Title: PI gain optimisation and artificial intelligence based direct torque control of induction motor equipped electric vehicle drives

Authors: Nitesh Tiwari; Shekhar Yadav; Sabha Raj Arya

Addresses: Department of Electrical Engineering, Madan Mohan Malaviya University of Technology, Gorakhpur, UP, India ' Department of Electrical Engineering, Madan Mohan Malaviya University of Technology, Gorakhpur, UP, India ' Department of Electrical Engineering, Sardar Vallabhbhai National Institute of Technology, Surat, India

Abstract: The objective of this paper is to design DTC-based IM drives for EV applications by using PI and artificial intelligent controllers. Two artificial intelligent controllers namely ANN and ANFIS are compared in this paper. The designing process of the ANFIS controller is independent of the drives, IM, or EV parameters. ANFIS controller only takes input-output data set to restructure the membership function artificially. IM-based EV drives system is a purely nonlinear system whose performance depends on the sudden change of speed and torque. Hence, controlled parameters of the motor drives system are needed to calculate very precisely. Some metaheuristics optimisation techniques such as DE, TLBO, GA, PSO, ABC, GWO, and JFO are implemented in this paper for obtaining the optimised value of the controlled parameter of the PI controller. The main advantage of using these optimisation techniques is that system identification is not required for implementation.

Keywords: differential evolution; grey wolf optimisation; jellyfish optimisation; artificial neuro-fuzzy inference system; electric vehicle; driving cycle.

DOI: 10.1504/IJEHV.2023.132034

International Journal of Electric and Hybrid Vehicles, 2023 Vol.15 No.2, pp.151 - 182

Received: 20 May 2022
Accepted: 16 Aug 2022
Published online: 07 Jul 2023 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article