DocumentCode :
162045
Title :
Genetic algorithm based speed controller design of IPMSM drive for EV
Author :
Chottiyanont, Pakorn ; Konghirun, Mongkol ; Lenwari, Wanchak
Author_Institution :
Dept. of Electr. Eng., King Mongkut´s Univ. of Technol. Thonburi, Bangkok, Thailand
fYear :
2014
fDate :
14-17 May 2014
Firstpage :
1
Lastpage :
5
Abstract :
In recent years, the development of the electrical vehicle (EV) in particular the performance enhancement of speed control has been widely attention. To ensure fast dynamic response and stable operation, the design of speed controller is critical and requires considerable effort. This paper proposes an automated design employed genetic algorithm (GA) to optimize PI speed controller of interior permanent magnet synchronous motor (IPMSM) used in the EV. The drive control system is designed on the basis of vector control scheme incorporated with the maximum torque per ampere (MTPA) control strategy to improve the drive performance. The optimization method provides an optimum solution in terms of both speed response and steady-state error. The simulation results verify the effectiveness of the proposed approach.
Keywords :
PI control; angular velocity control; dynamic response; electric vehicles; genetic algorithms; machine vector control; permanent magnet motors; synchronous motor drives; IPMSM drive; MTPA control; PI speed controller; drive control system; dynamic response; electrical vehicle; genetic algorithm; interior permanent magnet synchronous motor drive; maximum torque per ampere control; optimization; speed response; stable operation; steady-state error; vector control; Genetic algorithms; Mathematical model; Optimization; Permanent magnet motors; Sociology; Stators; Torque; Genetic algorithm (GA); IPMSM; MTPA; electric vehicle (EV);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), 2014 11th International Conference on
Conference_Location :
Nakhon Ratchasima
Type :
conf
DOI :
10.1109/ECTICon.2014.6839852
Filename :
6839852
Link To Document :
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