Based On Adhesion Coefficient ASR Adaptive Fuzzy Control For Electric Vehicle

Anti Skid Regulation(ASR) is a kind of automobile electronic equipment, which can control automobile driving wheels’skid to enhance the automobile driving performance and traffic safety. Anti Skid Regulation (ASR) is a kind of active safety control system. It is an extension of the antilock brake systems (ABS). Through controlling automotive drives an droller-blading turning rate, ASR can prevent the driving wheels of cars from excessive spinning at the beginning, accelerating and hill-climbing maneuvers. ASR can make sure the cars get the maximum traction and the best driving stability through using full of vertical adhesion and lateral adhesion from the ground as to enhance stability of the vehicle. Therefore, further study on anti skid regulation system car (ASR) is of great significance to solve the stability and safety.This paper mainly studies the vehicle anti skid regulation control systems. We will use the hub motor arrangement, controlled by regulating the motor voltage to the motor output torque, so that the wheel slip ratio remained near the ideal value (slip rate of10%-20%, the road can be made available to the wheels of the largest longitudinal adhesion coefficient and ideal lateral adhesion coefficient). The main research content includes the following sections:(1) Establish the ASR system model based on the adhesion coefficientFirst, we selected the structure of the electric vehicles in the program, and determined the relevant parameters. Then According to the relevant formulas we established the dynamic model、motor model、wheel model and the slip ratio calculate model in Simulink of Matlab.(2)Based on the classified adhesion coefficient of the research of PD control、fuzzy controlFirst, based on experience we design a two-input single-output PD controller. It can simulate the electric cars and analyze the ability of self-control of cars on different grounds. Then we design a fuzzy controller and analyze the ability like the PD controller. We have found that PD control have some features such as smooth transition, none of steady-state error and adaptive capacity. The most important feature for electric cars is that it is very comfortable for the cars to work on the road with low friction coefficient. At the same time, fuzzy control has the features that shorter transition time, and this control is more comfortable of working on the ground with high friction coefficient.(3)Based on the classified adhesion coefficient of the research of the research of PD+fuzzy compensationAs the PD control and fuzzy control have their each advantage, we want to imagine making the two parts together like the style of compensation controller. Through simulation we can find that:compensation control perform well on the transition time, steady-state error and adaptive capacity. These can express that compensation is possible.(4)Based on the adhesion coefficient of the adaptive compensation control systemBecause the mechanism modeling of the Electric car driving wheels is hard to be built, the compensation control based on the mechanism model of the friction cannot be achieved. For this case, an application of adaptive fuzzy system and PD control is presented for compensating the effect induced by the friction in robot system. And the Lyapunov stability theory is adopted to prove the uniform boundness of the tracking error. Simulation results and experiments show the effectiveness of this method.