Control Strategy of Electric Dynamometer Based on the Improved Whale Optimization Algorithm

With the rapid development of the new energy vehicle industry, the application prospects of electric dynamometers are expanding, and the requirements for control accuracy are increasingly demanding. To address the speed overshoot phenomenon of electric dynamometers under different test conditions, an Improved Whale Optimization Algorithm (IWOA) is proposed to optimize the control parameters of traditional PID controllers. Firstly, the working principle of the electric dynamometer was analyzed, and its mathematical model was established. Subsequently, to address the low diversity of the initial population in the traditional whale optimization algorithm, a chaotic mapping approach was introduced to enhance the diversity of the initial population. Thereafter, the improved algorithm was applied to optimize the control parameters of the electric dynamometer. A speed regulation simulation model of the electric dynamometer was built in Matlab/Simulink, and experimental analysis was conducted. The test results demonstrate that the optimized system reduces speed overshoot and improves control accuracy.