Abstract:

 A vehicle mass estimation algorithm, which can adapt to the variation of air resistance, windward area and transmission ratio, was proposed to reduce the dependence of mass estimation model on vehicle parameters for electric vehicle (EV) in engineering applications. The reduction of transmission ratio and slope were identified on the base of the vehicle operation information obtained through vehicle terminal. The air density, windward area and wind resistance coefficient extracted from air resistance were regarded as a parameter, which was identified by the extended Kalman filter algorithm together with the vehicle mass. The results show that the average error of quality parameter identification is 3.74% under different vehicle mass and road environments. The proposed algorithm can estimate vehicle mass in real time with good adaptability to variation of vehicle and environment parameters.

Key words: electric vehicle (EV) , vehicle mass , parameter-adaptive , identification algorithm ,  extended Kalman filter (EKF) , slope reconstruction