Abstract
The electric vehicle anti-skidding control system is used to ensure the stability of the vehicle under any circumstances. There is a typical feature in most anti-skidding detection methods; the skidding occurs first, and then the detection is performed. For methods that rely on slip rate detection, more accurate vehicle speeds are required, which are often difficult to accurately observe. The previous method was detection and could not do prediction. Skidding prediction can improve driver reaction time and increase safety. Therefore, this paper proposes a prediction method that does not depend on the slip rate. The skidding prediction can be performed by relying on the driving torque, as well as the wheel speed. In this paper, the characteristics of the transmission from the driving force to the friction force in the vehicle model are analyzed. As for the distributed electric vehicle, the slip factor was designed with traction torque and friction force for skidding prediction by its sharp increase before the maximum adhesion point. The variation in the slip factor and time period of skidding are revealed. A multi-information merged prediction model is designed to improve reliability. The co-simulation and experimental verification based on the physical skidding simulation platform are carried out.
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