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Tuan, Duong Anh
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Electrical & Electronics Engineering

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Journal : Bulletin of Electrical Engineering and Informatics

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Torque control of PMSM motors using reinforcement learning agent algorithm for electric vehicle application Ha, Vo Thanh; Tuan, Duong Anh; Van, Tran Thuy
Bulletin of Electrical Engineering and Informatics Vol 14, No 4: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i4.7852

Abstract

As electric vehicles (EVs) demand higher performance and efficiency, precise torque control in interior permanent magnet synchronous motors (IPMSMs) becomes increasingly vital. This paper introduces a reinforcement learning (RL)-based method to optimize torque control in IPMSMs. The RL agent is trained to regulate d-axis and q-axis currents, producing stator voltages to follow the desired motor speed. The control system includes an observation vector, voltage-based actions, and a specially designed reward function. Due to the nonlinear dynamics of the motor, training the agent requires significant computational effort. MATLAB/Simulink simulations are performed to compare the RL controller with a traditional PI controller. Results indicate that the RL controller delivers quicker and more accurate performance, although additional training is necessary to minimize overshoot.
Co-Authors Ha, Vo Thanh Van, Tran Thuy