Based on the traits of the four-wheel drive EV, a self-adaptive Kalman filter was applied to gain the information of vehicle velocity and traction forces on four wheels. With the estimated vehicle velocity and the driving forces on four wheels, the slope k of the curves of adhesion coefficient versus slip rate could be calculated and consequently the road adhesion condition could be accurately identified. Through calculating the difference between the estimated slope k with the optimized slope k as a control reference, the output torques of the motors were adjusted instantaneously to improve the using rate of the adhesion as well as the rationality of the traction control strategy. Simulation results illustrate that whether on high adhesion or low adhesion roads the vehicle is passing, the strategy can estimate the k effectively.


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    Title :

    Electric Vehicle Tire Slip Identification Method Based on Self-Adaptive Kalman Filter



    Published in:

    Advanced Materials Research ; 503-504 ; 1070-1073


    Publication date :

    2012-04-12


    Size :

    4 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English