JPH07186993A - Power steering controller - Google Patents

Abstract

PURPOSE:To secure a stable steering characteristic on the whole in time of car traveling by recognizing the driving state of a driver from those of car speed, accelerator opening and acceleration, and according to the recognition, variably setting the steering force. CONSTITUTION:Those of car speed from a car speed sensor 26, urban area degree and brish drive degree from a specified estimation method are fed to a controller 15 as input parameters, and this controller 15 calculates a current value to be fed to a solenoid 107a of a pressure control valve 107 on the basis of these input parameters. Operating oil pressure, namely, pressure being imposed on a plunger to be fed to a steering force variable device 105 is adjusted on the basis of the current value being fed to the solenoid 107a of the pressure control valve 107. Therefore, with the current value being fed to the solenoid 107a of the valve 107 controlled, the steering force of a steering wheel 4 is variably controllable in this way.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a power steering control device capable of variably controlling the steering force of a steering wheel.

[0002]

2. Description of the Related Art As a conventional power steering control device, the one described in Japanese Patent Application Laid-Open No. 5-50926 is known. This conventional invention determines a severity coefficient α representing the degree of severity of change of a steering angle within a reference time from a steering angular velocity of a steering wheel, and steering a steering wheel according to a value of the severity coefficient α. It controls resistance.

According to this conventional invention, when the rapid steering is frequently repeated, the steering resistance becomes larger than that when the rapid steering is not frequently repeated. Therefore, when the rapid steering is frequently repeated, the steering by the driver becomes excessive. It has the effect of being prevented.

[0004]

However, in the above-mentioned known example, the severity coefficient α, which is a parameter, is obtained from the steering angular velocity of the steering wheel, and the severity coefficient α is obtained.
Since the steering resistance is variably controlled based on the steering angle, when the steering wheel is operated near the neutral position (for example, when traveling on a highway), the steering angle changes. Therefore, the above control effect cannot be obtained.

It is desirable that the steering force of the steering wheel can be variably controlled according to changes in road traffic conditions such as urban areas, congested roads and mountain roads, and driving conditions of the driver. The present invention has been made in consideration of the above-described circumstances, and an object thereof is to make it possible to variably control the steering force characteristics of a steering wheel in accordance with road traffic conditions and the driving state of a driver, and to stabilize the driving force throughout the vehicle. An object of the present invention is to provide a power steering control device that can have steering characteristics.

[0006]

In order to achieve the above object, a power steering control device of the present invention is a steering force control means for variably controlling a steering force of a steering wheel of a vehicle according to a vehicle speed, a vehicle speed and an accelerator. A driving state of the driver based on the opening degree and the acceleration, for example, a driving state recognizing unit that detects a degree of acne is provided, and the steering force control unit variably sets the steering force according to a detection signal of the driving state recognizing unit. It is characterized by

Preferably, the road traffic condition when the vehicle is running,
For example, a road traffic recognition means for detecting the degree of urban area, the degree of congested road, the degree of mountain road, etc. is provided, and the steering force control means is
It is characterized in that the steering force is variably set according to the detection signals of the driving situation recognition means and the road traffic recognition means.

[0008]

According to the power steering device of the present invention,
The driving state recognizing means detects the degree of acne, which is the driving state of the driver, from the vehicle speed accelerator opening and the acceleration. Then, the steering force control means variably controls the steering force of the steering wheel according to the vehicle speed and the detection signal (crimp degree) of the driving state recognition means.

According to a particular aspect of the present invention, the road traffic recognizing means detects road traffic conditions when the vehicle is traveling, such as the degree of urban area, the degree of traffic jam and the degree of mountain road. The steering force control means variably sets the steering force of the steering wheel according to the detection signals of the vehicle speed, the driving situation recognition means, and the road traffic recognition means.

[0010]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the present invention will be described in detail below with reference to the accompanying drawings. The power steering apparatus of the present invention includes an estimating means for estimating the road traffic condition and the vehicle driving operation state of the driver. First, the estimating means (estimating method) will be described.

The estimation method estimates the vehicle driving operation state by the driver on the basis of the road traffic state obtained based on the vehicle traveling state parameter and the physical quantity representing the vehicle driving state. Specifically, as shown in FIG. 1, from the vehicle speed and the steering wheel angle, the average speed, the traveling time ratio (the ratio of the traveling time to the total time including the vehicle traveling time and the traveling stop time) as the vehicle traveling state parameters, and The average lateral acceleration is obtained. 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 road traffic conditions (city level, congestion level and mountain level) and parameters characterizing frequency distribution of 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.

A vehicle to which the estimation method according to the present 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. [Running Time Ratio Calculation Routine] For example, while the vehicle is in the driving state (including the running state and the running stopped state) after the engine is started, the processor of the controller 15 causes the running time ratio calculating routine shown in FIG. Is repeatedly executed.

In each calculation routine execution cycle, the processor inputs the vehicle speed signal vel from the vehicle speed sensor 26, which represents the actual vehicle speed, and determines whether 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 S following step S2 or S3
In 4, 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 value obtained by dividing the running time counter value rtime by the sum of this value and the running stop time counter value stime is multiplied by the value “100” to obtain the running time ratio ratio. (%) Is calculated (step S5).

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 thereafter, 1 is set.
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 the stored values vxsum [i] (i = 1 to 5) of the five accumulated speed registers built in the controller 10, respectively. 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 becomes 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 congested road 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.

[0027]

[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 the city driving, and the average speed is low and the traveling time ratio is low in the 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 in fitness from “0” to “1” as the running time ratio increases from 20% to 40%,
The degree of conformity is "1" between the traveling time ratios of 40% and 65%, and the degree of conformity decreases from "1" to "0" as the traveling time ratio increases from 65% to 85%. It is set. 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 speeds 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. Also, the membership function that defines the fuzzy set M has an average speed of 10 km / h to 20
The adaptability increases from "0" to "1" as it increases to km / h, and the adaptability is "1" between the average speed of 20 km / h and 40 km / h, and the average speed of 40 km / h. From 60
It is specified that the fitness decreases from "1" to "0" as it increases to km / h. The membership function that defines the fuzzy set B has an average velocity of 40
Goodness of fit becomes "0" as it increases from 60 km / h to 60 km / h
It is specified that the conformity is “1” when the average speed is 60 km / h or more.

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 degree [city] = Σ (adap [i] × r city [i]) ÷ adapt [i]
(I = 1 to 9) Congestion road degree [jam] = Σ (adap [i] × r jam [i]) ÷ adapt [i]
(I = 1 to 9) Specifically, the processor obtains the fitness 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 relates to the average speed. I-th of fuzzy sets S, M and B
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, the traveling time ratio fuzzy set S is obtained. "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 adequacy to the first rule of the combination of the actual traveling time ratio of 30% and the actual average speed of 10 km / h ad
apt [1] becomes "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.

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 (INT (vel /
10)) 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, the first to 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 S36).

Next, the processor sets the average value ave to "10".
It is determined whether it is larger than "0" (step S37),
If the determination result is affirmative, the average value is calculated in step S38.
The ave is reset to "100" and the process proceeds to step S39. On the other hand, if the determination result in step S37 is negative, the process immediately shifts from step S37 to step S39.
That is, the average value ave of the input data is limited to a value up to “100”.

In step S39, 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 sum num of the number of elements by the value "5" to calculate the variance var of the input data (step S40). Then, it is determined whether or not the variance var of the input data is larger than "100" (step S41). If the determination result is affirmative, the variance var is "10" in step S42.
After resetting to "0", the process proceeds to step S43, and if the determination result in step S41 is negative, step S41
To S43 immediately. That is, the variance var of the input data is limited to the value “100”.

In step S43, it is determined whether or not the total number num of elements is larger than "256". If the result of this determination is negative, the processing in the current 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 S44), and the processing in the current cycle is ended. That is, the number of elements num in the population is “256”
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 the 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.

An embodiment of the power steering control device according to the present invention will be described below. The present embodiment intends to control the vehicle driving characteristics so as to be adapted to the road traffic condition (urban road, etc.) and the driver's driving condition (severeness) estimated by the estimation method of the first embodiment. It is a thing. The procedure for estimating the road traffic condition and the driving condition is the same as that of the first embodiment, 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 the steering wheel will be described. The same members as those in the third embodiment are designated by the same reference numerals. Referring to FIG. 17, there is shown a schematic configuration diagram of a power steering device, in which a front wheel 1R is connected to a piston rod 2a of a power cylinder 2 via a tie rod 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 a tie rod 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 a 4-port 3-position directional control valve with a throttle (actually a rotary valve), and therefore, three of the four ports are provided with the supply line 101. 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. In FIG. 17, 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 (feel) 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 in advance within a predetermined range, 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 oil 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 situation information (corresponding to the above-mentioned city degree r city, etc.) and the driving state information from the above-mentioned 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 2 shows steering force characteristics of the (ideal) steering wheel 4 desired depending on road traffic conditions and driving conditions.

[0060]

[Table 2]

According to Table 2, 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 expressway in the road traffic situation is not estimated by the above-mentioned estimation method, the degree of expressway can be defined as a value which is the opposite of the degree of 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. 18 is stored in advance 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 shown by the broken line in FIG. 19 in accordance with 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. 20 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 expressway. Therefore, the parameter for correcting the current characteristic is the city degree (r city). Only tried. 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 indicating 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.

[0069]

As described above, according to the power steering control device of the present invention, the steering force characteristic of the steering wheel can be variably controlled according to the road traffic condition or the driving condition of the driver. Further, even in a neutral state in which the steering amount of the steering wheel is small, it is possible to obtain the control effect of the steering characteristic according to the traveling situation. Further, it has an excellent effect such that stable steering characteristics are obtained over the entire traveling of the vehicle.

[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 schematic configuration diagram of a power steering device of the present invention.

FIG. 18 is a map showing current characteristics with respect to vehicle speed (small urban area degree, small degree of crispness).

FIG. 19 is a map showing current characteristics with respect to vehicle speed (urban area degree increases).

FIG. 20 is a map showing current characteristics with respect to vehicle speed (increased degree of acne).

[Explanation of symbols]

 2 power cylinder 4 steering wheel 5 directional control valve 15 controller 26 vehicle speed sensor 105 steering force variable device 107 pressure control valve 201 input layer of neural network 203 output layer of neural network

Claims (2)

[Claims] 1. A steering force control means for variably controlling a steering force of a steering wheel of a vehicle according to a vehicle speed, and a driving state recognition means for detecting a driving state of a driver from a vehicle speed, an accelerator opening degree and an acceleration. The power steering control device, wherein the steering force control means variably sets the steering force according to a detection signal of the driving state recognition means. 2. A road traffic recognizing means for detecting a road traffic situation when a vehicle is traveling, wherein the steering force control means determines the steering force according to detection signals of the driving situation recognizing means and the road traffic recognizing means. The power steering control device according to claim 1, wherein the power steering control device is variably set.