Model Based Yaw Rate Estimation of Electric Vehicle with 4 in-Wheel Motors

This paper describes a methodology to estimate yaw rate of a 4-wheel-drive electric vehicle, in which wheel driven torque can be independently controlled by electric motor. Without non-driven wheels it would be difficult to estimate the vehicle yaw rate precisely, especially when some of the four wheels have large slip ratio. Therefore, a model based estimation methodology is put forward, which uses four wheel speeds, steering wheel angle and vehicle lateral acceleration as input signals. Firstly the yaw rate is estimated through three different ways considering both vehicle kinematics and vehicle dynamics. Vehicle kinematics based method has good estimation accuracy even when the vehicle has large lateral acceleration. However, it can not provide satisfying results when the wheel has large slip ratio. In contrast, vehicle dynamics based method is not so sensitive to wheel slip ratio. However, due to the parameter variation by large lateral acceleration, e.g. effective cornering stiffness, the estimation result is no more reliable. Therefore a fuzzy logic that depends on driving situation is adopted to calculate the weighted average of three estimated results. Finally the proposed method is validated through experimental data