Conditioned Adaptive Barrier Function Based Integral Super-Twisting Sliding Mode Control for Electric Vehicles With Hybrid Energy Storage System

Abstract

This paper proposes a conditioned adaptive barrier function-based integral super-twisting sliding mode controller for the hybrid energy storage system (HESS) with a field-oriented control of 3-phase induction motor for the electric vehicles (EVs). The conditioned approach ensures that the control input stays within bounds, the adaptive barrier adjusts the sliding mode controller (SMC) gains, and the super-twisting technique helps in reducing the chattering. Consequently, the overall system performance is improved. The HESS consists of a fuel cell, battery, and super-capacitor. A rule-based energy management system has been designed, defining different modes of operation for an efficient use of energy sources under different loading conditions. The designed energy management system accounts for the power inflow and the status of the energy sources. The proposed controller ensures smooth energy sources current tracking and stabilizes the DC bus voltage while controlling the motor speed and flux under various operating conditions. The controller's global asymptotic stability has been verified through Lyapunov stability analysis. Intensive computer simulations using Matlab/Simulink are performed to validate the proposed controller's performance and compare it with the conventional PI and SMC controllers. Finally, controller hardware-in-the-loop validation has been conducted for the real-time performance validation.