A Novel Nonlinear Modeling Method for Permanent-Magnet Synchronous Motors

Luo, Guangzhao; Zhang, Rong; Chen, Zhe; Tu, Wencong; Zhang, Sha; Kennel, Ralph

doi:10.1109/tie.2016.2578839

Cited by 63 publications

(30 citation statements)

References 20 publications

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“…It should be noted that the cross-coupling effect has been neglected in the proposed torque ripple model. In fact, the cross-coupling effect will induce an additional torque as written in (33) [30], [31].…”

Section: Discussionmentioning

confidence: 99%

Torque Ripple Modeling and Minimization for Interior PMSM Considering Magnetic Saturation

Lai

Guo

Mukherjee

et al. 2018

IEEE Trans. Power Electron.

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Torque ripple modelling and minimization for interior permanent magnet synchronous machines (IPMSMs) requires accurate information of the inductances which vary nonlinearly due to magnetic saturation. However, existing approaches fail to consider the magnetic saturation and thus their performance is limited under different load conditions. Therefore, this paper improves the torque ripple model by considering magnetic saturation, and employs this model for optimal current design to improve the performance of torque ripple minimization for IPMSMs under different load conditions. At first, numerical studies are performed to analyze and understand how magnetic saturation affects the torque ripples in IPMSMs. Then, a novel torque ripple model for IPMSMs is developed, in which the inductance term is replaced by exploring the machine electrical model. This improved torque ripple model is computation-efficient and it can provide fast and accurate torque ripple prediction. Based on this model, a genetic algorithm (GA) based optimal stator current design approach is proposed to minimize the torque ripple in IPMSMs. The proposed GA-based approach can adaptively optimize the stator current under different load conditions, which can guarantee the robust performance of torque ripple minimization under different saturation levels. The proposed approach is validated through experimental test on a laboratory IPMSM drive system. Index Terms--Geneticalgorithm, magnetic saturation, optimal stator current design, torque ripple modeling and minimization I. NOMENCLATURE t total Total torque T 0 Average torque t h Harmonic torque t cog Cogging torque t ecc Torque induced by cross-coupling effect L d , L q dq-axis inductances L dq , L qd dq-axis mutual inductances . Her research areas include modelling, control and testing of permanent magnet machines and switched reluctance machines. Guodong Feng (M'15) received the B.S. and Ph.D degrees in Engineering

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Section: Discussionmentioning

confidence: 99%

Torque Ripple Modeling and Minimization for Interior PMSM Considering Magnetic Saturation

Lai

Guo

Mukherjee

et al. 2018

IEEE Trans. Power Electron.

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“…In Ref. [19], the authors investigate a novel modeling method to realize a high-accuracy motor model by using the virtual damping winding. The proposed method provides the additional voltage and torque equation to consider the nonlinear characteristics.…”

Section: Novel Control Methodsmentioning

confidence: 99%

“…These achievements have been highlighted by many researchers who have proposed novel approaches to improve motor performance. Three groups of topics will be introduced in this paper: optimal design methods [1][2][3][4][5][6][7][8][9], novel motor structures [10][11][12][13][14][15][16], and novel control methods [17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

A research trend of electric machines with development of finite element analysis

Hijikata

Akatsu

2017

IEEJ Transactions Elec Engng

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Finite element analysis (FEA) has rapidly developed in the past three decades. In case of the magnetic field analysis, many researchers have proposed different electric machines by using FEA in order to achieve high efficiency, high torque density, low torque ripple, and so on. For further development of electric machines, this paper presents a literature survey on the state‐of‐the‐art research trends of the electric machine related to FEA in the last 3 years. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

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“…After decades of development, HILS has been deeply favored by scientific research units and manufacturers all over the world. In China, many manufacturers (CRRC, China's State Grid, China First Automobile) and higher teaching institutions (Shanghai Jiaotong University, National University of Defense Technology, Harbin Institute of Technology) have carried out scientific research in related fields based on HILS, and have achieved fruitful research results [41][42][43][44]. ATO has both optimization and control functions: the main processor unit (MPU) uses an optimization algorithm to optimize the train's ideal target speed distance curve based on constraints such as line condition and optimization objectives such as expected running time.…”

Section: The Relevant Data and Simulation Platform Of The Practical Ementioning

confidence: 99%

Multi-Objective Hybrid Optimization Algorithm Using a Comprehensive Learning Strategy for Automatic Train Operation

Wang

Liu

et al. 2019

Energies

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Aiming at the problem of easy-to-fall-into local convergence for automatic train operation (ATO) velocity ideal trajectory profile optimization algorithms, an improved multi-objective hybrid optimization algorithm using a comprehensive learning strategy (ICLHOA) is proposed. Firstly, an improved particle swarm optimization algorithm which adopts multiple particle optimization models is proposed, to avoid the destruction of population diversity caused by single optimization model. Secondly, to avoid the problem of random and blind searching in iterative computation process, the chaotic mapping and the reverse learning mechanism are introduced into the improved whale optimization algorithm. Thirdly, the improved archive mechanism is used to store the non-dominated solutions in the optimization process, and fusion distance is used to maintain the diversity of elite set. Fourthly, a dual-population evolutionary mechanism using archive as an information communication medium is designed to enhance the global convergence improvement of hybrid optimization algorithms. Finally, the optimization results on the benchmark functions show that the ICLHOA can significantly outperform other algorithms for contrast. Furthermore, the ATO Matlab/simulation and hardware-in-the-loop simulation (HILS) results show that the ICLHOA has a better optimization effect than that of the traditional optimization algorithms and improved algorithms.

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A Novel Nonlinear Modeling Method for Permanent-Magnet Synchronous Motors

Cited by 63 publications

References 20 publications

Torque Ripple Modeling and Minimization for Interior PMSM Considering Magnetic Saturation

Torque Ripple Modeling and Minimization for Interior PMSM Considering Magnetic Saturation

A research trend of electric machines with development of finite element analysis

Multi-Objective Hybrid Optimization Algorithm Using a Comprehensive Learning Strategy for Automatic Train Operation

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