Torque Ripples Minimization of DTC IPMSM Drive for the EV Propulsion System using a Neural Network

Bhim Singh; Pradeep Jain; A.P.Mittal; J.R.P.Gupta

Torque Ripples Minimization of DTC IPMSM Drive for the EV Propulsion System using a Neural Network

Vol. 8, No. 1, pp. 23-34, Jan. 2008

10.6113/JPE.2008.8.1.23

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Abstract

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.

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Cite this article

[IEEE Style]

B. Singh, P. Jain, A.P.Mittal, J.R.P.Gupta, "Torque Ripples Minimization of DTC IPMSM Drive for the EV Propulsion System using a Neural Network," Journal of Power Electronics, vol. 8, no. 1, pp. 23-34, 2008. DOI: 10.6113/JPE.2008.8.1.23.

[ACM Style]

Bhim Singh, Pradeep Jain, A.P.Mittal, and J.R.P.Gupta. 2008. Torque Ripples Minimization of DTC IPMSM Drive for the EV Propulsion System using a Neural Network. Journal of Power Electronics, 8, 1, (2008), 23-34. DOI: 10.6113/JPE.2008.8.1.23.