An Adaptive Dead-time Compensation Strategy for a Permanent Magnet Synchronous Motor Drive Using Neural Network

Naomitsu Urasaki; Tomonobu Senjyu; Toshihisa Funabashi; Hideomi Sekine

An Adaptive Dead-time Compensation Strategy for a Permanent Magnet Synchronous Motor Drive Using Neural Network

Vol. 6, No. 4, pp. 279-289, Oct. 2006

10.6113/JPE.2006.6.4.279

Dead time

Voltage source inverter

Permanent magnet synchronous motor

Neural Network

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Abstract

This paper presents a neural network based adaptive dead-time compensation strategy for an inverter fed permanent magnet synchronous motor drive. The neural network is used for identifying the dead-time compensation time (DTCT) that includes an equivalent dead-time, turn-on/off time and on-state voltage components of the voltage source inverter. In order to train the neural network, desired DTCTs for eight operating points are prepared as training data. The trained neural network can identify a desired DTCT for any operating point because it has the capability of the interpolation. The accuracy of the identified DTCT is experimentally confirmed by comparing the calculated active power with a measured one

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Cite this article

[IEEE Style]

N. Urasaki, T. Senjyu, T. Funabashi, H. Sekine, "An Adaptive Dead-time Compensation Strategy for a Permanent Magnet Synchronous Motor Drive Using Neural Network," Journal of Power Electronics, vol. 6, no. 4, pp. 279-289, 2006. DOI: 10.6113/JPE.2006.6.4.279.

[ACM Style]

Naomitsu Urasaki, Tomonobu Senjyu, Toshihisa Funabashi, and Hideomi Sekine. 2006. An Adaptive Dead-time Compensation Strategy for a Permanent Magnet Synchronous Motor Drive Using Neural Network. Journal of Power Electronics, 6, 4, (2006), 279-289. DOI: 10.6113/JPE.2006.6.4.279.