JPH0316820A - Suspension device for vehicle - Google Patents

Abstract

PURPOSE:To make it possible that the suspension force suits own taste is swiftly and minutely determined by detecting the road surface state in front of a vehicle, and performing fuzzy inference according to the detected car speed and the degree of the set suspension force to determine the suspension force and output to an adjusting means. CONSTITUTION:The road surface state in front of a vehicle front wheel 8 is detected by an ultrasonic sensor 10, and inputted to a road surface state detection part 2 to detect the degree of roughness/fineness of the road surface, and, inputted to a fuzzy controller 4 together with the car speed signal X3 from a car speed detection part 3 and the set suspension force signal X1 of a suspension force setting part 1. The fuzzy controller 4 performs fuzzy inference based on these input signals X1-X3, and the suspension force y is determined and outputted to a suspension force adjusting part 5. The adjusting part 5 increases/ decreases the suspension force of an oil dumper 7 based on this suspension force. With this constitution, the suspension force suits the taste of an occupant can be minutely and swiftly determined.

Description

DETAILED DESCRIPTION OF THE INVENTION +a+Field of Industrial Application This invention relates to a suspension system that adjusts the suspension force of a vehicle using fuzzy reasoning.

'(b) Prior Art The suspension force of the suspension system that suspends the wheels of a vehicle has a great effect on ride comfort and running stability. When the road surface is smooth, the greater the suspension force of the suspension system, the greater the driving stability, and this does not significantly deteriorate the comfort of the vehicle.

However, when driving on a highly uneven road surface, if the suspension force is large, the comfort deteriorates and the driving stability also deteriorates. Therefore, a suspension system has been proposed in which the road surface condition in front of the vehicle is detected using an ultrasonic sensor or the like, and the suspension force is increased or decreased based on the detection result. Generally, in such a suspension system, detected data of the road surface condition is inputted into a microcomputer, and after arithmetic processing is performed, the suspension force is changed based on the result of the calculation.

{0}Problems to be Solved by the Invention However, in the above-mentioned conventional suspension system, the calculation processing time in the microcomputer is long due to the propagation speed of vibrations acting on the vehicle from the road surface, and the calculation results are not realized. There was a problem in that it took a considerable amount of time to complete the process and it was not possible to obtain sufficient responsiveness. Furthermore, if the calculation is simplified in order to speed up the calculation process, the suspension force cannot be adjusted extremely finely, and there is a problem in that it is not possible to obtain the optimum suspension force for the road surface condition. Furthermore, for the same reason as No. 5, there is a problem in that the suspension force cannot be adjusted by combining factors other than road surface conditions, such as passenger preference regarding comfort.

An object of the present invention is to generate a fuzzy
To provide a suspension system for a vehicle that can quickly and precisely determine the suspension force based on a plurality of factors by determining the suspension force by performing the following steps. It is in.

(d) Means for Solving the Problems The vehicle suspension system of the present invention includes a road surface condition detection means for detecting the road surface condition in front of the vehicle, a speed detection means for detecting the traveling speed of the vehicle, and a vehicle suspension system that detects the vehicle suspension force. a setting means for setting and inputting the degree; a suspension force adjusting means for increasing or decreasing the suspension force of the vehicle;
Fuzzy inference means determines the suspension force to be output to the suspension force adjustment means by performing fuzzy inference using the detection results of the road surface condition detection means and the speed detection means and the setting value of the setting means as input values; What are the characteristics?

(e) Effect In this invention, the fuzzy inference means uses the road surface condition input from the road surface condition detection means, the traveling speed input from the speed detection means, and the degree of suspension force input from the setting means as input values.・The inference was made,
The suspension force to be output to the suspension force adjustment means is determined.

The fuzzy inference means performs fuzzy operations like a
It consists of a fuzzy calculation section and a defuzzification section that performs definite value calculations. The fuzzy calculation section is equipped with a function generator that follows predetermined fuzzy rules, and calculates a member function value for each input variable, and sends an inference value calculated based on the result to the defuzzification section. Output against. This fuzzy rule is if(x+ =A and X2=B -)th
It is expressed in the form en(y = Z), and (x+ −^an
dX2=B...) is called the antecedent part, and (y=Z) is called the consequent part.

FIG. 7 is a diagram for explaining a known method of outputting inference results according to the above-mentioned fuzzy rules.

Figures (A) and (B) show the membership functions corresponding to the two variables (X+, XZ) in the antecedent part, which are input values, and (C) in the figure corresponds to the consequent part, which is the output value. Represents a member sysop function. Here, two membership functions for the antecedent part are shown, but as the types of variables in the antecedent part increase, the number of membership functions will increase accordingly. In each figure, the horizontal axis represents the value of the variable, and the vertical axis represents the position (degree of affiliation) of the menhashisopu. Now, if the value of variable x1 in the first term of the antecedent part is X, then the degree of affiliation at that time. is 0.5 (same figure (A>
reference>. Also, the value of variable x2 in the second item of the antecedent part is x
, L, then the degree of membership is 0.3 (see (B) in the same figure).

In such a case, the fuzzy operation takes the smallest value among the degrees of membership. That is, in the above example, a degree of affiliation of 0.3 is selected. Next, truncate the Menhasisop function corresponding to Z at the above membership degree of 0.3, and calculate the lower trapezoidal part S.
Find the center of gravity position y'. Then, this y' is output as the inference result.

The above inference is performed for one rule, but generally multiple rules are set. In this case, the inference results shown in FIG. 7(C) are output for each rule. Then, the trapezoid parts output for each rule are logically summed, and the center of gravity y of the logically summed part (hatched area in FIG. 7(D)) is outputted as a determined logical value. In this way, the output value is determined so that the input value shown on the horizontal axis of the member system function in FIGS. 7(A) and 7(B) takes an intermediate value.

In the above logical method, the logical product operation rule for the degree of belonging belonging to the antecedent part (operation to select the smaller degree of belonging) and the logical sum operation rule for the trapezoidal part for the consequent part are mini-ma
These rules are called y-rules and are executed in the antecedent logical product circuit and the consequent logical sum circuit, respectively.

In this invention, the center of gravity y in FIG. 6(D) is output as the suspension force.

(f) Embodiment FIG. 1 is a diagram showing the structure of a vehicle suspension system according to an embodiment of the present invention.

In the vehicle 6, the road surface condition in front of the front wheels 8 is detected by the ultrasonic sensor 4.
Detected by J10. The detection results of the ultrasonic sensor 10 are input to the road surface condition detection section 2, and the degree of density of the road surface is detected as the road surface condition. Note that the road surface condition detecting means may be any device other than the ultrasonic sensor 10 as long as it can detect the degree of density of the road surface. Further, the rotational speed of the front wheel 8 is detected by the rotation sensor 9. The detection result of the four-wheel rotation sensor 9 is inputted to the vehicle speed detection section 36, and the running speed of the vehicle 6 is detected. The road surface condition and traveling speed detected by the vehicle speed detection unit 3 are road surface signals x2.
1-3 and vehicle speed signal x3 to the fuzzy controller 1 and roller 4. Further, the suspension force for suspending the wheels can be set and input by operating a switch (not shown) in the control section of the vehicle 6.

This setting result is input from the suspension force setting section 1 (which is the setting means of the present invention) to the fuzzy control roller 4 as a setting signal X. The fuzzy controller 4 performs fuzzy inference based on these input values X1 to X, according to fuzzy rules and member simplification functions, which will be described later.
The suspension force y obtained by this fuzzy inference is output to the suspension force adjustment section 5. The suspension force adjustment section 5 increases or decreases the suspension force of the oil damper 7 so as to realize the suspension force y input from the fuzzy controller 4.

As shown in FIG. 2, the oil damper 7
The orifice 23 provided in the orifice 23 is provided with an adjustment member 25, and the adjustment member 25 is displaced by the drive of the motor 22 to increase or decrease the opening area of the orifice 23. Therefore, by outputting a control signal to the motor driver 2↓ and driving the moke 22, the opening area of the orifice 23 can be increased or decreased.
The damping force acting on the piston 24, that is, the suspension force of the oil damper 7 can be increased or decreased.

FIG. 3 is a block diagram showing the configuration of the fuzzy controller 1 roller that constitutes a part of the suspension system of the vehicle.

The fuzzy controller 1 and the roller 4 include a fuzzy calculation section 40 and a defuzzification section 41. Fuzzy operation section 4
0 outputs the inference result Xi for each rule according to the fuzzy rules shown in FIG. This fuzzy calculation unit 40 is provided for each rule, and the inference results of the plurality of fuzzy calculation units 40 are output in parallel to the defuzzification unit 41. For example, the fuzzy calculation unit 40 located at the top in FIG.
(x+ =NS and x. =ZR and X
3 = NL)tl+en (y = NL).

FIG. 4(A) shows the configuration of the fuzzy calculation section 40. The fuzzy calculation unit 40 has four general-purpose non-hashish subfunction generators 50 to 53, and each of the member function generators 50 to 53 has a set value x1 and a label NS corresponding thereto, and a road surface condition X2 and a corresponding label NS. Rahel ZR, vehicle speed X3 and its corresponding label NL, and label NL corresponding to the tragic force y are input. Each of the function generators 50 to 53 generates a function corresponding to the Rahel. Of course, the member synoptic function of NS shown in FIG. 6(A) is generated in the member synoptic function generator 50, and the member synoptic function of ZR, not shown in FIG. 6(B), is generated in the member synoptic function generator 51. ,
In the Menhasisop function generator 52, N shown in FIG.
A Menhasisop function of L is generated. In addition, the menhasisop function generator 53 generates a menhasisop function of NL, which is not shown in FIG. 6(D). The member function functions shown in FIGS. 6(A) to 6(D), together with the fuzzy rules shown in FIG. 5, are predetermined based on information obtained empirically through test runs of the vehicle 6.

The outputs of the membership function generators 50 to 52, that is, the degree of membership of each term in the antecedent part of the fuzzy rule, are output to the antecedent part AND circuit 54, and
The smaller affiliation 9 { 0 degrees is selected by the ini rule. The result is sent to the consequent AND circuit 55. The consequent logical product circuit 55 applies the inference result from the antecedent logical product circuit 54 to the member symp function output from the menhashisop function generator 53, and applies the inference result from the antecedent logical product circuit 54 to
), perform the head truncation (take the logical product), and output the trapezoidal part as the inference result.

FIG. 4(B) is a diagram showing the configuration of the defuzzifier 41. As shown in the figure, the defuzzify unit 41 is composed of a logical sum circuit B (consequent part logical sum circuit) 60 and a definite value calculation circuit 61. The logical sum circuit 60 is a mini-ma
This is the part that calculates the max rule of the x rule, and the trapezoidal outputs (inference results) from each fuzzy calculation unit 40 are logically summed to form a hunting area as shown in FIG. 7(D). The determined value calculation circuit 61 determines the center of gravity position from this area and outputs the determined value of the suspension force y.

With the above configuration, the fuzzy controller 4 uses the set value X1 set and input in the suspension force setting section 1, the road surface condition X' detected in the road surface condition detecting section 2, and the weight l x 3 detected in the vehicle detecting section 3. Based on the fifth
Fuzzy inference is performed according to the fuzzy rules shown in the figure and the Menhaship functions shown in FIGS. 6(A) to 6(D). As is clear from Fig. 5, the fuzzy rule in this embodiment is that the rougher the road surface condition x2 and the lower the vehicle speed x3, the smaller the suspension force y. It is set to reflect the content. Therefore, the suspension force output from the fuzzy controller 4 decreases as the set value x becomes smaller, as the road surface condition x2 becomes rougher, and as the vehicle speed x3 decreases.

In response, the suspension force adjustment unit 5 drives the motor 22 to increase the opening area of the orifice 23 and reduce the damping force in the oil damper 7.

In this way, the Fuzzycon I Roller 4 determines the suspension force based on the relationship between the road surface condition and the vehicle speed, the comfort, and the driving stability obtained empirically through test driving, and furthermore, in this determination, the set value , the suspension force of the vehicle is adjusted so as to always realize comfort and running stability that satisfy the occupant, regardless of road surface conditions or running speed.

(Effects of the Invention) According to this invention, the suspension force of the vehicle can be quickly and extremely finely adjusted according to the road surface condition in front of the vehicle, the traveling speed of the vehicle, and the driver's preference. Regardless, there is an advantage in that the suspension force can be adjusted to a level that can always provide comfortable accommodation and running stability that satisfy the occupants.

[Brief explanation of the drawing]

Fig. 1 is a diagram showing the configuration of a suspension system for a vehicle that is an embodiment of the present invention, Fig. 2 is a diagram showing an oil damper that constitutes a part of the suspension system, and Fig. 3 is a diagram showing a part of the suspension system. 4(A) and 4(B) are diagrams showing the structure of the fuzzy operation section and defuzzify section, respectively, of the same fuzzy controller, and FIG. 5 is a diagram showing the structure of the fuzzy controller constituting the FIGS. 6(A) to 6(D), which are diagrams showing fuzzy rules, are diagrams representing member functions in the same fuzzy controller. Also,
FIGS. 7(A) to 7(D) are diagrams illustrating a known fuzzy inference method. 1 suspension force setting section, 1 road surface condition detection section, 1 vehicle speed detection section, 1 fuzzy controller, 1 suspension force adjustment section, 1 vehicle, 1 oil damper, 1 rotation sensor, 〇1 ultrasonic sensor (road surface condition detection means).

Claims (1)

[Claims] (1) Road surface condition detection means for detecting the road surface condition in front of the vehicle, speed detection means for detecting the running speed of the vehicle, setting means for setting and inputting the level of suspension force of the vehicle, and increasing or decreasing the suspension force of the vehicle. Suspension force adjustment means; Fuzzy inference means that performs fuzzy inference using the detection results of the road surface condition detection means and the speed detection means and the setting value of the setting means as input values to determine the suspension force to be output to the suspension force adjustment means. A vehicle suspension system characterized by comprising: