| Abstract: | In-wheel motor vehicles, characterized by the precise torque control and rapid responses, are well-suited for off-road conditions. However, off-road surfaces often present varied undulations and fluctuating adhesion conditions. Therefore, it is important to develop a vehicle drive force control strategy based on off-road condition recognition to improve the longitudinal driving stability of in-wheel motor vehicles. On the basis of the dynamic model, the paper analyzes the adhesion and geometric characteristics of the road surface and determines a set of vehicle characteristic parameters for off-road condition recognition. To address the distortion in estimating the wheel''s vertical load when it''s suspended off the ground, the study corrects the calculations for the vertical load, considering the actual changes in the vertical force from the ground that lead to alterations in the vertical load distribution ratio. Using the mapping relationship between the differences in each characteristic parameter and the off-road conditions, the paper employs fuzzy recognition to define four types of terrain conditions. The upper layer of drive force control takes into account both working conditions and drivers'' personal influences. The results of off-road working condition identification are used to determine the drive utilization coefficient, which serves as the weight for feedforward expected torque adjustment. The middle layer obtains the torque distribution coefficient from the vertical load on the four wheels and forms the drive force allocation algorithm. The lower layer compensates the dynamic torque to address the wheel slipping and suspension under off-road conditions. Both simulation tests and real vehicle verifications show that the off-road condition identification results agree with the expected outcomes, and the drive force control strategy effectively improves the vehicle stability and dynamics. |
