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Data-Driven Induction Motor Parameters Offline Identification Method Based on Actor-Critic Framework |
Qi Xing, Zhang Qian |
School of Electrical Engineering and Automation Anhui University Hefei 230601 China |
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Abstract The parameter identification of electric vehicle motor is a key method to improve the motor’s performance, making the motor output larger torque and higher efficiency as much as possible at any speed. However, as traditional identification methods are usually model-based, it suffered from model error, poor anti-noise capability, and failure to achieve optimal torque characteristics within the range of full speed. This paper proposed an offline data-based method to identify the rotor resistance and excitation inductance, which is able to obtain torque-optimized parameters given a specific motor speed and a specific motor current. To achieve the maximum torque at the given speed and the given current, a framework of Actor-Critic was designed, and observations, rewards and actions were specified. Experimental results have shown that the proposed method can obtain more accurate and more robust identification; meanwhile it can ensure the motor have an optimized torque output at any speed.
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Received: 05 March 2018
Published: 14 May 2019
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