Search Results

The in-wheel-motor (IWM) drive system has some interesting features, such as the vibration of this structure at low velocity. An explanation of this phenomenon is given in this paper by considering the dynamics performance of the in-wheel motor drive system under small slip ratio conditions. Firstly, a frequency response function (FRF) is deduced for the drive system that is composed of a dynamic tire model and a simplified motor model. Furthermore, an equation between the resonance velocity with the parameters of the drive system is obtained by combining the resonance frequency of this drive system with the fundamental frequency of the motor. The correctness of the equation is demonstrated through simulations and experimental tests on different road surfaces. The impact of different parameters on the vibration can be explained by this equation, which can give the engineer some instructions to design a control method to avoid this feature.

As a typical parameter of the road-vehicle interface, the road friction potential acts an important factor that governs the vehicle motion states under certain maneuvering input, which makes the prior knowledge of maximum road friction capacity crucial to the vehicle stability control systems. Since the direct measure of the road friction potential is expensive for vehicle active safety system, the evaluation of this variable by cost effective method is becoming a hot issue all these years. A ‘wheel slip based’ maximum road friction coefficient estimation method based on a modified Dugoff tire model for distributed drive electric vehicles is proposed in this paper. It aims to evaluate the road friction potential with vehicle and wheel dynamics analyzing by using standard sensors equipped on production vehicle, and fully take the advantage of distributed EV that the wheel drive torque and rolling speed can be obtained accurately.

This paper proposes an estimation method of road-tire friction coefficient for the 4WID EV(4-wheel-independent-drive electric vehicle) in the pure longitudinal wheel slip, lateral sideslip and combined slip situations, which fuses both estimated longitudinal and lateral friction coefficients together, compared with existing methods based on a tire model in one single direction. Unscented Kalman filter (UKF) is introduced to estimate one-directional friction coefficient based on a modified Dugoff tire model. Considering the output results for each direction as a signal for the same target with different noise, MSE-weighted fusion method is proposed to fuse these two results together in order to reach a higher accuracy. The tire forces are estimated with the benefits of the 4WID EV that the driving torque and rolling speed of each wheel can be accurately known. The sideslip angles and slip ratios of each tire are calculated with a vehicle kinematic model.

A new dynamic tire model for estimating the longitudinal/lateral road-tire friction force was derived in this paper. The model was based on the previous Dugoff tire model, in consideration of its drawback that it does not reflect the actual change trend that the tire friction force decreases with the increment of wheel slip ratio when it enters into the nonlinear region. The Dugoff model was modified by fitting a series of tire force data and compared with the commonly used Magic Formula model. This new dynamic friction model is able to capture accurately the transient behavior of the friction force observed during pure longitudinal wheel slip, lateral sideslip and combined slip situation. Simulation has been done under different situations, while the results validate the accuracy of the new tire friction model in predicting tire/road friction force during transient vehicle motion.