JP2000043745A - Road surface state judging device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To detect the change of a road surface state accurately by a device for judging the road surface state. SOLUTION: The side slip angle of a car body is estimated at every assuming road surface state by giving each tyre characteristic and a detected state amount to a vehicle operation model. The side slip angle of the car body at every assuming road surface state estimated at present is corrected based on the present state amount and the side slip angle of the car body before one estimate time. The said processing is carried out by modeling calculation units 10, 12. In a differentiation calculation units 14, 16, the side slip angular velocity of the car body at every assuming road state is calculated as an estimation value based on the side slip angle of the car body at every assuming road surface state after correction. While, in the calculation unit 18, the side slip angular velocity of the car body is calculated as the detection value based on the detected state amount. The present road surface state is judged by the comparison of the detection value with the estimation value at every assuming road surface state.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a road condition judging device, and more particularly, to a device for judging a road condition based on a vehicle motion model.

[0002]

2. Description of the Related Art A road surface condition judging device is mounted on a vehicle body and judges a road surface condition while the vehicle is running. The determination result of the road surface state by such a device is used in electronic traveling control. In order to further enhance the safety of traveling, it is required to improve the accuracy of determining the road surface condition. In particular, when performing various controls for running the vehicle in a four-wheel steering system or a vehicle body spin prevention system,
Accurate grasp of the actual road surface condition is indispensable.

[0003] Japanese Patent Application Laid-Open No. 8-119131 discloses a device for detecting a slip condition on a road surface. In this device, a vehicle motion model (state equation) is used as a basis, and a reference state quantity (for example, a vehicle lateral acceleration) is estimated by substituting various sensor values and tire characteristics stored in advance into the vehicle motion model. . Then, an error (residual error) between the reference state amount and a detection state amount (for example, vehicle lateral acceleration) based on the sensor value is calculated, and the errors are arranged in chronological order to create reference error time-series data. . On the other hand, a plurality of assumed error time series data are prepared according to each road surface condition. Then, the plurality of assumed error time-series data is compared with the reference error time-series data by pattern, and the current road surface state is determined based on which estimated error time-series data is closest.

Japanese Patent Application Laid-Open No. 9-311042 discloses an apparatus for estimating a vehicle body side slip angle using a vehicle motion model, similarly to the above-mentioned prior art. In this device, a road surface condition is determined from a comparison between a lateral acceleration estimated from a steady circular turning model and a detected lateral acceleration, and tire characteristics are determined based on the road surface condition. The tire characteristics are used in estimating the vehicle body side slip angle. In estimating the vehicle body side slip angle, a feedback control method using an observer is used. Such a control method is also described in Japanese Patent Application Laid-Open No. 3-122541, and the vehicle body slip angle is detected by using a state estimation technique which is one of modern control theories.

[0005]

However, the conventional apparatus described in Japanese Patent Application Laid-Open No. 8-119131 is
The purpose of the present invention is to detect a slip state at an early stage of steering before the vehicle body reaches a spin state, and in principle, the road surface state can be determined only at the start of steering. Therefore, it is not possible to cope with a case where the road surface condition changes during steering, and in that case, there is a problem that the road surface cannot be determined. That is,
In this conventional device, when the vehicle body starts to slip, a phase shift occurs between the modeling result and the actual sensor value, and the reference error time series data does not match any assumed error time series. Therefore, the determination of the road surface condition is restricted to the start of steering.

Further, in various conventional devices, it has not been possible to accurately determine a road surface condition in various running conditions. For example, in the related art, there has been a problem that the road surface can be determined only when turning.

The present invention has been made in view of the above-mentioned conventional problems, and an object of the present invention is to accurately estimate a road surface condition. It is another object of the present invention to be able to detect a change in the road surface condition even during the steering operation.

[0008]

In order to achieve the above object, the present invention provides a detecting means for detecting a state quantity relating to the movement of a vehicle, a vehicle movement model storing means for storing a vehicle movement model, and a plurality of assumptions. Tire characteristic storing means for storing a plurality of tire characteristics corresponding to road surface conditions; and a vehicle body slip angle for estimating a vehicle body skid angle for each assumed road surface condition by giving the tire characteristics and state quantities to the vehicle motion model. Estimating means and means for correcting the estimated vehicle body slip angle for each of the assumed road surface conditions, wherein the estimated vehicle body skid angle is calculated based on the current state quantity and the body slip angle estimated using the state quantity one estimated time ago. Feedback correction means for correcting the currently estimated vehicle body slip angle based on the vehicle body slip angle for each assumed road surface state corrected by the feedback correction means. Estimated angular velocity calculating means for calculating the vehicle body side slip angular velocity for each assumed road surface state as the estimated angular velocity, detection angular velocity calculating means for calculating the vehicle body side slip angular velocity as the detected angular velocity based on the state quantity, and the detected angular velocity and each of the assumed road surfaces And a road surface state determining means for comparing the estimated angular velocity for each state to determine the current road surface state.

In the above configuration, the tire characteristics are stored in advance in the tire characteristic storage means for each assumed road surface condition (for example, a snowy road (snow) and a normal road (dry)). Their tire characteristics and detected state quantities (eg, lateral acceleration,
When the yaw rate, the vehicle speed, and the steering angle) are given to the vehicle motion model, as a result, the vehicle body side slip angle is estimated for each assumed road surface state. Feedback correction is performed on the vehicle body side slip angle based on the current state quantity and the vehicle body side slip angle estimated based on the state quantity one estimated time (one sampling time or one control time) earlier. That is, the vehicle body sideslip angle is estimated and corrected at the same time for each sampling period. Then, for example, by differentiating the corrected vehicle slip angle for each assumed road surface state, the vehicle body slip angular velocity for each assumed road surface state is estimated as the “estimated angular velocity”.

On the other hand, the vehicle body side slip angular velocity is calculated as "calculated angular velocity" by calculation based on the detected state quantity. Therefore, the estimated angular velocity for each assumed road surface state is compared with the calculated angular velocity, and as a result of the comparison, the current road surface state is determined. That is, a plurality of estimated angular velocities are obtained using tire characteristics for each assumed road surface state, and the current road surface state is determined based on which is closer to the actual calculated angular velocity.

According to the present invention, basically, tire characteristics having non-linear characteristics are used. In estimating the vehicle body sideslip angle by modeling, feedback correction based on the current state quantity and the vehicle body sideslip angle one estimated time ago is performed. Since the phase shift is performed, there is an advantage that the above-described phase shift can be avoided, and the determination that follows the change in the road surface state during steering can be performed. Here, with respect to the feedback correction, a technique related to the above-mentioned Japanese Patent Application Laid-Open No. 9-311042 is disclosed, but various methods can be applied as the correction method as long as the problem of the phase shift can be avoided.

[0012]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Preferred embodiments of the present invention will be described below with reference to the drawings.

FIG. 1 shows a preferred embodiment of a road surface condition judging device according to the present invention, and FIG. 1 is a block diagram showing the whole structure.

This road surface condition determination device is a device mounted on a vehicle such as an automobile, for example, and automatically determines the state of the road surface on which the vehicle is traveling.
Each configuration shown in FIG. 1 is realized by software or hardware. Of course, this road surface condition determination device may be configured as a combination of software and hardware.

In FIG. 1, modeling operation units 10, 1
Reference numeral 2 denotes a unit for estimating a state quantity (in this embodiment, "the vehicle body side slip angle") based on the vehicle body traveling based on the nonlinear vehicle model. Here, signals from various sensors mounted on the vehicle, specifically, state quantities such as a lateral acceleration (lateral G), a yaw rate, a vehicle speed, and a steering angle are input to the respective modeling calculation units 10 and 12. ing. In the present specification, the lateral acceleration, the yaw rate, the vehicle speed, and the steering angle are represented by the following symbols in the drawings. In addition, those state quantities are also sent to the calculation unit 18 described later.

[0016]

(Equation 1) FIG. 2 shows a specific configuration example of the modeling operation units 10 and 12 shown in FIG. Here, the modeling operation unit 10 for snow and the modeling operation unit 12 for dry
Have the same configuration. They may be configured separately as shown in FIG. 1, but may be of course integrated.

In this example, the arithmetic unit 60 has a state equation as a non-linear vehicle model, and is a means for estimating the vehicle side slip angle by giving the various state quantities and tire characteristics to the state equation. The memory 60 </ b> A of the arithmetic unit 60 stores in advance tire non-linear characteristics as shown in FIG. 3. Here, in the modeling operation unit 10 for snow, sn memory is stored in the memory 60A.
The ow tire non-linear characteristic is stored, while the dry modeling operation unit 12 stores the dry
The tire non-linear characteristics are stored.

When the respective components of the modeling calculation sections 10 and 12 are compared, only the tire characteristics to be used are different. Therefore, it is desirable that both are substantially configured as one modeling operation unit. This is also true for the other overlapping configurations shown in FIGS.

In FIG. 2, the components surrounding the calculation unit 60 (calculation unit 62, calculation unit 64, addition calculation unit 66, differentiation calculation unit 68, and difference calculation unit 70) are the vehicle body slip angles estimated as described above. This constitutes a feedback correction means for correcting. More specifically, the calculation unit 62 calculates the vehicle body side slip angular velocity based on the current state quantity. On the other hand, based on the vehicle body sideslip angle one estimated time ago (specifically, the vehicle body sideslip angle after correction to be described later), the differential calculation unit 68 calculates the vehicle body sideslip angular velocity. The difference calculator 70 calculates a difference (residual difference) between the current vehicle sideslip angular velocity calculated by the calculator 62 and the vehicle sideslip angular velocity calculated by the differential calculator 68 and corresponding to one estimated time before. Is done. The calculation unit 64 determines a correction value (estimated correction value) based on the difference, and the correction value is added to the addition calculation unit 6.
In step 6, it is added to the vehicle body side slip angle output from the calculation unit 60. The corrected vehicle sideslip angle is output to the outside, and is also input to the differential operation unit 68 described above. The calculation unit 64 may be configured by, for example, a function or a table that determines a correction value.

According to the above feedback correction, even if the actual road surface condition changes during steering, the estimation calculation can be performed in accordance with the change, so that the problem of the phase shift described in the conventional example can be solved.

Returning to FIG. 1, the vehicle body side slip angle (estimated value) estimated by the snow modeling operation unit 10 is represented as follows in FIG.

[0022]

(Equation 2) The differential operation unit 14 performs a differential operation on the estimated vehicle body side slip angle, thereby obtaining a vehicle body side slip angular velocity. In the drawings, the vehicle body side slip angular velocity is expressed as follows.

[0023]

(Equation 3) As described above, the estimated value (estimated angular velocity) of the vehicle body side slip angular velocity corresponding to the road surface state snow is obtained by the snow modeling operation unit 10 and the differential operation unit 14.

On the other hand, the vehicle body side slip angle (estimated value) estimated by the dry modeling operation unit 12 is represented as follows in FIG.

[0025]

(Equation 4) The estimated vehicle body sideslip angle is input to the differential operation unit 16, and a differential operation is performed on the vehicle body sideslip angle, whereby the vehicle body sideslip angular velocity is calculated. The vehicle body side slip angular velocity is represented as follows in the figure.

[0026]

(Equation 5) To summarize the above, the vehicle body skidding angular velocity corresponding to snow is calculated by the modeling calculation unit 10 and the differentiation calculation unit 14, and the vehicle body skid angular velocity corresponding to dry is calculated by the modeling calculation unit 12 and the differentiation calculation unit 16.

The calculating unit 18 calculates the vehicle body side slip angular velocity as a detection value based on the lateral acceleration, the yaw rate, and the vehicle speed input from the sensors. here,
In the figure, the vehicle body side slip angular velocity is represented as follows.

[0028]

(Equation 6) Then, the following calculation formula is executed in the calculation unit 18. This calculation is the same as that performed by the calculation unit 62 in FIG.

[0029]

(Equation 7) Therefore, the vehicle body sideslip angular velocity is specified as a detection value as an output of the calculation unit 18, and on the other hand, as described above, the vehicle body sideslip angular velocity corresponding to each assumed road surface state is calculated as an estimated value.

The operation section 18 in FIG. 1 executes substantially the same calculation as the operation section 62 in FIG. 2, and therefore, can be integrally formed. Further, since the differential operation units 14 and 16 in FIG. 1 execute the same operation as the differential operation unit 68 in FIG. 2, they can be integrally configured.

The noise removing section 20 is a means for executing filtering on the above-described detector and the two estimated values, and includes three filters 22 and 2 corresponding to the respective values.
4, 26. These filters 22, 2
Reference numerals 4 and 26 are provided to eliminate or reduce error factors such as road surface disturbance such as a bank road and a cant road, and sensor noise.
It has both functions as a high-pass filter of z and a low-pass filter of 3 Hz. That is, it functions as a bandpass filter. Of course, the characteristics of the filter can be appropriately set according to the application. The three filters 22, 24, 26 need not always be provided, and any one of them may be used.

The two estimated values and the detected values, which have been subjected to the filtering in the noise removing unit 20, are used in an error calculating unit 28.
Has been entered. On the other hand, in the present embodiment, among these values, the vehicle body side slip angular velocity particularly corresponding to the assumed road surface state of snow is sent to the update determination unit 30. Here, the vehicle body side slip angular velocity output from the filter 22 is represented as follows in the figure.

[0033]

(Equation 8) The update determination unit 30 is a unit for determining whether or not to update the previous determination result when performing the determination of the road surface state described later in detail for each sampling cycle. In the present embodiment, the determination is executed with reference to the vehicle body side slip angular velocity particularly corresponding to the assumed road condition of snow, and specifically, it is calculated whether or not the following determination formula is satisfied.

[0034]

(Equation 9) Update determination result signal 100 output from update determination unit 30
Has information on whether or not the condition of the above equation (2) has been satisfied, and the information is based on a road surface state determination unit 48 described later in detail.
Used in

The error calculator 28 provided at the subsequent stage of the noise eliminator 20 has two error calculators 3.
2, 34. Each deviation calculator 3
2 and 34, the error of the estimated value with respect to the detected value is sequentially calculated.
Is calculated, and the deviation calculator 34 calculates dry
Are calculated. In addition, when the state quantities at a certain time are input in parallel to the modeling operation units 10 and 12 and the operation unit 18, whereby the estimated value and the detected value are calculated, the estimation related to the state amount at the same time is performed. The timing is controlled so that the value and the detected value are input to the error calculating unit 28 at the same time.

The above-mentioned error indicates the likelihood of the estimated value estimated by modeling. In other words, the error indicates the degree of conformity of the preconditions (assumed road surface conditions) used in each modeling. Furthermore,
By confirming which tire characteristic matches the current situation, it is possible to determine the current road surface condition as a result.

The operation units 36 and 38 are provided downstream of the error operation unit 28. Each of the operation units 36 and 38 is configured by accumulation operation units 40 and 44 and filters 42 and 46, respectively. Here, the accumulators 40 and 4
Numeral 4 is means for calculating the square of the error output from each of the deviation calculators 32 and 34 and calculating the accumulated value by accumulating the squared error over a predetermined number. Here, the predetermined number is, for example, ten. That is, an operation for accumulating 10 errors is performed for each sampling cycle,
The accumulated value is input to filters 42 and 46, respectively.

In the present embodiment, the filters 42 and 46 are constituted by low-pass filters of 0.5 Hz, and the accumulated values are smoothed by these filters.

By the operation of the arithmetic units 36 and 38, an error amount having a statistical or averaged property is obtained based on a plurality of errors, and the error amount is used for determining the road surface condition. Will be. Incidentally, an absolute value operation may be performed instead of the square operation described above. In addition, the number to be accumulated can be appropriately set from the viewpoint of determination accuracy and responsiveness. Each of the accumulating sections 40 and 44 has a memory for storing a predetermined number of pieces of error information, and the memory capacity is appropriately set according to the number of pieces of information to be stored.

In FIG. 1, the error amount output from the operation unit 36 is expressed as follows.

[0041]

(Equation 10) The error amount output from the arithmetic unit 38 is expressed as follows.

[0042]

[Equation 11] In the present embodiment, the road surface state determination unit 48 includes an evaluation value calculation unit 50 and a road surface state determination unit 52. The evaluation value calculator 50 evaluates the evaluation value K for determining the road surface condition.
Is calculated. In the present embodiment, the following calculation is performed.

[0043]

(Equation 12) As will be described later, especially when the current road surface state is a high μ road, the error amount corresponding to snow is significantly larger than the error amount corresponding to dry, and therefore, the magnitudes of such error amounts are mutually different. By making the comparison, it is possible to accurately determine the current road surface condition. For this reason, as described above, the ratio of the two error amounts is calculated by equation (3).

The road surface condition determining section 52 has a comparator 52A and a memory 52B. The comparator 52A is a means for comparing the evaluator K with a fixed threshold C, and the memory 52B
Is a memory for storing the result of the previous determination. Comparator 52
In A, when it is determined that the evaluation value K is smaller than the threshold value C, the road surface state determination unit 52 determines that the road is a low μ road, and when the evaluation value K is equal to or more than the threshold value C, Is determined to be a high μ road.

However, in this embodiment, the determination result of the road surface condition is updated only when the update determination result signal 100 indicates that the update is to be performed, and in other cases, the previous determination result is maintained as it is. I have. This is based on the possibility that the current road surface state is erroneously determined in a state where the behavior of the vehicle is small.

In the configuration example shown in FIG.
Although one is shown, the current road surface state may be determined using a plurality of threshold values. In the above-described embodiment, the evaluation value K is used. However, as long as an error corresponding to each assumed road surface state is used as a criterion, various determination methods can be used. However, in the state where the behavior of the vehicle is small as described above, the possibility of an erroneous determination increases, and in such a case, it is desirable to maintain the previous determination result.

FIG. 3 shows modeling operation units 10 and 12
3 shows an example of the non-linear tire characteristics held in the example.
In the graph shown in FIG. 3, the horizontal axis is the side slip angle of the tire, and the vertical axis is the cornering force. As shown in the drawing, the characteristics of the snow are more saturated than those of the dry from the region where the side slip angle is small. Due to such a difference in characteristics, when the actual road surface state is dry, a remarkable difference occurs between the estimated value of snow and the estimated value of dry as described above. It is possible to determine the road surface state by using the phenomenon. The phenomenon is specifically described below.

FIGS. 4 and 5 show the relationship between various state quantities and the vehicle body side slip angular velocity. FIG. 4 shows a case where the road surface state is a high μ road, and FIG. 5 shows a case where the road surface state is a low μ road. In each figure, (A) shows a change in the steering angle, and (B) shows a change in the yaw rate, the lateral acceleration, and the vehicle speed. Also, (C)
Indicates a vehicle side slip angle. (D) is the detected value (sensor value) and each estimated value (slip angular velocity of the estimation system for dry, sno
(slip angular velocity of the estimation system for w).

As is clear from the comparison between FIGS. 4 and 5,
In the case of a high μ road, an error between the sensor value and the estimated value of snow becomes significant. In other words, on a low μ road,
Neither estimated value is much different from the detected value, and both dry and snow errors are not much different, but on a high μ road, a large difference is found between these errors. The present invention utilizes such a phenomenon to determine the current road surface state as a result.

FIGS. 6 to 9 show the results of the road surface determination. Here, FIGS. 6 and 7 show the determination results of the road surface state when the lane change is performed when the road surface state is the high μ road, and FIGS. 8 and 9 show the case where the slalom is performed on the low μ road. 3 shows the determination result of the road surface condition in FIG. 6 and 7 show the cases of Case 1 and Case 2, respectively, and FIGS. 8 and 9 also show the cases of Case 1 and Case 2, respectively.

In each of the figures, (A) shows a change in the steering angle, (B) shows a change in the yaw rate, the lateral acceleration and the vehicle speed, and (C) shows a change in the evaluation value. , (D) show the determination results.

In FIGS. 6 and 7, when the steering angle changes (lane change) as shown in FIG. 6A (lane change), the yaw rate, the lateral acceleration and the vehicle speed change greatly with the change of the steering angle. The evaluation value is obtained as shown in FIG. 1C by the configuration shown in FIG. Then, the road surface state is determined using the evaluation value as shown in (D). In case 1 and case 2 shown in FIGS. 6 and 7, both are determined to be high μ roads.

On the other hand, as shown in FIGS. 8 and 9, when slalom is performed on a low μ road, the steering angle changes as shown in FIG. In this case, the evaluation value fluctuates as shown in FIG. At this time,
As shown in (D), the road is initially determined to be a high μ road, but is determined to be a low μ road when the value falls below a low μ road threshold.

As described above, according to the present embodiment, there is an advantage that the current road surface condition can be accurately determined by following a change in the road surface condition. Therefore, there is an advantage that various controls for improving the safety of vehicle traveling can be realized by effectively utilizing the determination result of the road surface state.

In the examples shown in FIGS. 8 and 9,
As shown in (C), a threshold for determining a low μ road and a threshold for determining a high μ road are set as thresholds. Of course, the road surface state may be determined by using one threshold value and update determination as described above without using two threshold values. Further, the road surface condition may be more finely determined using three or more threshold values. In that case, it is desirable to prepare a number of tire characteristics corresponding to the assumed road condition to be determined. Note that the suitability of each road surface condition may be represented based on the difference between the threshold value and the evaluation value.

[0056]

As described above, according to the present invention,
The current road surface state can be accurately estimated, and even if the road surface state changes during steering, the change can be accurately detected.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating an embodiment of a road surface condition determination device according to the present invention.

FIG. 2 is a block diagram illustrating a specific configuration example of a modeling operation unit.

FIG. 3 is a characteristic diagram showing tire characteristics.

FIG. 4 is a diagram illustrating a relationship between various state quantities and a vehicle body slip angular velocity on a high μ road.

FIG. 5 is a diagram showing a relationship between various state quantities and a vehicle body side slip angular velocity on a low μ road.

FIG. 6 is a diagram illustrating a determination result when a lane change is performed on a high μ road (case 1).

FIG. 7 is a diagram illustrating a determination result when a lane change is performed on a high μ road (case 2).

FIG. 8 is a diagram showing a determination result when slalom is performed on a low μ road (case 1).

FIG. 9 is a diagram illustrating a determination result when slalom is performed on a low μ road (case 2).

[Explanation of symbols]

10, 12 modeling operation unit, 14, 16 differentiation operation unit, 18 operation unit, 20 noise removal unit, 28 error operation unit, 30 update determination unit, 36, 38 operation unit, 48
Road surface condition determination unit, 50 evaluation value calculation unit, 52 road surface condition determination unit.

 ────────────────────────────────────────────────── ─── Continuing on the front page (72) Inventor Katsuhiro Asano 41-Cho, Yokomichi, Nagakute-cho, Aichi-gun, Aichi Prefecture Inside Toyota Central Research Laboratory Co., Ltd. (72) Inventor Kenji Totsu 2 Asahi-cho, Kariya City, Aichi Prefecture 1-chome Aisin Seiki Co., Ltd. (72) Inventor Takayuki Ito 2-1-1 Asahi-cho, Kariya-shi, Aichi F-term in Aisin Seiki Co., Ltd. 3D032 CC21 CC30 DA03 DA23 DA29 DA33 DA82 DC03 DC04 DC12 DC13 DC33 DC34 DD17 EA04 EB21 GG01

Claims (1)

[Claims] 1. A detecting means for detecting a state quantity relating to a motion of a vehicle, a vehicle motion model storing means storing a vehicle motion model, and a tire characteristic storing means storing a plurality of tire characteristics corresponding to a plurality of assumed road surface conditions. A vehicle body slip angle estimating means for estimating a vehicle body skid angle for each assumed road surface state by giving the tire characteristics and state quantities to the vehicle motion model; and a vehicle body skid for each of the estimated assumed road surface states. Feedback correcting means for correcting the currently estimated vehicle body slip angle based on the current state quantity and the vehicle body slip angle estimated using the state quantity one estimated time ago. Based on the vehicle body slip angle for each assumed road surface state corrected by the feedback correction means, the vehicle body slip angular velocity for each assumed road surface state is estimated angular velocity Estimated angular velocity calculating means for calculating as, detected angular velocity calculating means for calculating the vehicle body slip angular velocity as a detected angular velocity based on the state quantity, comparing the detected angular velocity with the estimated angular velocity for each of the assumed road surface states, A road surface state determination device, comprising: a road surface state determination unit that determines the road surface state of the road surface.