Multi-objective structure optimization for interior permanent magnet synchronous motors under complex operating conditions
In order to improve the dynamic performance of permanent magnet synchronous motors (PMSMs) under complex operating conditions and reduce energy consumption, this paper establishes a finite element model of the PMSM and proposes a method of representing the operating characteristics of the PMSM on th...
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| Veröffentlicht in: | Structural and multidisciplinary optimization 2024-07, Vol.67 (7), p.120, Article 120 |
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| creator | Sun, Zhicheng Hu, Jianjun Xin, Yuntong Guo, Qi Yao, Zutang |
| description | In order to improve the dynamic performance of permanent magnet synchronous motors (PMSMs) under complex operating conditions and reduce energy consumption, this paper establishes a finite element model of the PMSM and proposes a method of representing the operating characteristics of the PMSM on the speed-torque plane using equivalent points. Based on the equivalent points, a multi-objective optimization method for the structure of PMSMs under complex operating conditions is proposed. Firstly, the method establishes an approximate model of the finite element model to study the influence of the permanent magnet structure and position on the dynamic performance of the PMSM. Subsequently, an improved particle swarm optimization algorithm is utilized to obtain the Pareto front solutions for the optimization objectives. Finally, a fuzzy membership degree algorithm is employed to extract the optimal compromise solution. The results show that the proposed optimization method can reduce the PMSM’s torque ripple, improve the average torque, decrease the energy consumption, and improve vehicle comfort. |
| doi_str_mv | 10.1007/s00158-024-03823-w |
| format | Article |
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Based on the equivalent points, a multi-objective optimization method for the structure of PMSMs under complex operating conditions is proposed. Firstly, the method establishes an approximate model of the finite element model to study the influence of the permanent magnet structure and position on the dynamic performance of the PMSM. Subsequently, an improved particle swarm optimization algorithm is utilized to obtain the Pareto front solutions for the optimization objectives. Finally, a fuzzy membership degree algorithm is employed to extract the optimal compromise solution. The results show that the proposed optimization method can reduce the PMSM’s torque ripple, improve the average torque, decrease the energy consumption, and improve vehicle comfort.</description><identifier>ISSN: 1615-147X</identifier><identifier>EISSN: 1615-1488</identifier><identifier>DOI: 10.1007/s00158-024-03823-w</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Algorithms ; Computational Mathematics and Numerical Analysis ; Energy consumption ; Engineering ; Engineering Design ; Equivalence ; Finite element method ; Multiple objective analysis ; Optimization ; Pareto optimization ; Particle swarm optimization ; Permanent magnets ; Synchronous motors ; Theoretical and Applied Mechanics ; Torque</subject><ispartof>Structural and multidisciplinary optimization, 2024-07, Vol.67 (7), p.120, Article 120</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. 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Based on the equivalent points, a multi-objective optimization method for the structure of PMSMs under complex operating conditions is proposed. Firstly, the method establishes an approximate model of the finite element model to study the influence of the permanent magnet structure and position on the dynamic performance of the PMSM. Subsequently, an improved particle swarm optimization algorithm is utilized to obtain the Pareto front solutions for the optimization objectives. Finally, a fuzzy membership degree algorithm is employed to extract the optimal compromise solution. 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Based on the equivalent points, a multi-objective optimization method for the structure of PMSMs under complex operating conditions is proposed. Firstly, the method establishes an approximate model of the finite element model to study the influence of the permanent magnet structure and position on the dynamic performance of the PMSM. Subsequently, an improved particle swarm optimization algorithm is utilized to obtain the Pareto front solutions for the optimization objectives. Finally, a fuzzy membership degree algorithm is employed to extract the optimal compromise solution. The results show that the proposed optimization method can reduce the PMSM’s torque ripple, improve the average torque, decrease the energy consumption, and improve vehicle comfort.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s00158-024-03823-w</doi></addata></record> |
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| subjects | Algorithms Computational Mathematics and Numerical Analysis Energy consumption Engineering Engineering Design Equivalence Finite element method Multiple objective analysis Optimization Pareto optimization Particle swarm optimization Permanent magnets Synchronous motors Theoretical and Applied Mechanics Torque |
| title | Multi-objective structure optimization for interior permanent magnet synchronous motors under complex operating conditions |
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