Electric Vehicle Integrated With PMSM and Regenerative Braking System Speed Evaluation Based on Diverse Control Strategies

Abstract

The choice of a vehicle speed controller for a permanent magnet synchronous driven battery electric vehicle (BEV), integrated with a regenerative braking system (RBS), plays a pertinent role in how far a vehicle can travel. While many studies have implemented varied control strategies, the proportional-integral (PI) based controller is predominately studied and practically used. Generally, the performance of PI controller compared to Modeled Predictive Controller; Reference Tracking Signal Controller Based on Generated Polynomial and Reference Tracking Signal Controller Based on Controlled Polynomial in a permanent magnet synchronous motor (PMSM) driven battery electric vehicle integrated with RBS speed control based on field-oriented control mechanism is lacking. In order to address that shortcoming, this paper aims to investigate the performance of a PI controller compared to generalized predictive controllers based on the difference between a reference speed and a controlled speed of the battery electric vehicle. The performance for each controller considered was evaluated in terms of the state of charge (SOC), R^2, slip ratio, minimum error metrics, and peak speed using real-time driving scenario factoring braking, throttling, wind speed, and cruise effects for 15 s. The results show that the PI controller outperforms the other controllers on most metrics. Except for the peak SOC, slip ratio, and peak speed, the Reference Tracking Signal Controller Based on Generated Polynomial seems to be better, although with a drawback of the highest error metrics. Generally, all the controllers yielded excellent regenerative braking effects in SOC and effective control of the speed trajectory.