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The control strategy of switched reluctance motor (SRM) in-wheel motor is investigated in order to reduce the influence of torque ripple of SRM on the ride comfort. The nonlinear model of switched reluctance motor (SRM) is established and the variable angle control strategy with optimal switch angles is applied to control SRM. However, the variable angle control strategy can not reduce the torque ripple of SRM significantly. Therefore, some advanced control strategies are developed to improve the ride comfort in electric vehicle. In this paper, the fuzzy proportional integration differential (PID) is developed to improve the torque ripple of SRM in which the fuzzy control idea is utilized to adjust the parameters of proportional integration differential (PID) control online and ensure the adaptive capabilities of the fuzzy proportional integration differential (PID) control to motor driving system.

In partly autonomous driving such as level 2 or level 3 automatic driving from SAE international classification, the switching of the driving right between the human driver and the machine plays an important role in the driving process of vehicle [1]. In this paper, the data collected from vehicle states and the driving behavior of drivers is completed via a simulator and self-report questionnaires. A fuzzy analytic network process (Fuzzy-ANP) model is developed to evaluate the driving capability of the drivers in real time from vehicle states due to its direct inherent link to the change of the driving state of drivers Moreover, in this model, the idea of group decision and multi-index fusion is adopted. The questionnaire is required to identify the experimental results from the simulator. The results show that the proposed Fuzzy-ANP model can evaluate the driving capability of the participants in real time accurately.