Speed Control Simulation of the Electric Vehicle Driving Motor

Abstract

In order to realize precise speed control of driving motor, an adaptive fuzzy PID control strategy for motors was established based on the existing proportional-integral-derivative (PID) control theory. The motor speed control model is built by simplifying the parameters of a brushless DC motor using the Sim Power Systems toolbox in MATLAB/Simulink environment, which involves the simulation of motor speed control including low speed, high speed, and road bump situations in city traffic environment. Results show that the time of the adaptive fuzzy PID control is 0.08s at low speed, the adjustment time of the conventional PID control is 0.22s, and the adjustment times are 0.12s and 0.32s at high speed. After encountering road bumps, the adaptive fuzzy PID control can quickly react and return to normal speed, whereas the conventional PID control is evidently affected by the interference.

Brushless DC Motor Control Strategy for Electric Vehicles

“…Brushless DC motor, as the controlled object, includes the motor speed and current adaptive fuzzy PID control [4]. For example, in a speed loop, the controller inputs the error e and the error rate of change ec after the detected speed feedback value is compared with a given value.…”