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


    Contributors:


    Publication date :

    2012


    Size :

    4 Seiten




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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