Efficiency Optimization of Variable Iron Loss Resistance Asynchronous Motor Based on Grey Wolf Optimization Algorithm
Asynchronous motor is widely used in various industrial fields. When asynchronous motor works in case close to the rated load, it will run at maximum efficiency. However, most of the load is 50–100% of rated load and it will lead to the serious waste of energy. This paper proposes an efficiency opti...
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| Published in: | Journal of electrical engineering & technology Vol. 19; no. 1; pp. 485 - 493 |
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Singapore
Springer Nature Singapore
01.01.2024
Springer Nature B.V 대한전기학회 |
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| Abstract | Asynchronous motor is widely used in various industrial fields. When asynchronous motor works in case close to the rated load, it will run at maximum efficiency. However, most of the load is 50–100% of rated load and it will lead to the serious waste of energy. This paper proposes an efficiency optimization control strategy based on the grey wolf optimization algorithm to improve the operating efficiency of asynchronous motors at light loads. The motor loss model considering the change of iron loss is established and it makes the asynchronous motor model more accurate. The grey wolf optimization algorithm is used to find the optimized flux value. When the asynchronous motor operates at the optimal flux, the loss power of the motor is decreased and the operation efficiency improves effectively. The proposed method reduces the flux search time and improves the stability of the system. The simulation model is established and the simulation results are provided to verify the feasibility of the proposed control strategy achieving the global efficiency optimum of asynchronous motor. |
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| AbstractList | Asynchronous motor is widely used in various industrial fields. When asynchronous motor works in case close to the rated load, it will run at maximum efficiency. However, most of the load is 50–100% of rated load and it will lead to the serious waste of energy. This paper proposes an efficiency optimization control strategy based on the grey wolf optimization algorithm to improve the operating efficiency of asynchronous motors at light loads. The motor loss model considering the change of iron loss is established and it makes the asynchronous motor model more accurate. The grey wolf optimization algorithm is used to find the optimized flux value. When the asynchronous motor operates at the optimal flux, the loss power of the motor is decreased and the operation efficiency improves effectively. The proposed method reduces the flux search time and improves the stability of the system. The simulation model is established and the simulation results are provided to verify the feasibility of the proposed control strategy achieving the global efficiency optimum of asynchronous motor. Asynchronous motor is widely used in various industrial fields. When asynchronous motor works in case close to the rated load, it will run at maximum efficiency. However, most of the load is 50–100% of rated load and it will lead to the serious waste of energy. This paper proposes an efficiency optimization control strategy based on the grey wolf optimization algorithm to improve the operating efficiency of asynchronous motors at light loads. The motor loss model considering the change of iron loss is established and it makes the asynchronous motor model more accurate. The grey wolf optimization algorithm is used to find the optimized flux value. When the asynchronous motor operates at the optimal flux, the loss power of the motor is decreased and the operation efficiency improves effectively. The proposed method reduces the flux search time and improves the stability of the system. The simulation model is established and the simulation results are provided to verify the feasibility of the proposed control strategy achieving the global efficiency optimum of asynchronous motor. KCI Citation Count: 0 |
| Author | Chen, Shuang Nai, Ji-qiu Zhao, Yan-cheng Guo, Zhen Tong, Di Ye, Ming-hao |
| Author_xml | – sequence: 1 givenname: Zhen surname: Guo fullname: Guo, Zhen organization: School of Information and Control Engineering, Qingdao University of Technology – sequence: 2 givenname: Di orcidid: 0000-0003-2307-7740 surname: Tong fullname: Tong, Di email: tongdi1996@163.com organization: School of Information and Control Engineering, Qingdao University of Technology – sequence: 3 givenname: Yan-cheng surname: Zhao fullname: Zhao, Yan-cheng organization: School of Information and Control Engineering, Qingdao University of Technology – sequence: 4 givenname: Shuang surname: Chen fullname: Chen, Shuang organization: School of Information and Control Engineering, Qingdao University of Technology – sequence: 5 givenname: Ji-qiu surname: Nai fullname: Nai, Ji-qiu organization: School of Information and Control Engineering, Qingdao University of Technology – sequence: 6 givenname: Ming-hao surname: Ye fullname: Ye, Ming-hao organization: School of Information and Control Engineering, Qingdao University of Technology |
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| Keywords | Loss model Iron loss resistance change Efficiency optimization Asynchronous motor Grey wolf optimizer |
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| Title | Efficiency Optimization of Variable Iron Loss Resistance Asynchronous Motor Based on Grey Wolf Optimization Algorithm |
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