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| Low Switching Frequency Model Predictive Control Strategy Based on Online Parameter Identification Compensation of Linear Induction Motor for Urban Rail Application |
| Xu Wei1, Dong Dinghao1, Ge Jian1, Li Weiye2, Lin Guobin3, Liu Zhicheng4, Yuan Wenye5 |
1. State Key Laboratory of Advanced Electromagnetic Engineering and Technology Huazhong University of Science and Technology Wuhan 430074 China
2. Xiangyang CRRC Motor Technology Co. Ltd Xiangyang 441047 China
3. Maglev Transportation Engineering R&D Center Tongji University Shanghai 201804 China
4. Guangzhou Metro Group Co. Ltd Guangzhou 510330 China
5. Zhuzhou CRRC Times Electric Co. Ltd Zhuzhou 412001 China |
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Abstract To reduce the hardware cost of converter and switching loss, the linear induction motor (LIM) and drive system for urban rail application with strong current and high capacity usually need to operate in a low-switching-frequency mode. However, the conventional low-switching-frequency control method often amplify the influence of discretization error in micro-processor while introducing severe harmonic current and thrust fluctuations, thereby deteriorating the observer performance. Therefore, a multistep finite control set model predictive control (FCS-MPC) strategy with online parameter identification is proposed, which can reduce the current harmonic under low-switching- frequencies and enhance the reliability of system by using high precise parameters. Firstly, the MPC algorithm with switching item in cost function is adopted to realize low switching frequency control at high sampling frequency. Furthermore, the multistep mode is used to suppress the increase of harmonic content caused by the reduction of switching frequency. Then, the influence of the two different low-switching-frequency realization methods on performance is compared. Considering that the magnetizing inductance in LIM for urban rail is deeply affected by the end effect, the parameter sensitivity of the MPC method is further analyzed and the parameter identification is introduced, which realizes the accurate estimation of magnetizing inductance at low-switching-frequency, improves the precision of prediction accuracy and parameter robustness of MPC, and reduces the harmonic content in the drive system. Simulation and experimental results show that the proposed method can well realize accurate tracking of the magnetizing inductance in LIM at low-switching frequency, and effectively suppress the current harmonic of the drive system combined with the multistep FCS-MPC algorithm.
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Received: 10 November 2021
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2022, Vol. 37 
