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Torque Ripples Minimization of DTC IPMSM Drive for the EV Propulsion System using a Neural Network
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  • Torque Ripples Minimization of DTC IPMSM Drive for the EV Propulsion System using a Neural Network
  • Torque Ripples Minimization of DTC IPMSM Drive for the EV Propulsion System using a Neural Network
저자명
Singh. Bhim,Jain. Pradeep,Mittal. A.P.,Gupta. J.R.P.
간행물명
Journal of power electronics : JPE
권/호정보
2008년|8권 1호|pp.23-34 (12 pages)
발행정보
전력전자학회
파일정보
정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

This paper deals with a Direct Torque Control (DTC) of an Interior Permanent Magnet Synchronous Motor (IPMSM) for the Electric Vehicle (EV) propulsion system using a Neural Network (NN). The Conventional DTC with optimized switching lookup table and three level torque controller generates relatively large torque ripples in an electric vehicle motor drive. For reducing the torque ripples, a three level torque controller is hereby replaced by the five level torque controller. Furthermore, the switching lookup table of the five level torque controller based DTC is replaced with a Neural Network. These DTC schemes of an IPMSM drive are simulated using MATLAB/SIMULINK. The simulated results are compared with the conventional DTC and it is found that the ripples in the torque, as well as in the stator current, are reduced drastically.