| Summary: | This paper designed a fuzzy adaptive proportional integral differential (PID) control algorithm to optimize the overshoot of speed and torque, fuel consumption and exhaust emissions of the traditional PID control strategy in the process of working condition switching of an extended range electric vehicle. The simulation was carried out in Matlab/Simulink, and the optimization of the control strategy was verified by a bench test. The results show that the fuzzy adaptive PID control strategy effectively reduced the speed overshoot in the process of working condition switching compared with the traditional PID control strategy. The bench test proved that the fuzzy adaptive PID control strategy could effectively optimize the switching process, especially in the speed and torque reduction switching process, and the speed overshoot rate of the fuzzy PID control was greatly reduced to 0.7%, far less than that of the traditional PID control with 6.6%, while the torque overshoot rate was within 0.8%. Additionally, the fuzzy adaptive PID control could effectively reduce the fuel consumption, especially in the switching process of increasing the speed and torque, where the fuel consumption of the fuzzy adaptive PID control was 2.1% and 0.5% lower than that of the traditional PID control, respectively. Additionally, the fuzzy adaptive PID control could also reduce the particulate emissions, especially in the process of increasing the speed and torque, where the number of particles of the fuzzy PID control was 11% and 19% less than that of the traditional PID control, respectively. However, the NOx emissions based on the fuzzy PID control were slightly higher than those of the traditional PID control due to the smooth operation and improved combustion.
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