Electric Vehicle Traction System Performance Enhancement Using a High-Gain Adaptive Controller

Abstract

Electric vehicle traction systems often incorporate a field-oriented induction motor drive system with a proportional-integral (PI) speed controller having fixed gains. However, under external disturbances and parameters variation, the speed regulator performance may degrade. This work proposes solutions for tuning the PI gains of the speed regulator by using a high-gain adaptive controller, which automatically adjusts the PI controller gains based on the motor speed tracking error. To overcome gains drift caused by sensor noise, potentially leading to instability, modifications like the sigma, dead-zone, and epsilon method are applied to the adaptive law. Preliminary simulations and experimental results show that the epsilon modification-based high-gain controller outperforms the sigma and dead zone modifications for the induction motor drive system. Therefore, rigorous experimental validation of the epsilon-modified high-gain controller on an indirect field-oriented induction motor drive system is demonstrated for the following cases: square wave speed reference tracking, external disturbance rejection, detuning, field weakening, as well as different initial conditions for gains. Finally, the controller’s performance is also investigated on a prototype electric vehicle (EV) traction system that consists of a 2.2 KW induction motor powered by a 400V, 6.6 A.h Li-ion battery bank. The experimental results on the prototype EV traction system validate a better speed tracking performance as compared to the fixed gains PI controller while requiring almost the same amount of current.

Keywords

• Electric vehicle
• induction motor drive
• speed regulation
• indirect field orientation
• high-gain adaptive controller