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Energy-Saving Control of Induction Motor for Electric Vehicle Based on Online Parameter Estimation
Alternative Title20200908225535
Shengwen, Fan1,2; Shuya, Dai1,2; Ruizhi, Li3; Xinsen, Zhang1,2
Source PublicationJournal of Physics: Conference Series
2020
Volume1449
Issue1
Pages012130
DOI10.1088/1742-6596/1449/1/012130
Language英语
ISSN17426588
AbstractIn order to improve the problem of insufficient endurance mileages of pure electric vehicles, an energy-saving control strategy of induction motor based on the online parameter estimation is proposed. Considering the model of considering the iron loss of the stator of the induction motor, the loss minimization model is used to control the energy of the motor to reduce the steady-state loss of the motor. At the same time, an observer with the model reference adaptive system (MRAS) is designed to online estimated the rotor time constant and stator resistance of the motor, and reduce the influence of parameter variation on the loss minimization control, which makes the loss model more accurate and the energy-saving effect is more ideal. Finally, the control strategy is verified by simulation. The simulation results show that the energy-saving effect of this algorithm is obvious when the motor runs at a high speed under a light load. © Published under licence by IOP Publishing Ltd.
KeywordControl strategies Energy-saving control Energy-saving effect Model reference adaptive system On-line parameter estimations Pure electric vehicles Rotor time constant Stator resistance
Conference Name2019 2nd International Symposium on Power Electronics and Control Engineering, ISPECE 2019
Conference DateNovember 22, 2019 - November 24, 2019
Conference PlaceTianjin, China
Indexed ByEI
Citation statistics
Document Type会议论文
Identifierhttp://ir.nssc.ac.cn/handle/122/7746
Collection中国科学院国家空间科学中心
Affiliation1.School of Electrical and Control Engineering, North China University of Technology, Beijing; 100144, China;
2.Collaborative Innovation Center of Key Power Energy-Saving Technologies, Beijing; 100144, China;
3.National Space Science Center, CAS, Beijing; 100190, China
Recommended Citation
GB/T 7714
Shengwen, Fan,Shuya, Dai,Ruizhi, Li,et al. Energy-Saving Control of Induction Motor for Electric Vehicle Based on Online Parameter Estimation[C],2020:012130.
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