Heat dissipation analysis and multi-objective optimization of a permanent magnet synchronous motor using surrogate assisted method
Permanent magnet synchronous motors (PMSM) have been substantially used in electric vehicles (EVs) due to their advantages such as low loss, large torque, and high power density. With the continuous improvement of the PMSM performance requirements, its heat dissipation has also attracted increasing...
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| Veröffentlicht in: | Case studies in thermal engineering Jg. 27; S. 101203 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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Elsevier Ltd
01.10.2021
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| ISSN: | 2214-157X, 2214-157X |
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| Abstract | Permanent magnet synchronous motors (PMSM) have been substantially used in electric vehicles (EVs) due to their advantages such as low loss, large torque, and high power density. With the continuous improvement of the PMSM performance requirements, its heat dissipation has also attracted increasing attention. This paper proposes a cooling system to realize the heat dissipation of the motor through internal oil circulation and external water circulation. Meanwhile, to obtain the best cooling system parameters, an optimization framework is developed for heat dissipation optimization of the motor. First, the most suitable Latin hypercube sampling (LHS) method is selected for sampling through the Coordinates exchange algorithm. Second, we separately study the modeling accuracy of thirteen surrogate models and finally select the back propagation (BP) neural network model. Then, we use six multi-objective optimization algorithms (MOOAs) to optimize the model, and select the optimal solution via the utopian point method. Finally, the motor heat dissipation situation is effectively improved, and the effectiveness and reliability of the optimization framework are proved, which provides an alternative mean for the heat dissipation design optimization of the motor and has prominent practical significance.
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| AbstractList | Permanent magnet synchronous motors (PMSM) have been substantially used in electric vehicles (EVs) due to their advantages such as low loss, large torque, and high power density. With the continuous improvement of the PMSM performance requirements, its heat dissipation has also attracted increasing attention. This paper proposes a cooling system to realize the heat dissipation of the motor through internal oil circulation and external water circulation. Meanwhile, to obtain the best cooling system parameters, an optimization framework is developed for heat dissipation optimization of the motor. First, the most suitable Latin hypercube sampling (LHS) method is selected for sampling through the Coordinates exchange algorithm. Second, we separately study the modeling accuracy of thirteen surrogate models and finally select the back propagation (BP) neural network model. Then, we use six multi-objective optimization algorithms (MOOAs) to optimize the model, and select the optimal solution via the utopian point method. Finally, the motor heat dissipation situation is effectively improved, and the effectiveness and reliability of the optimization framework are proved, which provides an alternative mean for the heat dissipation design optimization of the motor and has prominent practical significance. Permanent magnet synchronous motors (PMSM) have been substantially used in electric vehicles (EVs) due to their advantages such as low loss, large torque, and high power density. With the continuous improvement of the PMSM performance requirements, its heat dissipation has also attracted increasing attention. This paper proposes a cooling system to realize the heat dissipation of the motor through internal oil circulation and external water circulation. Meanwhile, to obtain the best cooling system parameters, an optimization framework is developed for heat dissipation optimization of the motor. First, the most suitable Latin hypercube sampling (LHS) method is selected for sampling through the Coordinates exchange algorithm. Second, we separately study the modeling accuracy of thirteen surrogate models and finally select the back propagation (BP) neural network model. Then, we use six multi-objective optimization algorithms (MOOAs) to optimize the model, and select the optimal solution via the utopian point method. Finally, the motor heat dissipation situation is effectively improved, and the effectiveness and reliability of the optimization framework are proved, which provides an alternative mean for the heat dissipation design optimization of the motor and has prominent practical significance. [Display omitted] |
| ArticleNumber | 101203 |
| Author | Gao, Liang Li, Wei Garg, Akhil Li, Yongsheng Li, Congbo |
| Author_xml | – sequence: 1 givenname: Yongsheng surname: Li fullname: Li, Yongsheng organization: College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, 400044, China – sequence: 2 givenname: Congbo surname: Li fullname: Li, Congbo organization: College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, 400044, China – sequence: 3 givenname: Akhil surname: Garg fullname: Garg, Akhil organization: State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, 430074, China – sequence: 4 givenname: Liang orcidid: 0000-0002-1485-0722 surname: Gao fullname: Gao, Liang organization: State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, 430074, China – sequence: 5 givenname: Wei orcidid: 0000-0002-7772-5697 surname: Li fullname: Li, Wei email: welly@cqu.edu.cn organization: College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, 400044, China |
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| Keywords | Permanent magnet synchronous motors Surrogate model Optimization framework Multi-objective optimization algorithms Electric vehicles Water oil mixed cooling system Utopian point method |
| Language | English |
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| SubjectTerms | Electric vehicles Multi-objective optimization algorithms Optimization framework Permanent magnet synchronous motors Surrogate model Utopian point method Water oil mixed cooling system |
| Title | Heat dissipation analysis and multi-objective optimization of a permanent magnet synchronous motor using surrogate assisted method |
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