JPH0337341A - Speed controller for automobile - Google Patents

Abstract

PURPOSE:To carry out the optimum speed control corresponding to the road surface state by controlling the road surface state by fuzzy-estimating the dynamic frictional coefficient between the road surface and a tire on the basis of the state of the road surface on which an automobile travels and the traveling speed and controlling the speed of the automobile according to the result of the estimation. CONSTITUTION:In the control of the speed of an automobile, the state of a road surface on which the automobile travels and the traveling speed of the automobile are detected by the means 2 and 6. Then, each detection signal is inputted into a fuzzy controller 8, and the speed of the automobile is fuzzy- controlled according to a plurality of fuzzy rules having the detected road surface state and the traveling speed as the former variables and having the dynamic frictional coefficient between the road surface and a tire as the posterior variables and the membership function of each above-described variable which is allotted for a prescribed fuzzy label. Then, a driving mechanism 12 such as a throttle valve in an engine is controlled by a speed control circuit 10 according to the dynamic frictional coefficient outputted from the fuzzy controller.

Description

[Detailed description of the invention] (Industrial application field) The present invention relates to a speed control device for a motor vehicle.

(Prior Art) As a conventional speed control method for an automobile, there is a maximum speed control method in which a maximum speed limit is set, and when the traveling speed exceeds the maximum speed limit, the degree of ignition of a plug is limited.

(Problem to be solved by the invention) However, such conventional maximum speed control methods,
Since it was not adapted to the road surface conditions, there was a problem in that when the road surface was slippery, there was a risk that the vehicle would slip or fall even if it was within the maximum speed limit.

The present invention has been made in view of such problems, and an object of the present invention is to enable speed control according to road surface conditions.

(Means for Achieving the Problem) In order to achieve such an object, the speed control device for an automobile of the present invention includes a detection means for detecting the road surface condition and the traveling speed of the automobile, and a A plurality of fuzzy rules in which input data related to road surface conditions and traveling speed are used as antecedent variables, and the dynamic friction coefficient is used as a consequent variable, and each of the antecedent variables and consequent variables are assigned to each fuzzy label. The present invention is characterized by comprising a fuzzy controller that fuzzy controls the speed of the vehicle according to the membership function of each variable.

(Operation) According to the above configuration, the dynamic friction coefficient is fuzzy inferred using the road surface condition and the traveling speed, and accurate speed control is performed according to the inference result.

(Example) Hereinafter, an example of the present invention will be described in detail with reference to the drawings.

FIG. 1 is a block circuit diagram of a speed control device for an automobile according to an embodiment of the present invention. In FIG. 1, reference numeral 2 denotes a road surface condition detection means that transmits ultrasonic waves to the road surface and detects the road surface condition based on the reflected waves of the ultrasonic waves from the road surface. To be more specific, the above-mentioned reflected waves from a dry road surface, a frozen road surface, a road surface with many pebbles, a road surface with puddles, etc., have different timings from transmission to reception of the reflected waves, and their waveforms and levels. Since it is different, road surface condition detection means 2
stores them in a table memory in advance, and then displays the reflected wave waveform/waveform stored in the table memory.
By comparing the level with that of the reflected wave from the reflected wave measurement section, a road surface condition signal X1 is output in the form of a voltage.

Reference numeral 6 denotes a running speed detection means for detecting the running speed of the automobile and outputting a running speed signal x2 in the form of a voltage according to the detection.

8 is a diagram in which the road surface condition signal X11 and the traveling speed signal X2 inputted from each of the detection means 2.6 are used as antecedent variables, and the dynamic friction coefficient y between the road surface and the tires is used as a consequent variable. The plurality of fuzzy rules shown and each antecedent variable 111 assigned to each fuzzy label shown in FIGS. 3-4. This is a fuzzy controller that fuzzy controls the speed of the vehicle according to X2 and the membership function of each consequent variable y.

Reference numeral 10 denotes a speed control circuit that responds to the dynamic friction coefficient output output from the fuzzy controller 8 in the form of one voltage. Reference numeral 12 denotes a drive mechanism for a throttle valve of the engine, which is driven based on a control signal from the speed control circuit 10.

The fuzzy controller 8 stores a plurality of types of fuzzy rules in the form of if (antecedent part) to then (consequent part) shown in FIG. In each fuzzy rule shown in FIG. 2, xi and x2 are antecedent variables given from the corresponding road surface condition detection means 2 and traveling speed detection means 6, respectively, y is a consequent variable of the dynamic friction coefficient, NL... - Each PL is a fuzzy label name of a fuzzy set to which the antecedent variable and the consequent variable belong. The fuzzy labels for xi are NL: r smooth J, NM: r quite fine, NS: somewhat fine, ZR: normal, PS:
r Slightly rough J, PM: r Fairly rough", PL: "Rough"
, and the fuzzy labels related to speed are ZR: r stop J, PS: r low speed J, PM: "medium speed J, PL: r
The fuzzy labels regarding the dynamic friction coefficient y are ZR: r small J, PS: r slightly small, l, PM: r slightly large J, PL: r large.

For example, rule 1 [if x 1=NL, X 2=P
According to the linguistic expression, “L then y=ZR]
If the road surface is smooth and the vehicle is traveling at high speed, the coefficient of kinetic friction will be ', and the rule n[if X1=PL, x2=
According to the linguistic expression, PS then y=PL] is "dynamic friction coefficient output when the road surface is rough and the vehicle is traveling at low speed."

Furthermore, the fuzzy controller 8 is shown in FIGS. 3(a) and 3(b),
Antecedent variable Xl as shown in FIG.

2. The membership function of each of the consequent variables y in the membership function coordinate system is stored. Third
The horizontal axis in FIG. 3(a) shows the roughness value, and the horizontal axis in FIG. 3(b) shows the velocity value. The horizontal axis of FIG. 4 shows the dynamic friction coefficient value.

Next, the operation of the speed control device shown in FIG. 1 will be explained with reference to FIGS. 2 to 4.

First, the signal x given from each detection means 2.6
Based on l=α, ×2=β, membership values that fit the corresponding membership functions of each fuzzy rule from FIGS. 3(a) and (b), respectively, NLf (α)=0. N
Mf (α)=0. NSf (α)=0.7. ZRf
(U)=0.3. PSf ((t)=0°PMf (a
') = 0. PLr (a”)=O, ZRf (β)=0
．． PSf(β')=0.8. PMf (13>=0.
2°PL, rCβ)=0 is obtained. Then, for each fuzzy rule, the smallest membership value of each antecedent part XI, X2 is selected as the antecedent part suitability (
MIN operation). For example, rules! In, since each membership value of the antecedent part is [0,0], the antecedent part fitness is "
0". In this way, each membership function with respect to y of each fuzzy rule is cut from FIG. 4 based on the antecedent suitability obtained for each rule, and each membership function with respect to y of all the cut fuzzy rules is superimposed. (MAX calculation), dynamic friction coefficient data Y regarding the dynamic friction coefficient y at the position corresponding to the position of the center of gravity G of the superimposed figure shown by the diagonal line is output.

This data Y is given to the speed control circuit 1O as a voltage signal, and a control signal corresponding to the data Y is given from the speed control circuit IO to the throttle valve drive mechanism 12. , the throttle valve is closed to limit the fuel supply, thereby maintaining the vehicle speed at a safe speed without slipping.

In the opposite case, the throttle flight is opened and the fuel supply is not restricted.

(Effects of the Invention) As is clear from the above explanation, according to the present invention, the dynamic friction coefficient is fuzzy inferred using the road surface condition and the traveling speed, and the speed of the vehicle is controlled according to the inference result. Appropriate speed control is performed according to road conditions.

[Brief explanation of drawings]

The figures relate to an embodiment of the present invention, FIG. 1 is a block diagram showing the configuration of a speed control device according to the embodiment of the present invention, and FIG. 2 shows fuzzy rules stored in the fuzzy controller of FIG. 1. 3(a) and 3(b) each show a membership function for an antecedent part variable, and FIG. 4 shows a membership function for a consequent part variable. 2... Road surface condition detection means, 6... Traveling speed detection means, 8... Fuzzy controller.

Claims (1)

[Claims] (1) A detection means that detects the road surface condition and the traveling speed of the vehicle, and each data regarding the road surface condition and the traveling speed input from the detection means is used as an antecedent variable, and the coefficient of dynamic friction is used as a consequent variable. A fuzzy controller that fuzzy controls the speed of the vehicle according to a plurality of fuzzy rules and membership functions of each of the antecedent and consequent variables assigned to each fuzzy label. Automobile speed control device.