Sensing System Assisted Novel PID Controller for Efficient Speed Control of DC Motors in Electric Vehicles

PID controllers are widely used in different systems including electric vehicles (EVs) for their simplicity and practical application. However, there are errors between the controlled signal and the desired signal. This system controls EV speed using a sensor feedback-supported novel controller based on a novel dandelion optimization PID controller (DO-PID). This letter aims to reduce system error between the reference and output signals. The results obtained from the proposed controller are compared with classical PID control, firefly-PID controller, teaching learning-based optimization-PID controller, and particle swarm optimization-PID controller. Simulation results show that the novel controller outperforms the existing controllers. Various types of errors are found for all the controllers, and it is seen that the error obtained from DO-PID is less than the error from other controllers. It is found that the integral square error, integral absolute error, integral error, integral time square error, and integral time absolute error in controlling the speed of EV with DO-PID controller are obtained as 0.04161, 0.1115, 0.04022, 0.02068, and 0.02068, respectively. Finally, analysis has been done to check the disturbance rejection capability of the proposed controller.