State-Timing Based Adaptive Field Weakening Control for Ultracapacitor-Fed Induction Motor Electric Vehicles

Abstract

The demand for high-performance and energy-efficient electric vehicles (EVs) is driving the development of advanced motor control strategies and optimized energy management systems. Induction motors (IMs), due to their inherent robustness and cost-effectiveness, remain a prominent choice for EV traction applications. However, enhancing their high-speed performance and achieving superior energy utilization, particularly in conjunction with ultracapacitor-based (UC) energy storage, is still a significant challenge.This paper presents a novel State-Timing Based Adaptive Field Weakening Control (ST-AFWC) strategy tailored for ultracapacitor-fed IM electric vehicles. The proposed approach dynamically adjusts the stator flux reference based on real-time motor state variables (speed, torque, and acceleration demand) and timing cues derived from vehicle dynamics. This allows the drive system to seamlessly transition between different operating regions while optimizing both performance and energy efficiency.Extensive simulations were performed in MATLAB/Simulink R2021a, incorporating detailed models of the induction motor, ultracapacitor dynamics, and vehicle longitudinal behavior. Experimental validation was conducted using a dSPACE-based real-time test bench, featuring a coupled motor-dynamometer setup and ultracapacitor emulation, with the ST-AFWC algorithm implemented on a TI DSP F28379D controller.The results demonstrate that ST-AFWC achieves up to 15-20% higher high-speed capability, 8-10% overall efficiency improvement, and 12% enhancement in regenerative braking energy recovery, compared to conventional field weakening methods. Furthermore, the adaptive control significantly reduces ultracapacitor voltage ripple and improves energy utilization, contributing to extended system lifespan. These findings validate ST-AFWC as a practical and scalable solution for next-generation ultracapacitor-fed IM EVs.