Control of DC adjustable speed electric vehicle based on PSO-PID algorithm optimization research

At present, electric energy vehicles gradually replace traditional fuel vehicles as the mainstream transportation with their advantages of saving environment, which makes the research of motor speed control a mainstream technology. Aiming at the problem that the parameters of the double closed-loop speed controller, which is widely used in new energy vehicles, are still difficult to adjust in actual speed regulation, resulting in poor control effect, this paper proposes a particle swarm optimization (PSO)-based control algorithm for electric vehicles to improve the anti-interference capability of the motor, so as to better adapt to the actual operation of the motor controller. Firstly, the motor is modeled and analyzed; then the speed control and observation of the motor is realized by using the PID control method based on the speed loop; finally, in order to improve the stability of the motor speed and the anti-interference ability of the real-time control, the PSO algorithm is introduced in the controller to adjust the PID parameters of the inner loop in real time, thus realizing the control of the DC motor speed control system. In addition, simulation experiments were performed in Matlab/Simulink and ITAE metrics were introduced to demonstrate the optimization process of PSO. The results show that the DC motor speed control system under the joint PSO-PID control has faster response and stronger anti-interference capability, and the research results are of great value for engineering guidance.t.