CN101867339B - Motor control method of electronic mechanical braking system - Google Patents

Abstract

The invention provides a motor control method of an electronic mechanical braking system. The control method adopts a fuzzy controller and takes an error E of the practical slip rate S of wheels and the optimum expected slip rate S0 set by the system and the change rate EC of the error E as the double input of the fuzzy controller; and the variable quantity U of the current of the motor is obtained by a fuzzy control table-look-up method. The motor control method has fast response speed and small overshoot, and can improve the adaptability of the electronic mechanical braking system for all pavements.

Description

A kind of motor control method of electromechanical braking system

Technical field

Design vehicle braking technology of the present invention field is specifically related to a kind of motor control method of electromechanical braking system.

Background technology

The braking moment of electromechanical braking system is compared with traditional brake fluid system by being installed in being produced by motor-driven brake mechanism on four tires, can simplify braking system structure, be convenient to arrange, assembling and maintenance.And because the nonlinear Control of changeable and tire of vehicle condition in the braking procedure need to provide to the motor of electromechanical braking system a kind of fast response time, overshoot is little, can improve the control algolithm to the adaptive capacity on various road surfaces.

Summary of the invention

Technical problem to be solved by this invention is to provide a kind of motor control method of electromechanical braking system, its fast response time, and overshoot is little, can improve electromechanical braking system to the adaptive capacity on various road surfaces.

Operation principle of the present invention such as Fig. 1 comprise the steps:

A, data acquisition: the controller collection is installed in the pulse signal of the wheel speed sensors on the wheel, obtains each wheel wheel speed angular velocity signal; By the wheel wheel speed signal, calculate vehicle velocity V, according to formula S=1-ω r/V, ω represents wheel speed angular speed, and V represents the speed of a motor vehicle, obtains the slip rate S of car load reality;

B, controller obtain error rate EC after differentiating according to the error value E of actual slip rate S and best expectation slip rate S0 and error value E, with error value E and the error rate EC input variable as fuzzy controller, obtain output variable U by the fuzzy control look-up table, described U is the variable quantity of torque motor electric current in the electromechanical braking system, when error E is larger, output variable U should be fast as far as possible the minimizing error E, and when error E more hour, the control of output variable U is leading by EC, EC is larger, and U is less in output.This fuzzy reasoning control law is to formulate according to expert of the art's manual control law, the principle that lays down a regulation is: when error is larger, controlled quentity controlled variable should reduce error as quickly as possible, when error hour, except eliminating error, also the stability of necessary taking into account system is shaken to avoid unwanted hyperharmonic;

C, controller increase or reduce the electric current of motor according to output variable U, thereby increase or reduce braking moment.

The operation principle of electromechanical braking system of the present invention such as Fig. 1.

The fuzzy control that the present invention sets up is achieved in that by formula y=(n-m) * [x-(b-a)/2]/(b-a) the obfuscation of input variable E and EC and output variable, [a wherein, b] be the actual range of controller input variable, [m, n] be fuzzy subset's domain, actual input variable E and EC are transformed into variable Y 1 and Y2 in fuzzy subset's domain, change into again the fuzzy value of input variable E and EC by the triangle membership function; The membership function of the output variable U of fuzzy controller also adopts the triangle membership function.The progression of the triangle membership function of input and output identical and as required the definition.Be normally defined 5 grades.

The present invention can carry out precision by gravity model appoach to the fuzzy subset's of fuzzy control reasoning process output reverse gelatinization and calculate, and obtains the accurate output variable U of fuzzy controller, and the reverse gelatinization computing formula of fuzzy controller is $U=\frac{\underset{j=1}{\overset{k}{\mathrm{\Σ}}}{\mathrm{\θ}}_j\left(\underset{i=1}{\overset{n}{\mathrm{\Π}}}{\mathrm{\μ}}_{A_i^j}\left(x_i\right)\right)}{\underset{j=1}{\overset{k}{\mathrm{\Σ}}}\left(\underset{i=1}{\overset{n}{\mathrm{\Π}}}{\mathrm{\μ}}_{A_i^j}\left(x_i\right)\right)},$ Wherein

The membership function value of output variable U, θ _jFuzzy subset's domain value for the output variable U of the fuzzy controller of correspondence.Also can pass through the gelatinization of additive method reverse.

Described motor can be selected pulsewidth regulation and control (PWM) motor.Carry out the motor of regulation and control and select pulsewidth regulation and control (PWM) motor, the output variable U of fuzzy control of the present invention is percentage, and output variable is as the pulsewidth regulation and control duty ratio (PWM) of pulsewidth regulation and control motor.

The motor control method of a kind of electromechanical braking system that proposes according to the present invention, key is that this control method adopts fuzzy controller, expect the error E of slip rate S0 with the best of wheel actual slip rate S and default, and the rate of change EC of error E is as the dual input of fuzzy controller, by the controlled output of fuzzy control look-up table, output variable is the variable quantity U of current of electric.

Use the present invention, can utilize Fuzzy control system not need the mathematical models of control object, fast response time, the characteristic that overshoot is little is improved the response characteristic of electromechanical braking system, improves the adaptive capacity to various road surfaces.

Description of drawings

Fig. 1 is the fundamental diagram of electromechanical braking system of the present invention;

Fig. 2 is the control model of fuzzy control of the present invention;

Fig. 3 is fuzzy control input and output functional arrangement of the present invention;

Fig. 4 is the manual control law of fuzzy reasoning process of the present invention.

Embodiment

The below describes embodiments of the invention in detail.

The major control target of mechanical type brake system electric is to allow actual slip rate S follow the tracks of all the time expectation slip rate S0 in whole braking procedure, producing maximum road surface attachment systems, thereby all can obtain preferably braking ability in the situation of various different road surfaces.

The mathematical control model of the fuzzy control of the present embodiment such as Fig. 2.The present embodiment is with formula S=1-ω r/V, ω represents wheel speed angular speed, V represents the speed of a motor vehicle, obtain actual slip rate S by divider and adder-subtracter, subtract each other with expectation slip rate S0 by adder-subtracter and to obtain error value E, E obtains error rate EC by differential, and E and EC are as two inputs of the control table (2-D) of fuzzy controller, obtain exporting U by tabling look-up, the output U of this example is the pulsewidth regulation and control duty ratio (PWM) of pulsewidth regulation and control (PWM) motor.

The operation principle of fuzzy controller is as follows:

The input variable of 1 selective system, output variable;

2, the exact value with input variable becomes fuzzy quantity;

3, according to input variable (fuzzy quantity) and fuzzy control rule, press the fuzzy deduce synthesize rule and calculate fuzzy control quantity;

4, calculate accurate controlled quentity controlled variable by fuzzy control quantity obtained above.

The input variable of Fuzzy control system is the actual slip rate S and the error value E of expectation slip rate S0 and the rate of change EC of error value E of electromechanical braking system; Output variable U is the variable quantity of torque motor electric current in the actual electromechanical braking system.

The membership function of E, EC and output variable U as shown in Figure 3.By formula y=(n-m) * [x-(b-a)/2]/(b-a), [a wherein, b] be the actual range of fuzzy controller input variable, [m, n] be fuzzy subset's domain, actual input variable E and EC are transformed into variable Y 1 and Y2 in fuzzy subset's domain, change into again the fuzzy value of input variable E and EC by the triangle membership function; The membership function of the output variable U of fuzzification process also adopts the triangle membership function.Here the variable grade of triangle membership function is 5 grades, and the membership function of input variable E, EC and output variable U is equally distributed.

The fuzzy control rule of fuzzy controller: the fuzzy reasoning form is: IF E=Ai and EC=Bi THEN U=Ci; Wherein Ai is the error fuzzy subset, and Bi is the error change fuzzy subset, and Ci is the output variable fuzzy subset, according to manual control strategy, sums up 25 fuzzy control rules, as shown in Figure 4.Wherein, manually the design principle of control strategy is: when error was larger, controlled quentity controlled variable should reduce error as quickly as possible, when error hour, except eliminating error, stability that also must taking into account system is to avoid unwanted hyperharmonic concussion.Be specially: when error E is larger, the minimizing error that output variable U should be fast as far as possible, and when error E hour, the control of output variable U is leading by EC, EC is larger, output variable U is less.

The fuzzy subset of the output controlled quentity controlled variable U that said process is obtained by the reverse gelatinization calculates accurate controlled quentity controlled variable.Reverse gelatinization formula is $U=\frac{\underset{j=1}{\overset{k}{\mathrm{\Σ}}}{\mathrm{\θ}}_j\left(\underset{i=1}{\overset{n}{\mathrm{\Π}}}{\mathrm{\μ}}_{A_i^j}\left(x_i\right)\right)}{\underset{j=1}{\overset{k}{\mathrm{\Σ}}}\left(\underset{i=1}{\overset{n}{\mathrm{\Π}}}{\mathrm{\μ}}_{A_i^j}\left(x_i\right)\right)},$ Wherein The output membership function value, θ _jFuzzy subset's domain value for the control output variable U of correspondence.

Obtain control table by said process, place fuzzy controller, corresponding different actual slip rate error and error rate thereof can obtain the output variable U of fuzzy controller by tabling look-up, and output variable U is the percentage form, namely the controlled quentity controlled variable of motor.Output variable in this example is the pulsewidth regulation and control duty ratio (PWM) of pulsewidth regulation and control motor, pulsewidth regulation and control motor is controlled the output torque of motor by the size of control motor input current, again by planetary gear, belt pulley, bolt and nut, make nut produce thrust, finally obtain braking moment.

Claims (3)

1. the motor control method of an electromechanical braking system is characterized in that comprising the steps:

A, data acquisition: the controller collection is installed in the pulse signal of the wheel speed sensors on the wheel, obtains each wheel wheel speed angular velocity signal; By the wheel wheel speed signal, calculate vehicle velocity V, according to formula S=1-ω r/V, ω represents wheel speed angular speed, and V represents the speed of a motor vehicle, obtains the slip rate S of car load reality;

B, controller obtain error rate EC after differentiating according to the error value E of actual slip rate S and target slip ratio S0 and error value E, with error value E and the error rate EC input variable as fuzzy controller, obtain output variable U by the fuzzy control look-up table, described U is the variable quantity of torque motor electric current in the electromechanical braking system, the obfuscation of described fuzzy controller is by formula y=(n-m) * [x-(b-a)/2]/(b-a), [a wherein, b] be the actual range of fuzzy controller input variable, [m, n] is fuzzy subset's domain; Actual input variable E and EC are transformed into variable Y 1 and Y2 in fuzzy subset's domain, change into again the fuzzy value of input variable E and EC by the triangle membership function; The membership function of the output variable U of fuzzy controller also adopts the triangle membership function; The reverse gelatinization computing formula of described fuzzy controller is

Wherein

The output membership function value, θ _jFuzzy subset's domain value for corresponding output variable U;

C, controller increase or reduce the electric current of motor according to output variable U, thereby increase or reduce braking moment.

2. the motor control method of electromechanical braking system according to claim 1 is characterized in that the variable grade of described triangle membership function is 5 grades.

3. the motor control method of electromechanical braking system according to claim 1 is characterized in that described motor is pulsewidth regulation and control motors.

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