Comparative study of PID control algorithms for an electric vehicle

Abstract

Electric vehicles have emerging as prominent alternative for sustainable, clean and cleaner energy emissions in transportation. Modelling and controlling of electric vehicles have attracted increasing attention from researchers. Proportional Integral derivative (PID) controllers are most extensively used in the control of any system because of their simplicity, robustness, and successful practical application. A comparative study of the different control algorithms used in the PID controller of an electric vehicle is carried out in the present work, including the control of the electric vehicle for the Transfer Function model by applying three control algorithms, i.e., the Ziegler-Nichols (ZN) algorithm, Modified ZN (MZN) algorithm, and the Internal Model Control (IMC) algorithm for the second order transfer function model and the equivalent first-order with delay time (FOPDT) model of an electric vehicle. It also includes control of the electric vehicle using the state space model by applying two control algorithms, i.e., the Linear Quadratic Regulator (LQR) algorithm and the Pole Placement (PP) algorithm. The gain values of the PID controller Kp, Ki, and Kd are calculated by considering Transfer function case and the State space model case. The performance of these approaches is evaluated by using the Integral-Square-Error (ISE), Integral-Absolute-Error (IAE), Integral-Time-Absolute-Error (ITAE), and the Integral-Time-Square-Error (ITSE). The comparison is carried out based on domain specifications and performance indices, in order to identify the superiority of the control techniques.