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Model Predictive Current Control of Double-Side Linear Vernier Permanent Magnet Machines Considering End Effect |
Chen Xiao1,2, Zhao Wenxiang1,2, Ji Jinghua1,2, Tao Tao1,2, Xue Rui1,2 |
1.School of Electrical and Information Engineering Jiangsu University Zhenjiang 212013 China; 2.Jiangsu Key Laboratory of Drive and Intelligent Control for Electric Vehicle Zhenjiang 212013 China |
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Abstract In this paper, a two-vectors model predictive current control of double-side linear vernier permanent magnet machines is presented, in which the end effect is considered. Finite control set model predictive control has many advantages in the field of motor drive, but the vector selection range of the traditional implementation is relatively small. Two-vectors model predictive control simultaneously operates two arbitrary voltage vectors in single control cycle that enlarges the selection range of voltage vectors and improves the current control performance. Due to the end effect of the linear machines and the differences of mutual inductance between the windings, the equivalent dq axis inductance fluctuates with the change of position, and the parameter mismatch will cause the deterioration of the model predictive control performance. In order to solve this problem, the forgetting factor recursive least square method is used to identify the equivalent dq axis inductance online and compensates the end effect, so as to further improve the performance of the two-vectors model predictive current control. Based on the dSPACE rapid control prototype system, the effectiveness of the proposed algorithm is verified by experiments.
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Received: 29 June 2018
Published: 10 January 2019
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