefficient K2 is increased, the vehicle characteristic becomes sporty. .

[0109]

[Table 5]

The controller 15 calculates the in-phase coefficient K1 corresponding to the vehicle speed V in accordance with the map corresponding to the vehicle speed / in-phase coefficient characteristics shown by the solid line in FIG. . The in-phase coefficient K1 is
It represents the ratio of the front wheel steering angle to the rear wheel steering angle, and takes a value that increases as the vehicle speed increases in a vehicle speed region of a predetermined vehicle speed (for example, 60 km / h) or higher.

Further, the controller 15 calculates the anti-phase coefficient K1 corresponding to the vehicle speed V in accordance with the map corresponding to the vehicle speed / anti-phase coefficient characteristics shown by the solid line in FIG. The anti-phase coefficient K2 has a value that increases or decreases as the vehicle speed increases in a predetermined vehicle speed range (for example, a vehicle speed range of 30 km / h to 125 km / h).

For example, the map shown in Table 6 is stored in advance in the memory of the controller 15, and this map is optimized in accordance with the road traffic situation (for example, a traffic jam road) and the driving condition of the driver (acne level). Increase / decrease speed V
1 and increase / decrease coefficient α are set respectively. In the map of Table 6, the road traffic condition is selected as the optimum traffic condition having the highest suitability for each of the expressway, the mountain road, the city road and the congested road. In addition, the driving condition is a crispness degree drive “0 to 100”, for example, a degree “0.
~ 29 "is" comfortable "and degree is" 30-79 "
When the level was “normal”, and when the degree was “80 to 100”, it was “crisp”, and the state was divided into three levels in advance.

[0113]

[Table 6]

The in-phase coefficient K1 is corrected as shown by the dotted line in FIG. 31 according to the increasing / decreasing speed V1 read according to the map in the same manner as in the fourth embodiment. That is,
As the increase / decrease speed V1 takes a positive value, the in-phase coefficient K1
The in-phase coefficient K1 is corrected so that takes a large value.
In other words, the rising start speed of the in-phase coefficient K1 is “60
The characteristic line of the map is moved so that "-V1" becomes smaller as the increase / decrease coefficient takes a positive value. As a result, the common-mode coefficient K1 suitable for road traffic conditions, driving conditions, and vehicle speeds
Is required.

The anti-phase coefficient K2 is corrected as shown by the dotted line in FIG. 32 according to the increase / decrease coefficient α read according to the map in Table 6. That is, the anti-phase coefficient K2 is corrected so that the anti-phase coefficient K2 takes a larger value as the increase / decrease coefficient α takes a value larger than “1”. In other words, the characteristic line is multiplied by α and moved based on the obtained increase / decrease coefficient α. As a result, the anti-phase coefficient K2 suitable for the road traffic condition, the driving condition, and the vehicle speed is obtained.

Thereafter, the steering valve operation control unit 34 controls the operation according to the deviation between the target rear wheel steering angle δR calculated as described above and the actual rear wheel steering angle δRa from the rear wheel steering angle sensor 17. The signal SR is output to the rear wheel steering valve 10 via the output section 35, whereby the rear wheel steering actuator 11 causes the actual steering angle of the rear wheels 13L, 13R to match the rear wheel steering angle δR. It works as intended.

As described above, also in the four-wheel steering system of the fifth embodiment, as in the case of the fourth embodiment, as shown in Table 4, the steering characteristics according to the road traffic condition and the driving condition can be realized. The driving feeling when steering the rear wheels is improved. [Sixth Embodiment] The sixth embodiment relates to the third embodiment.
A four-wheel steering system having different control methods will be described. The configuration of the four-wheel steering system of the sixth embodiment is similar to that of the third embodiment, but does not necessarily require the same input / output as the third embodiment. Therefore, unnecessary input / output sensors and the like can be omitted.

In the sixth embodiment, the steering valve actuation control section 34 calculates the rear wheel steering valve actuation control signal SR based on the output data from the input section 30 and the mode decision section 32. When the rear wheel phase control is selected by, the rear wheel steering angle δR is calculated based on the steering wheel angle θH and the yaw rate Y. Control unit 34
Calculates the rear wheel steering angle ΔR based on the following known arithmetic expression.

ΔR = aδF + bγ (a <0) In the above equation, δF and δR represent the front wheel steering angle and the rear wheel steering angle, γ represents the yaw angular velocity, and a and b represent the coefficients. The first coefficient a is a constant, for example -0.0.
A preset value of 48 is used. First coefficient a
Are stored in advance in a memory (not shown) built in the controller 15 as the control unit 34. Note that the method of calculating the first coefficient a is publicly known, and therefore description thereof will be omitted.

As the second coefficient b, a value which is preset to a value which can suppress the center-of-gravity slip angle when the vehicle is turning and which is stored in the memory is used. The second coefficient b takes a positive value in order to improve the stability of the vehicle against disturbances such as side winds and road surface irregularities applied to the vehicle. In the above formula, Table 7
The vehicle characteristic can be changed to a luxury vehicle or a sporty vehicle by changing the second relation b according to the control rule shown in FIG. That is, if the second coefficient b is increased,
While the vehicle characteristics are luxurious, the sporty vehicle characteristics can be obtained by decreasing the second coefficient b.

[0121]

[Table 7]

Further, in the memory of the controller 15, for example, the map shown in Table 8 is stored in advance,
In this map, the optimal increase / decrease degree of the second coefficient b is set according to the road traffic situation (for example, a congested road) and the driving state of the driver (acne degree). In the map shown in Table 8, the road traffic condition is selected as the optimum traffic condition having the highest suitability for each of the highway, the mountain road, the city road and the congested road. In addition, the driving condition is a crispness degree drive “0 to 100”, for example, a degree “0.
~ 29 "is" comfortable "and degree is" 30-79 "
When the level is “normal”, and when the degree is “80 to 100”, the level is “quick”, and the levels are preliminarily assigned to three levels.

[0123]

[Table 8]

The second coefficient b is corrected according to the map. For example, when the road traffic condition is a highway and the driver's driving condition, that is, the degree of acne is crisp according to the estimation method, the second coefficient b is set to be “slightly reduced”. In Table 8, “slightly decreased” means an increase / decrease degree intermediate between “normal” and “reduced”. Thereafter, the steering valve operation control unit 34 outputs the operation control signal SR according to the deviation between the target rear wheel steering angle δR calculated in this way and the actual rear wheel steering angle δRa from the rear wheel steering angle sensor 17,
The output is output to the rear wheel steering valve 10 via the output unit 35, whereby the rear wheel steering actuator 11 operates so that the actual steering angle of the rear wheels 13L, 13R matches the rear wheel steering angle δR.

As described above, also in the four-wheel steering system of the sixth embodiment, as shown in Table 4 in the same manner as in the fourth and fifth embodiments, the steering characteristics according to the road traffic situation and the driving state are shown. Can be realized, and the driving feeling at the time of steering the rear wheels is improved. [Seventh Embodiment] An embodiment of the vehicle driving characteristic control method according to the present invention will be described below.

The present embodiment is intended to control the vehicle driving characteristics to be suitable for the vehicle driving operation state (acne degree) estimated by the estimation method of the above-mentioned embodiment. The procedure of is the same as that of the above estimation method, and the description of the device configuration and the like for this is omitted. In this embodiment, an automobile equipped with a power steering device capable of variably controlling the steering force of a steering wheel will be described. The same members as those in the third embodiment are designated by the same reference numerals.

Referring to FIG. 33, there is shown a schematic configuration diagram of the power steering system, in which the front wheel 1R is connected to the piston rod 2a of the power cylinder 2 via the knuckle arm 3. That is, the power cylinder 2 is composed of a double rod type hydraulic cylinder, and the other piston rod 2a of the power cylinder 2 is also connected to the other front wheel 1L via the knuckle arm 3.

The power cylinder 2 is connected to the hydraulic pressure supply source 6 via a hydraulic circuit. Here, the hydraulic pressure supply source 6 includes a hydraulic pump 7 driven by an engine 8 of the automobile, and the hydraulic pump 7 discharges the hydraulic oil sucked from the reservoir tank 14 from its discharge port. The hydraulic circuit includes a supply pipe line 101 extending from the discharge port of the hydraulic pump 7, and the supply pipe line 101 is branched into two branch pipes 102 on the downstream side of the directional control valve 5. These branch pipes 102 are respectively connected to both pressure chambers of the power cylinder 2.

The directional control valve 5 is composed of a 4-port 3-position directional control valve with throttle (actually a rotary valve). Therefore, in three of the four ports, the supply line 101 is provided. And branch line 102 are respectively connected, and the remaining ports are connected to the return line 1
It is connected to the reservoir tank 14 via 03. Although not shown in detail, the switching operation of the directional control valve 5 is performed by operating the steering wheel 4,
As a result, the flow direction of the hydraulic oil supplied from the hydraulic pump 7 to the power cylinder 2 is controlled according to the operating direction of the steering wheel 4. Therefore, when the steering wheel 4 is steered, the power cylinder 2 is operated according to the steering direction, so that the steering force of the steering wheel 4 can be assisted. That is, as is well known, the piston rod 2a of the power cylinder 2 is adapted to be operated by the rack and pinion 104 which is interlocked with the operation of the steering wheel 4, and at this time, the power cylinder 2 is also operated simultaneously. Thus, the steering wheel 4 can be easily operated. When the steering wheel 4 is not operated, the directional control valve 5
Is in the neutral position, so that both pressure chambers of the power cylinder 2 are connected together via the directional control valve 5 to the low pressure side, that is, the reservoir tank 14. Note that, in FIG. 33, the rack of the rack and pinion 104 has an axis line of 9
It is shown as being different by 0 degrees.

The power steering control system of this embodiment further comprises a steering force varying device 105 for varying the steering force (feeling) of the steering wheel 4. The steering force varying device 105 includes an input shaft 4 a to which the rotation of the steering wheel 4 is input and an output shaft 1 integrally connected to the pinion gear side of the rack and pinion 104.
The hydraulic pump 7 is provided at the connecting portion between the hydraulic pump 7 and
It is designed to be operated by receiving the supply of hydraulic oil discharged from.

The input shaft 4a and the output shaft 104a of the steering wheel 4 are relatively rotatable within a predetermined range in advance, and the directional control valve is formed by the difference in the rotation angle between the input shaft 4a and the output shaft 104a. 5, the direction switching is performed. Although not shown in detail, the steering force varying device 105 includes a plurality of plungers that slide on the output shaft 104a side by hydraulic pressure, and these plungers are
Upon receiving the supply of hydraulic pressure, the input shaft 4a is pressed and the relative rotation between the input shaft 4a and the output shaft 104a is suppressed.

When the force of pressing the input shaft 4a of the plunger is strong, the degree of relative rotation between the input shaft 4a and the output shaft 104a is reduced, whereby the operation of the directional control valve 5 is suppressed. As a result, the steering force (feel) of the steering wheel 4 increases (becomes heavier). When the force pressing the input shaft 4a of the plunger is weak, the input shaft 4a
And the degree of relative rotation of the output shaft 104a is increased, which facilitates the operation of the directional control valve 5. As a result, the steering force (feel) of the steering wheel 4 is reduced (lightened).

By continuously changing the force pressing the input shaft 4a of the plunger, the steering force of the steering wheel 4 can be continuously changed. With respect to the hydraulic system of the steering force variable device 105, a branch pipe line 106 extending from the middle of the supply pipe line 101 connecting the hydraulic pump 7 and the directional control valve 5 is connected to the hydraulic pressure supply port of the steering force variable device 105. There is. Further, an electromagnetic pressure control valve 107 is provided in the middle of the branch pipe line 106, and the hydraulic oil discharged from the hydraulic pump 7 is supplied to the steering force varying device 105 via the pressure control valve 107. It has become so. Further, the hydraulic oil supplied to the steering force varying device 105 enters the pressure chamber of the plunger, and is discharged to the return pipe 103 via the pipe (108) through the orifice (not shown).

The operating hydraulic pressure supplied to the steering force varying device 105, that is, the pressure applied to the plunger is the pressure control valve 107.
Is adjusted based on the current value supplied to the solenoid 107a. The solenoid 107a of the pressure control valve 107 is electrically connected to the controller 15, and the controller 15 variably controls the current value supplied to the solenoid 107a. The pressure control valve 10
Although the control of No. 7 is performed by controlling the amount of current supplied to the solenoid 107a, duty control may be performed on / off the energization of the solenoid 107a.

Therefore, the steering force of the steering wheel 4 can be variably controlled by controlling the current value supplied to the solenoid 107a of the pressure control valve 107. When the current value supplied to the solenoid 107a is the maximum, the pressure control valve 107 is closed, the operating oil pressure is not supplied to the steering force varying device 105, and the input shaft 4a and the output shaft 104a rotate without resistance. . As a result, since the directional control valve 5 operates normally, the power cylinder 2 also operates normally and the steering force of the steering wheel 4 becomes light.

When the current value supplied to the solenoid 107a decreases, the valve opening amount of the pressure control valve increases in accordance with the decrease in the current value, and the operating oil pressure supplied to the steering force varying device 105 increases. The relative rotation between the input shaft 4a and the output shaft 104a is suppressed. As a result, the operation of the directional control valve 5 is suppressed, so that the operation of the power cylinder 2 is suppressed and the steering force of the steering wheel 4 becomes heavy.

In the controller 15, the vehicle speed V from the vehicle speed sensor 26 (corresponding to the above-mentioned vehicle speed signal VX), the road traffic condition information (corresponding to the above-mentioned city level r_city, etc.) and the driving state information (from the above estimation method). (Corresponding to the above-mentioned degree of crispness drive) is supplied as an input parameter. The controller 15 calculates the current value supplied to the solenoid 107a of the pressure control valve 107 based on these input parameters.

Table 9 shows steering force characteristics of the (ideal) steering wheel 4 desired depending on road traffic conditions and driving conditions.

[0139]

[Table 9]

According to Table 9, it is desirable that the steering force is light when the road traffic is an urban road and the driving condition, that is, the degree of acne is small, and the steering force is slightly heavy when the degree of acne is large. Is desirable. Further, when the road traffic condition is a highway and the degree of pimple is small, it is desirable that the steering force is slightly heavy, and when the degree of pimple is large, the steering force is heavy. Further, when the road traffic condition is a congested road, it is desirable to have a light steering force regardless of the degree of pimple. Also, the road traffic situation is mountainous,
When the degree of pimple is small, it is desirable that the steering force is light, and when the degree of pimple is large, it is desirable that the steering force is heavy.

Although the degree of the expressway in the road traffic condition is not estimated by the above-mentioned estimation method, the degree of the expressway can be defined as a value opposite to the degree of the urban road. That is, when the degree of the urban road is small, the degree of the expressway takes a large value, and when the degree of the urban road is large, the degree of the expressway takes a small value.

A vehicle speed / current characteristic map shown in FIG. 34 is previously stored in the memory of the controller 15. The controller 15 obtains a target current value according to the vehicle speed according to this characteristic map, and supplies a current to the solenoid 107a based on this target current value. In addition,
This characteristic map is set on the basis of the case where the degree of the urban road is the smallest (the degree of the expressway is large) and the degree of the acne degree is the smallest.

In a region where the vehicle speed is up to 20 km / h,
The target current value has a maximum value (for example, 1 A). In the vehicle speed range of 20 to 70 km / h, the target current value decreases from the maximum value at a constant rate as the vehicle speed increases. In the region where the vehicle speed is 70 km / h or more, the target current value is almost half the maximum value (for example, 0.5).
It becomes constant at 5A). The current value supplied to the solenoid varies depending on the solenoid standard.

Further, the controller 15 corrects the current characteristic according to changes in conditions such as road traffic conditions and driving conditions. That is, the controller 15 corrects the current characteristic as indicated by the broken line in FIG. 35, according to the degree of the input city level (r_city). That is, the target current value of the current characteristic is corrected so that the target current value takes a larger value as the degree of city area increases. As a result,
As the degree of urban area increases, the steering force of the steering wheel 4 decreases (becomes lighter).

On the other hand, the controller 15 sets the target current value to the maximum value (for example, 1 A) regardless of the driving condition, especially when the degree of traffic jam is supplied as the road traffic condition information.
Set to. As a result, the steering force of the steering wheel 4 becomes extremely light, and it is possible to obtain optimum steering characteristics for traveling on a congested road. Controller 15
Corrects the current characteristic as indicated by the broken line in FIG. 36 in accordance with the input degree of crispness drive. That is, the target current value of the current characteristic is corrected so that the target current value takes a smaller value as the degree of squeeze drive increases. As a result, the steering force of the steering handle 4 increases (becomes heavier) as the degree of crispness drive increases.

As a result of the actual vehicle test, the degree of the mountain road can be considered as an intermediate value between the degree of the city road and the highway. Therefore, the parameter for correcting the current characteristic is only the city degree (r_city). And As mentioned above,
In the power steering control device of the present embodiment, according to the degree of urban roads as road traffic conditions, by variably controlling the current supply value to the solenoid of the pressure control valve that is a control parameter of the power steering control device, The steering force characteristic of the steering wheel can be variably adjusted according to the degree of urban roads. As a result,
The steering characteristic of the steering wheel according to the road traffic situation is given to the vehicle.

Further, a neural network output drive that represents the degree of acne as a driving operation state by the driver
Accordingly, the value of the current supplied to the solenoid of the pressure control valve, which is a control parameter of the power steering control device, is variably controlled, so that the steering force characteristic of the steering wheel can be variably adjusted according to the degree of pimple. As a result, the vehicle is given a steering characteristic as a sporty vehicle when the degree of acne on the driver's driving operation is increased, while the vehicle is steered as a luxury vehicle if the degree of acne is decreased and the vehicle is operated slowly. The characteristics will be given. [Eighth Embodiment] An embodiment of the vehicle driving characteristic control method according to the present invention will be described below.

The present embodiment intends to control the vehicle driving characteristics so as to be suitable for the vehicle driving operation state (acne degree) estimated by the estimation method of the above-mentioned embodiment. The procedure of is the same as that of the above estimation method, and the description of the device configuration and the like for this is omitted. In this embodiment, a shift control device and a control method for an automatic transmission for a vehicle will be described.

FIG. 37 shows a schematic structure of an automatic transmission for an automobile according to the present invention. Reference numeral 201 in the figure denotes an internal combustion engine, and the output of this engine 201 is transmitted to drive wheels (not shown) via an automatic transmission 202. The automatic transmission 202 includes a torque converter 204, a gear transmission 203, a hydraulic circuit 205, a controller 15, and the like. The gear transmission 203 includes, for example, a gear train with four forward gears and one reverse gear, and a number of gear shift friction engagement means for performing gear shift operations by switching the gear ratio of the gear train. The shift friction engagement means is, for example, a hydraulic clutch or a hydraulic brake.

FIG. 38 is a partial block diagram of the gear transmission 203. The first drive gear 23 is provided around the input shaft 203a.
The first and second drive gears 232 are rotatably arranged. In addition, the first drive gear 231 and the second drive gear 23
Hydraulic clutches 233 and 234 are fixedly mounted on the input shaft 203a between the two as shift friction engaging means. The drive gears 231 and 232 are respectively connected to the clutch 233.
And 234 engage with each other to rotate integrally with the input shaft 203a. The intermediate transmission shaft 235 arranged in parallel with the input shaft 203a is connected to the drive axle via a final reduction gear unit (not shown). This intermediate transmission shaft 23
5 includes a first driven gear 236 and a second driven gear 237.
Is fixed, and these driven gears 236 and 2 are
37 meshes with the drive gears 231 and 232, respectively.

Therefore, when the clutch 233 and the first drive gear 231 are engaged, the rotation of the input shaft 203a is caused by the clutch 233, the first drive gear 231, the first driven gear 236, and the intermediate transmission shaft 235. The first speed is established, for example. Also, the clutch 23
4 and the second drive gear 232 are engaged, the rotation of the input shaft 203a is generated by the clutch 234 and the second drive gear 2
32, the second driven gear 237, and the intermediate transmission shaft 235, whereby the second speed is established, for example. First
From the state where the clutch 233 on the high speed side is engaged, the clutch 234 on the second speed side is engaged while releasing the engagement of the clutch 233, whereby the automatic transmission 2 shifts from the first speed to the second speed. Shift up fast. On the contrary, by engaging the clutch 233 while releasing the engagement of the clutch 234 from the state where the clutch 234 is engaged, the automatic transmission 202 shifts down from the second speed to the first speed. .

The clutches 233 and 234 are hydraulic multi-plate clutches. FIG. 39 shows a cross section of the clutch 233. The clutch 233 has a large number of friction engagement plates 2.
Has 50. Then, when hydraulic oil is supplied into the clutch 233 from the oil passage 214 to be described later through the port 251, the piston 252 moves forward and the friction engagement plates 2 are moved.
50 is frictionally engaged. On the other hand, the return spring 25
3 is pressed by the oil passage 214 through the port 251.
When the piston 252 returns while discharging the hydraulic oil therein, the frictional engagement between the frictional engagement plates 250 is released.

In order to completely release the engagement of the clutch 233, each friction engagement plate 250 may be put on standby at the standby position. At the standby position, a sufficient clearance is provided between the friction engagement plates 250 to prevent the generation of so-called drag torque. Therefore, the clutch 233
In the case of engaging with each other, first, a so-called rattling operation is performed in which each friction engagement plate 250 is moved by an ineffective stroke to a position where the above-mentioned clearance is substantially zero, that is, a position immediately before friction engagement occurs. There is a need. Therefore, the rattling operation requires a rattling time. On the other hand, in the engaged state of the clutch 233, even if the friction engagement plates 250 start to separate from each other, the drag torque described above is generated for a while. Therefore, the clutch 233 must be completely disengaged before being disengaged. After the hydraulic oil is started to be discharged from 233, a hydraulic pressure release time is required as a dead time.

The clutch 234 is also the clutch 2
It is configured similarly to 33, and requires a predetermined rattling time and hydraulic pressure release time at the time of connection and at the time of release. The hydraulic circuit 205 has a duty solenoid valve (hereinafter simply referred to as a solenoid valve) corresponding to each of the above-mentioned speed change friction engagement means, and each speed change friction engagement means, that is, each clutch or brake, is provided. Operate independently of each other. Since each solenoid valve operates each clutch and brake in the same manner, the solenoid valve that operates the clutch 233 will be described with reference to FIG. 40, and description of the other solenoid valves will be omitted.

FIG. 40 shows a part of the hydraulic circuit 205,
Solenoid valve 2 capable of supplying hydraulic pressure to hydraulic clutch 233
11 is provided. This solenoid valve 211 is a normally closed two-position switching valve and has ports 211a to 211c at three locations.
have. A first oil passage 213 extending to an oil pump (not shown) is connected to the first port 211a. An unillustrated pressure regulating valve or the like is interposed in the middle of the first oil passage 213, and the working hydraulic pressure (line pressure) regulated to a predetermined pressure is supplied.

A second oil passage 214 extending to the hydraulic clutch 233 is provided at the second port 211b, and a second oil passage 214 is provided at the third port 21b.
1c includes a third oil passage 2 extending to an oil tank (not shown).
15 are respectively connected. These second and third
In the middle of the oil passages 214 and 215, the throttles 216 and 216, respectively.
217 is provided. The flow passage area of the throttle 216 provided in the second oil passage 214 is set larger than the flow passage area of the throttle 217 provided in the third oil passage 215.
Further, the second oil passage 21 between the clutch 233 and the throttle 216
An accumulator 218 is connected in the middle of 4.

The solenoid valve 211 is connected to the controller 15
The controller 15 controls the duty ratio at a predetermined cycle, for example, a control cycle of 50 hertz. When the solenoid 211e of the solenoid valve 211 is deenergized, the valve body 21
1f is pressed by the return spring 211g to shut off the first port 211a and the second port 211b, and
The second port 211b and the third port 211c are connected. On the other hand, when the solenoid 211e is energized, the valve body 211f lifts against the spring force of the return spring 211g to allow the first port 211a and the second port 211b to communicate with each other and the second port 211a. 211b
And the third port 211c are shut off.

The controller 15 includes a ROM (not shown),
It includes a storage device such as RAM, a central processing unit (CPU), an input / output device, a counter used as a timer, and the like. On the input side of the controller 15, various sensors, for example, Nt sensor 221, No sensor 222,
The θt sensor 223 and the like are electrically connected. The N
The t sensor 221 is a turbine rotation speed sensor that detects the rotation speed Nt of the turbine of the torque converter 204 (that is, the input shaft of the gear transmission 203).

Further, the No sensor 222 (corresponding to the vehicle speed sensor 22 described above) is a transfer drive gear rotation speed sensor for detecting the rotation speed No of a transfer drive gear (not shown). The controller 15 can calculate the vehicle speed V (corresponding to the above-described vehicle speed signal vx) based on the rotation speed No. Then, the θt sensor 223 (corresponding to the above-mentioned throttle opening sensor 23) is
This is a throttle valve opening sensor for detecting a valve opening θt of a throttle valve arranged in the intake passage (not shown) of the engine 201.

Each of the sensors 221 to 223 supplies a detection signal to the controller 15 at a predetermined cycle.
Further, the controller 15 includes parameters representing road traffic conditions and driver's driving conditions calculated by the above-described estimation method (for example, congestion road degree r_jam, city road degree r_city, highway degree r_high, mountain road degree r_mount, and snoring). Drive) is supplied. “Shift change execution procedure” The storage device of the controller 15 stores in advance a procedure for determining an optimum command shift stage from the input detection signal and each parameter and executing a shift change based on this command shift stage. Has been done. The controller 15 repeatedly executes this procedure at a predetermined cycle, so that the coupling side clutch 233
And the clutch 234 on the disengagement side is operated to shift the automatic transmission 202.

The procedure for carrying out this shift change is shown in FIG.
1 and the flowchart of FIG. 42.
First, in step S60, the controller 15 determines the vehicle speed V from the vehicle speed sensor (No sensor 22) and the throttle opening θt from the throttle opening sensor (θt sensor 23).
To calculate.

Next, in step S62, the controller 15 reads in the road condition parameters r_jam, the degree of urban road r_city, the degree of highway r_high and the degree of mountain road r_mount, which are the road condition parameters calculated by the estimation method, and
The read input value is converted from "0-100" to "0-10". Further, the controller 15 reads the degree of acne drive, which is the operating state parameter calculated by the estimation method, and sets the read input value to “0”.
˜100 ”to“ 0-10 ”.

Although the highway degree r_high is not calculated by the estimation method, it can be inferred to take a value opposite to the urban road degree r_city. Therefore, the expressway degree r_high is defined as “10” minus the value of the urban road degree r_city. In step S64, the controller 15 calculates the road gradient RS based on a gradient sensor mounted on the vehicle or a sensor signal from an engine output and acceleration (not shown).

At step S66, the controller 15
Determines whether or not the obtained congestion degree r_jam is the maximum value "10", and if the determination result is affirmative, executes step S68. In step S68, the controller 15 determines that the vehicle speed V is a predetermined vehicle speed V0 (for example, 40 km /
It is determined whether or not it is smaller than h), and if the determination result is affirmative, step S70 is executed.

At step S70, the shift command variable SHIF
T0 becomes "2", and the controller performs a shift change based on a preset second-speed hold shift map. The shift map for the second speed hold is shown in FIG.
As shown in FIG. 3, a part of the 2 → 3 upshift line is moved to the high speed side to widen the vehicle speed region for maintaining the 2nd speed, and the 2 → 1 downshift line is not provided.

Therefore, when the road traffic condition is "congested road running" and the vehicle speed is 40 km / h, 2
According to the shift map for the speed hold, the shift stage is in the second speed hold state. In the second speed hold state, even if the vehicle speed temporarily becomes "0" and the vehicle is stopped, the second speed state is maintained, and even if the vehicle is frequently stopped and started, there is no shift shock and the vehicle is smooth. It is possible to start,
It becomes possible to obtain appropriate engine braking during deceleration.

On the other hand, when the result of the determination in step S66 is negative, the shift pattern moving mode is set and step S72 is executed. In step S72, the controller 15 determines whether or not the urban road degree r_city is the maximum value “10”, and if the determination result is affirmative, step S
Perform 74. If the determination result in step S68 is negative, that is, if the vehicle speed is 40 km / h or more even if it is determined to be a traffic jam, the controller 15
The second speed hold mode is released to enter the shift pattern movement mode, and step S74 is executed.

At step S74, the controller 15
Is the degree of acne based on the city map shown in FIG.
The shift line movement coefficient KM is obtained from the relationship between drive and road gradient RS. The range of the shift line movement coefficient KM is, for example, 0 to 1.0. On the other hand, when the determination result in step S72 is negative, the process proceeds to step S78, and in step S76, the controller 15 causes the highway degree r_hi.
It is determined whether or not gh is the maximum value "10", and if the determination result is affirmative, step S78 is executed.

In step S78, the controller 15
Is the shift line movement coefficient KM based on the relationship between the degree of acne drive and the road gradient RS based on the highway map shown in FIG.
Ask for. Further, when the determination result in step S76 is negative, the process proceeds to step S80, and in step S80, the controller 15 determines from the relationship between the acne degree drive and the road gradient RS based on the mountain road map shown in FIG. The shift movement line coefficient KM is obtained.

After any of step S74, step S78 and step S80 is executed, the controller 1
In step S82, 5 executes a command shift stage SHIFT0 calculation routine. The shift line movement coefficient KM obtained in the above steps has a large degree of uphill of the road gradient RS and the degree of pimple driv that represents the driving state of the driver.
It takes a large value when e is large. In addition, the value of the shift line movement coefficient KM increases in the order of the road traffic condition of the highway, the city road, and the mountain road. "Command shift stage calculation routine", FIG. 47 and FIG.
Referring to FIG. 8, the procedure for executing the command shift stage SHIFT0 calculation routine (shift line moving means) will be described with reference to the flowchart of FIG. Note that, in explaining this procedure, the current shift stage is in the second speed state (command shift stage SHIFT0 = “2”).

In the memory device of the controller 15, 1 →
2,2 → 3,3 → 4 Upshift maps divided for each upshift line and 4 → 3,3 → 2,2 → 1 Downshift maps divided for each downshift line Two basic types of base shift maps are stored. Further, each shift line has two types of basic shift patterns: a mild pattern for realizing a gentle shift change and a sports pattern for realizing a light shift change.

Note that FIG. 47 shows only the 2 → 3 upshift lines, for example, and FIG. 48 shows only the 2 → 1 downshift lines, for example. Since the other shift lines are the same, the description is omitted. In this routine, the determination vehicle speed (NOU, NOD) is obtained from the throttle opening θt and the obtained shift line movement coefficient KM,
The command shift speed SHIFT0 is determined from the judgment vehicle speed.

First, in step S84, the controller 15 obtains the vehicle speed value NOUS corresponding to the actual throttle opening θt 'from the sports pattern of the upshift line as shown in FIG. Next, in step S86, the controller 15 similarly obtains the vehicle speed value NOUM corresponding to the actual throttle opening θt ′ from the mild pattern of the upshift line.

In step S88, the controller 15
Substitutes the shift line movement coefficient KM, the vehicle speed value NOUS and the vehicle speed value NOUM obtained in the above steps into the following arithmetic expression to obtain the upshift speed NOU. NOU = NOUM + KM · (NOUS-NOUM) Since the range of the shift line movement coefficient KM is “0 to 1.0”, the upshift speed N obtained from this arithmetic expression
OU is determined between the vehicle speed value NOUM and the vehicle speed value NOUS.

For example, the shift line movement coefficient KM is "0".
At this time, the upshift speed NOU becomes equal to the vehicle speed value NOUM. In other words, the upshift line has a mild pattern. On the other hand, when the shift line movement coefficient KM is "1.0", the upshift speed NOU becomes equal to the vehicle speed value NOUS. That is, the upshift line becomes a sports pattern.

When the shift line movement coefficient KM changes from "0 to 1.0", the upshift speed NOU is the vehicle speed value NOUM.
To the vehicle speed value NOUS. Assuming that the shift movement coefficient KM is kept constant and the throttle opening θt is arbitrarily changed, the dashed-dotted upshift line shown in FIG. 47 is virtually obtained.

Therefore, the upshift line is corrected based on the shift line movement coefficient KM. When the value of the shift line movement coefficient KM changes from "0 to 1.0", the upshift line moves from the mild pattern to the sports pattern in the right direction in the figure, as indicated by the broken line in FIG.

Next, in step S90, the controller 15 obtains the vehicle speed value NODS corresponding to the actual throttle opening θt 'from the downshift line of the sports pattern shown in FIG. In step S92, similarly,
The controller 15 determines the vehicle speed value NOD corresponding to the actual throttle opening θt ′ from the downshift line of the mild pattern.
Ask for M.

In step S94, the controller 15
Calculates the upshift speed NOD by substituting the shift line movement coefficient KM, the vehicle speed value NODS and the vehicle speed value NODS obtained in the above steps into the following arithmetic expression. NOD = NODM + KM · (NODS−NODM) Since the range of the shift line movement coefficient KM is “0 to 1.0”, the downshift speed N obtained from this arithmetic expression
OD is determined between the vehicle speed value NODM and the vehicle speed value NODS.

For example, the shift line movement coefficient KM is "0".
At this time, the downshift speed NOD becomes equal to the vehicle speed value NODM. In other words, the downshift line has a mild pattern. On the other hand, when the shift line movement coefficient KM is "1.0", the upshift speed NOD becomes equal to the vehicle speed value NODS. That is, the downshift line becomes a sports pattern.

When the shift line movement coefficient KM changes from "0 to 1.0", the downshift speed NOD is the vehicle speed value NODM.
To the vehicle speed value NODS. Assuming that the shift movement coefficient KM is kept constant and the throttle opening θt is arbitrarily changed, the dashed-dotted downshift line shown in FIG. 48 is virtually obtained.

Therefore, the downshift line is corrected based on the shift line movement coefficient KM. When the value of the shift line movement coefficient KM changes from "0 to 1.0", the downshift line moves from the mild pattern to the sports pattern in the right direction in the figure as shown by the broken line in FIG. .

Next, in step S96, the controller 15 determines whether or not the actual vehicle speed V read by the vehicle speed sensor is higher than the upshift speed NOU obtained in step S88, and the result of the determination is affirmative. If there is, step S98 is executed. In step S98, the controller 15 adds 1 to the value of the command shift stage SHIFT0. As a result, the controller 15 determines that the command shift stage is
Upshift is performed based on the value of SHIFT0. In the case of this embodiment, the command shift stage SHIFT0 is "2" to "3".
Therefore, the 2 → 3 upshift is performed.

On the other hand, when the determination result in step S96 is negative, the controller 15 determines in step S100 whether or not the actual vehicle speed V is lower than the downshift speed NOD obtained in step S94. If the determination result is affirmative, step S102 is performed.
In step S102, the controller 15 subtracts 1 from the value of the command shift stage SHIFT0. As a result, the controller 15 carries out the downshift based on the value of the command shift stage SHIFT0. In the case of this embodiment, since the command shift stage SHIFT0 changes from "2" to "1", the 2 → 1 downshift is executed.

If the determination result in step S100 is negative, the value of the command shift stage SHIFT0 is maintained as it is, and the command shift stage SHIFT0 calculation routine ends. As described above, according to the shift control device for an automatic transmission for a vehicle of the present invention, the road traffic condition and the driving condition (crimp degree drive) and the road gradient R obtained by the estimation method are used.
The shift line movement coefficient KM is determined according to S, and the shift map obtained by moving (correcting) the upshift line and the downshift line based on the shift line movement coefficient KM is obtained. Then, the command shift stage SHIFT0 is determined based on this shift map, and the shift change is executed. Therefore, a suitable shift feeling can be obtained according to road traffic conditions and driving conditions.

For example, when traveling on a steep slope on a mountain road in a cramped state, both the upshift line and the downshift line of the shift map are moved to the sport pattern side, which results in a light shift change. As a result, the shift feeling becomes crisp. Further, when the vehicle is traveling on a flat highway in a relaxed state, both the upshift line and the downshift line of the shift map are moved to the mild pattern side, which results in a gradual shift change. As a result, the shift feeling is relaxed. [Ninth Embodiment] An embodiment of the vehicle driving characteristic control method according to the present invention will be described below.

The present embodiment is intended to control the vehicle driving characteristics to be suitable for the vehicle driving operation state (acne degree) estimated by the estimation method of the above-mentioned embodiment. The procedure of is the same as that of the above estimation method, and the description of the device configuration for this is omitted. In the present embodiment, an automobile equipped with an engine output control device as a device for variably controlling the vehicle driving characteristics will be described.

Referring to FIG. 51, in the middle of the intake pipe 301 connected to the combustion chamber (not shown) of the vehicle engine,
A throttle body 304 incorporating a slot valve 303 that changes the opening of an intake passage 302 formed by the intake pipe 301 and adjusts the amount of intake air supplied into the combustion chamber is interposed. A throttle shaft of the throttle valve 303 is rotatably supported by a throttle body 304, and the throttle shaft is rotated according to the depression amount of an accelerator pedal 305. Then, by rotating the throttle shaft, the throttle valve 3
03 is rotated in the opening direction. The driving torque of the engine is increased according to the opening degree of the throttle valve 303.

The throttle valve 303 is the accelerator pedal 3
Apart from the operation of 05, it is also operated by an actuator 306 provided on the throttle body 304. Although the throttle valve 303 is operated by the actuator 306, the throttle valve 306 is not opened unless the accelerator pedal 305 is depressed.

When the actuator 306 is not operating, the opening degree of the throttle valve 303 depends on the accelerator pedal 30.
It corresponds to the depression amount of 5 on a one-to-one basis. Actuator 3
When 06 operates, the throttle valve 303 is closed regardless of the depression amount of the accelerator pedal 305, and the engine drive torque is forcibly reduced.
In this way, by adjusting the operation of the actuator 306, the opening degree of the throttle valve 303 can be changed regardless of the depression amount of the accelerator pedal 305, and the drive torque of the engine can be arbitrarily adjusted.

The operation of the actuator 306 is controlled by the controller 15. The controller 15 controls the operation of the actuator 306 based on an output signal output from a torque calculation unit 307 (hereinafter referred to as TCL 307) that calculates a target drive torque of the engine. In practice, the controller 15 is designed to duty-control a torque control solenoid valve (not shown) that controls the operation of the actuator 306.

In this embodiment, when the lateral acceleration generated in the turning vehicle exceeds a preset value, the drive torque of the engine is reduced to prevent the vehicle from departing from the turning circuit. . The target drive torque of the engine when performing this control is calculated by TCL307,
The engine drive torque can be reduced as needed. Hereinafter, the process until the TCL 307 calculates the target drive torque will be described based on the block diagram of FIG. 52.

The TCL 307 has a target lateral acceleration calculating section 308 for calculating the target lateral acceleration. The target lateral acceleration calculation unit 308 is supplied with the vehicle speed V from the vehicle speed sensor 26 and the steering angle δ of the front wheels from the steering angle sensor as parameters, respectively, and the target lateral acceleration calculation unit 308 uses the parameters based on these parameters. Calculate the target lateral acceleration GYO from the following formula. Then, the calculated target lateral acceleration GYO is output to the target longitudinal acceleration calculation unit 309.

GYO = δ / [ω · {A + (1 / V ² )}] where ω is the wheelbase of the vehicle, A is the stability of the vehicle determined by the configuration of the suspension system, tire characteristics, road surface conditions, etc. Is a factor. The target longitudinal acceleration calculation unit 309 sets an acceleration in the vehicle longitudinal direction that prevents the vehicle from undergoing extreme under-steering, that is, a target longitudinal acceleration Gxo based on the target lateral acceleration GYO.

That is, in the target longitudinal acceleration calculating section 309, based on the vehicle speed V and the input target lateral acceleration GYO, T
The target longitudinal acceleration Gxo is read from the map shown in FIG. 53 stored in advance in the CL 307, and the target longitudinal acceleration Gxo is output to the correction unit 310. The road gradient correction amount calculation unit 311 supplies the road gradient correction amount parameter to the correction unit 310, and the correction unit 310 corrects the target longitudinal acceleration Gxo input based on this parameter, and the torque conversion unit 312. Output to. The road gradient correction amount calculation unit 311 calculates the road gradient correction amount parameter based on the vehicle speed V and the road gradient data.

Therefore, the torque conversion unit 312 is supplied to the target longitudinal acceleration G corrected in consideration of the vehicle speed and the road gradient.
xo will be output. Next, the torque conversion unit 31
In 2, first, the reference drive torque TB is calculated from the following equation based on the input target longitudinal acceleration Gxo. TB = (Gxo.Wb.r + TL) / (. Rho.m.rho.d.rho.T) where TL is the road-load torque which is the resistance of the road surface obtained as a function of the lateral acceleration GL of the vehicle. For example, FIG. I'm asking from the map.

Next, the torque conversion unit 312 calculates the target drive torque Toc from the following formula based on the reference drive torque TB. Toc = α ・ TB + (1-α) ・ Td where Td is the required drive torque, which is based on the engine speed NE detected by the crank angle sensor and the accelerator opening θA detected by the accelerator opening sensor. The required drive torque Td desired by the driver is obtained from the map of FIG. 55 stored in TCL. α is a weighting coefficient and is set empirically by turning the vehicle, but on a high μ road, for example, at a value set to about 0.6, the engine target set at a predetermined cycle is set. When the increase / decrease amount of the driving torque Toc is very large, a shock is generated due to the downward deceleration of the vehicle, which leads to a decrease in the riding comfort. Therefore, the increase / decrease amount of the target driving torque Toc of the engine changes the riding comfort of the vehicle. If the target drive torque Toc becomes large enough to cause a decrease, it is necessary to regulate the increase / decrease amount of the target drive torque Toc.

The target drive torque Toc obtained as described above is further output to the torque change amount clip section 313, and its increase / decrease amount is restricted. In the torque change amount clipping unit 313, the target drive torque Toc calculated this time is calculated.
If the absolute value | ΔT | of the difference between (n) and the previously calculated target drive torque Toc (n-1) is smaller than the predetermined clip amount Tk, the calculated current target drive torque Toc ( n) is adopted as it is, but the target drive torque Toc calculated this time is used.
When the value ΔT obtained by subtracting the previously calculated target drive torque Toc (n-1) from (n) is smaller than the negative first clip amount Tk, that is, when the target drive torque Toc needs to be rapidly reduced. Sets the target drive torque Toc of this time by the following equation.

Toc (n) = Toc (n-1) -Tk That is, the reduction amount with respect to the previously calculated target drive torque Toc (n) is regulated by the clip amount Tk, and the deceleration shock caused by the reduction of the drive torque of the engine is suppressed. ease. On the other hand, the value ΔT obtained by subtracting the target drive torque Toc (n-1) calculated last time from the target drive torque Toc (n) calculated this time is the clip amount Tk.
In the above case, that is, when it is necessary to rapidly increase the target drive torque Toc, the clip amount Tk is added to the previous target drive torque Toc (n-1) and the current target drive torque Toc (n) is added. Is set by the following formula.

Toc (n) = Toc (n-1) + Tk That is, the value ΔT obtained by subtracting the target drive torque Toc (n-1) calculated last time from the target drive torque Toc (n) calculated this time is the clip amount Tk. If the value exceeds the target drive torque Toc (n-1) calculated last time, the increase amount is restricted by the clip amount Tk to reduce the acceleration shock due to the increase in the engine drive torque, and to reduce the accelerator pedal when the driver depresses the accelerator pedal. We are trying to improve the acceleration performance over the conventional one.

The clip amount is input from the clip amount calculation unit 314 to the torque change amount clip unit 313.
The clip amount calculation unit 314 calculates the clip amount from the map shown in FIG. 56 stored in advance in the TCL 307 based on the degree of acne in the operating state from the above estimation method, and the clip amount is calculated as the torque change amount clip unit 313.
Is output to.

Therefore, the torque change amount clip portion 31
In No. 3, the target drive torque Toc is regulated based on the clip amount calculated according to the degree of crunch of the driver. Then, the target drive torque Toc corrected by the torque change amount clipping unit 313 is output to the throttle opening control unit 315 in the controller 15, and the throttle opening control unit 315 causes the actuator 306 to operate based on the target drive torque Toc. Control the operation of. According to the present embodiment, it becomes possible to control the engine output according to the degree of pimples, and more sharp turning traveling is realized.

The present invention is not limited to the above embodiment, but can be variously modified. For example, in the embodiment relating to the estimation method, the vehicle speed, the accelerator opening, the longitudinal acceleration and the lateral acceleration are used as frequency distribution (frequency analysis) detection target parameters, and the average value and variance of the frequency distribution are used as input parameters to the neural network. However, it is not essential to use all of these parameters when implementing the estimation method of the present invention, and the use of other parameters is not excluded.

Further, in the present embodiment, the parameter representing the road traffic condition was obtained by fuzzy inference, but this is not essential. In the embodiment of the vehicle driving characteristic control method, in order to easily achieve the neural network function by the controller 15, the weighted sum of the parameters respectively input to the controller 15 as the neural network is obtained as the output parameter from the neural network. However, in the neural network, the output parameter may be obtained by non-linearly converting the weighted sum of the input parameters.

Also, the controller 15 in each embodiment is
It may be provided for each control device.

[0206]

According to the method for estimating a vehicle driving operation state of the present invention, a plurality of vehicle driving parameters are detected, each average value of the plurality of vehicle driving parameters is obtained, and the road traffic condition during the vehicle traveling is determined. By estimating the average value and the road traffic condition as an input parameter, the output parameter representing the vehicle driving operation state by the driver is obtained based on the weighted sum of the plurality of input parameters. It is possible to estimate the vehicle driving operation state of the driver, which is difficult to be expressed directly, for example, the degree of acne in the vehicle driving operation of the driver.

According to a particular aspect of the present invention, the plurality of vehicle driving parameters are detected, the respective variance values of the plurality of vehicle driving parameters are obtained, and the road traffic condition during the vehicle running is estimated to obtain the respective variances. Since the output parameter indicating the vehicle driving operation state by the driver is obtained based on the weighted sum of the plurality of input parameters using the value and the road traffic condition as input parameters, a more appropriate estimation result can be obtained.

According to the particular aspect of the present invention, since the plurality of vehicle driving parameters include the vehicle speed, the accelerator opening, and the longitudinal acceleration and lateral acceleration of the vehicle, the vehicle driving operation state can be properly estimated. Further, according to the aspect in which the vehicle speed and the steering wheel angle are detected, the longitudinal acceleration is calculated from the detected vehicle speed, and the lateral acceleration is calculated from the detected vehicle speed and the steering wheel angle, the number of sensors required for implementing the estimation method of the present invention can be increased. Can be reduced.

Further, according to the mode in which the vehicle speed is detected and the longitudinal acceleration is calculated from the detected vehicle speed, the number of sensors required for the estimation method of the present invention can be further reduced. According to the aspect using the neural network, the estimation of the vehicle driving operation state can be performed relatively easily. In addition to the input parameters that characterize the frequency distribution of vehicle driving parameters, according to the aspect of using the input parameters that represent road traffic conditions such as the degree of urban area, the degree of congested road, and the degree of mountain road, according to the aspect of estimating the vehicle driving operation state, The influence of the traffic situation on the vehicle driving operation state is reflected, and a more appropriate estimation result can be obtained.

Further, according to the aspect in which the road traffic condition is determined based on the average speed, the traveling time ratio and the average lateral acceleration, the road traffic condition can be accurately grasped and the vehicle driving operation condition can be accurately estimated. According to the vehicle driving characteristic control method of the present invention, the device for variably controlling the vehicle driving characteristic mounted on the vehicle is drive-controlled in accordance with the output parameter. It is possible to control the vehicle so that it is suitable for the estimation result, and thus it is possible to drive the vehicle which is suitable for the overall vehicle driving state including the vehicle driving operation state by the driver and the road traffic state.

According to the specific mode of applying the vehicle driving characteristic control method to the engine output control device, the limit change amount is changed according to the output parameter. It can be controlled to fit the estimation result. Further, according to the specific aspect of the vehicle driving characteristic control method of the present invention, the device for variably controlling the vehicle driving characteristic is drive-controlled according to the output parameter thus obtained and the road traffic condition. The vehicle driving characteristics required by individual drivers according to changes in road traffic conditions are realized.

According to the specific mode in which the vehicle driving characteristic control method is applied to the rear wheel steering control device, the coefficient for obtaining the rear wheel steering angle is variably set according to the output parameter and the road traffic condition. Therefore, it is possible to control the rear wheel steering characteristics of the rear wheel steering control device so as to be suitable for the estimation result of the vehicle driving operation state and the road traffic condition. According to the specific aspect in which the vehicle driving characteristic control method is applied to the power steering device, the steering force of the steering wheel is variably set according to the output parameter and the road traffic condition. Can be controlled according to the estimation result of the vehicle driving operation state and the road traffic condition.

According to a particular mode in which the vehicle driving characteristic control method is applied to the shift control device for an automatic transmission, the shift map is variably set according to the output parameter and the road traffic condition. It is possible to control the shift feeling of the device to be suitable for the estimation result of the vehicle driving operation state and the road traffic situation. According to the specific aspect in which the vehicle driving characteristic control method is applied to the suspension device, the damping force of the suspension is variably set according to the output parameter and the road traffic condition. It is possible to perform control so as to be suitable for the estimation result of the driving operation state and the road traffic condition.

[Brief description of drawings]

FIG. 1 is a conceptual diagram showing a road traffic condition grasping procedure in an embodiment of a method for estimating a vehicle driving operation state according to the present invention.

FIG. 2 is a conceptual diagram showing a driving operation state grasping procedure in the embodiment.

FIG. 3 is a schematic block diagram showing a controller and a sensor for carrying out the estimation method according to the embodiment.

4 is a flowchart of a traveling time ratio calculation routine executed by the controller shown in FIG.

FIG. 5 is a flowchart showing an average speed calculation routine executed by a controller.

FIG. 6 is a flowchart of an average lateral acceleration calculation routine executed by the controller.

FIG. 7 is a graph showing a membership function that defines a fuzzy set regarding a traveling time ratio.

FIG. 8 is a graph showing a membership function that defines a fuzzy set for average speed.

FIG. 9 is a graph showing an example of calculating the matching degree of the actual traveling time ratio with respect to the traveling time ratio fuzzy set.

FIG. 10 is a graph showing an example of calculating the fitness of the actual average speed for the average speed fuzzy set.

FIG. 11 is a graph illustrating an average lateral acceleration / mountain road degree map.

12 is a flowchart of a frequency analysis routine executed by the controller of FIG.

FIG. 13 is a graph showing an array forming a population of input data as a frequency analysis target.

FIG. 14 is a conceptual diagram showing a processing element that constitutes a neural network.

FIG. 15 is a conceptual diagram of a neural network including the processing elements shown in FIG.

16 is a flow chart showing a degree of acne degree calculation routine executed by the controller of FIG.

FIG. 17 is a vehicle driving operation state (road traffic situation) of the present invention.
It is a conceptual diagram which shows the other Example of the estimation method of.

FIG. 18 is a schematic diagram showing a main part of a four-wheel steering system according to the present invention.

19 is a functional block diagram showing a configuration related to a four-wheel steering function of the controller of FIG.

20 is a functional block diagram showing in detail the configuration of the road surface μ detection unit in FIG.

21 is a functional block diagram showing in detail a part of a configuration related to a rear wheel steering angle calculation function of the steering valve operation control unit of FIG.

FIG. 22 is a functional block diagram showing the rest of the configuration of the steering valve operation control unit.

FIG. 23 is a pseudo steering wheel angle θ′H based on the steering wheel angle θH.
It is a graph which shows the map used for the calculation of.

FIG. 24 is a graph showing a map used for calculation of the in-phase coefficient K1 based on the vehicle speed V and correction of the in-phase coefficient K1 according to the road surface μ.

FIG. 25 is a graph showing the relationship between the road surface μ and the rising start speed V1 of the in-phase coefficient K1.

FIG. 26 is a graph showing a map used for calculation of yaw rate gain K4 based on vehicle speed V and correction of yaw rate gain K4 according to road surface μ.

FIG. 27 is a graph showing a map used for calculating a first-order lag time constant τ based on a vehicle speed V.

FIG. 28 is a graph showing the correction of the vehicle speed / in-phase steering amount characteristic performed in accordance with the increase in the degree of crunch.

FIG. 29 is a graph showing the correction of the vehicle speed / reverse-phase steering amount characteristic performed in accordance with the increase in the degree of crunch.

FIG. 30 is a graph showing selection of yaw rate gain / yaw rate phase delay characteristics performed according to the degree of crunch.

FIG. 31 is a map showing the relationship between vehicle speed and in-phase coefficient characteristic.

FIG. 32 is a map showing the relationship between vehicle speed and anti-phase coefficient characteristic.

FIG. 33 is a schematic configuration diagram of a power steering device according to the present invention.

FIG. 34 is a graph showing current characteristics with respect to vehicle speed (small urban area degree, small degree of cracking).

FIG. 35 is a graph showing current characteristics (increase in urban area) with respect to vehicle speed.

FIG. 36 is a graph showing current characteristics (acne degree) with respect to vehicle speed.

FIG. 37 is a schematic configuration diagram showing a shift control device for an automatic transmission of a vehicle according to the present invention.

38 is a schematic configuration diagram showing a part of a gear train in the gear transmission of FIG. 37. FIG.

FIG. 39 is a diagram showing the clutch of FIG. 37.

FIG. 40 is a schematic configuration diagram showing a part of a hydraulic circuit for operating the clutch of FIGS. 38 and 39.

FIG. 41 is a flowchart of a shift control routine.

FIG. 42 is a flowchart of a command shift stage SHIFT0 calculation routine.

FIG. 43 is a shift map for the second speed hold mode.

FIG. 44 is an urban road map for calculating the shift line movement coefficient KM based on the relationship between the degree of crunch and the gradient.

FIG. 45 is a highway map for calculating the shift line movement coefficient KM based on the relationship between the degree of crunch and the gradient.

FIG. 46 is a mountain road map for calculating a shift line movement coefficient KM based on the relationship between the degree of crunch and the gradient.

FIG. 47 is a shift map showing some upshift lines.

FIG. 48 is a shift map showing some downshift lines.

FIG. 49 is a shift map showing moving upshift lines.

FIG. 50 is a shift map showing moving downshift lines.

FIG. 51 is a schematic diagram showing a main part of an engine output control device.

FIG. 52 is a block diagram of a torque calculation unit (TCL).

FIG. 53 is a map showing the relationship between vehicle speed, target lateral acceleration, and target longitudinal acceleration.

FIG. 54 is a map showing a relationship between lateral acceleration and road load torque.

FIG. 55 is a map showing the relationship among engine speed, required drive torque, and accelerator opening.

FIG. 56 is a map showing the relationship between the degree of crunch and the clip amount.

[Explanation of symbols]

 4 Steering Handle 15 Controller 16 Steering Wheel Angle Sensor 26 Vehicle Speed Sensor 34 Steering Valve Actuation Control Unit 60 Yaw Rate Sensor 104 Throttle Opening Sensor 201 Input Layer of Neural Network 203 Output Layer of Neural Network

─────────────────────────────────────────────────── ─── Continuation of the front page (51) Int.Cl. ⁶ Identification code Internal reference number FI Technical display location B62D 101: 00 103: 00 109: 00 111: 00 113: 00 137: 00 (72) Inventor Tani Masanori Mitsubishi Motors Co., Ltd., 3-8-3, Shiba, Minato-ku, Tokyo (72) Inventor Kiyosuke Sano 5-33-8, Shiba, Minato-ku, Tokyo (72) Inventor, Masahito Hira 5-3-33, Shiba, Minato-ku, Tokyo Within Mitsubishi Motors Corporation (72) Inventor Takashi Teshima 5-33-8, Shiba, Minato-ku, Tokyo Within Mitsubishi Motors Corporation

Claims (19)

[Claims] 1. A plurality of vehicle driving parameters are detected, respective average values of the plurality of vehicle driving parameters are obtained, and road traffic conditions during vehicle traveling are estimated, and the respective average values and road traffic conditions are input parameters. As a method for estimating a vehicle driving operation state, an output parameter representing a vehicle driving operation state by the driver is obtained based on a weighted sum of the plurality of input parameters. 2. A plurality of vehicle driving parameters are detected, respective variance values of the plurality of vehicle driving parameters are obtained, road traffic conditions are estimated when the vehicle is running, and the respective variance values and road traffic conditions are input parameters. As a method for estimating a vehicle driving operation state, an output parameter representing a vehicle driving operation state by the driver is obtained based on a weighted sum of the plurality of input parameters. 3. The vehicle driving operation state estimating method according to claim 1, wherein the plurality of vehicle driving parameters include a vehicle speed, an accelerator opening, and a longitudinal acceleration of the vehicle. 4. The method for estimating a vehicle driving operation state according to claim 3, wherein the vehicle speed is detected, and the longitudinal acceleration is calculated from the detected vehicle speed. 5. The method for estimating a vehicle driving operation state according to claim 3, wherein the plurality of vehicle driving parameters further include lateral acceleration. 6. The method for estimating a vehicle driving operation state according to claim 5, wherein the vehicle speed and the steering wheel angle are detected, and the lateral acceleration is calculated from the detected vehicle speed and the steering wheel angle. 7. The vehicle driving operation state estimating method according to claim 1, wherein the output parameters are obtained by inputting the plurality of input parameters into a neural network. 8. The vehicle driving method according to claim 1 or 2, wherein a weighted sum of the plurality of input parameters is obtained so that the output parameter represents a degree of acne in a vehicle driving operation of a driver. Method of estimating operation state. 9. The method for estimating a vehicle driving operation state according to claim 1 or 2, wherein the plurality of vehicle driving parameters are weighted to obtain a frequency distribution. 10. A plurality of second input parameters representing road traffic conditions are obtained based on a plurality of preset fuzzy rules or maps and the detected vehicle traveling state parameters, and the plurality of input parameters and the aforesaid The output parameter is obtained based on a weighted sum of a plurality of second input parameters.
Alternatively, the vehicle driving operation state estimating method according to claim 2. 11. The method according to claim 10, wherein the road traffic condition includes an urban area degree and a congestion road degree, and the traveling state parameter includes an average speed and a traveling time ratio. 12. The method according to claim 11, wherein the road traffic condition further includes a mountain road degree, and the traveling condition parameter further includes an average acceleration. 13. A device for variably controlling a vehicle driving characteristic, which is mounted on a vehicle, is drive-controlled according to the output parameter obtained by the vehicle driving operation state estimating method according to claim 1. A vehicle driving characteristic control method characterized by the above. 14. A turning state detecting means for detecting a turning state of the vehicle, a target drive torque setting means for setting a target drive torque of the vehicle based on the turning state detected by the previous state detecting means, and the target drive torque. When the change amount of the target drive torque set by the setting unit exceeds a predetermined limit change amount, the change amount of the drive torque change limit unit limits the change amount to the limit change amount; It is applied to an engine output control device having an engine output control means for controlling the output of the engine based on a target drive torque, and changing the limit change amount of the drive torque change amount control means according to the output parameter. 14. The vehicle driving characteristic control method according to claim 13. 15. A device for variably controlling a vehicle driving characteristic, which is mounted on a vehicle, and outputs the output parameter and the road traffic condition obtained by the vehicle driving operation state estimating method according to claim 1. 14. The vehicle driving characteristic control method according to claim 13, wherein the driving control is performed according to 16. A rear wheel steering control device for controlling rear wheel steering based on the rear wheel steering angle by multiplying a front wheel steering state and a vehicle operating parameter by a coefficient to determine a rear wheel steering angle, wherein the coefficient 16. The vehicle driving characteristic control method according to claim 15, wherein is set variably according to the output parameter and road traffic conditions. 17. A power steering device adapted to variably control a steering force of a steering wheel of a vehicle according to a vehicle speed, wherein the steering force is variably set according to the output parameter and road traffic conditions. The vehicle driving characteristic control method according to claim 15. 18. A shift control device for an automatic transmission that performs shift control based on a shift map determined by a vehicle speed and a throttle opening, wherein the shift map is changed according to the output parameter and road traffic conditions. 16. The setting is performed.
Of vehicle driving characteristics control method. 19. The vehicle driving system according to claim 15, which is applied to a suspension device that variably controls a damping force of a wheel suspension, and the damping force is variably set according to the output parameter and road traffic conditions. Characteristic control method.