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Content Provider | IEEE Xplore Digital Library |
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Author | Kwang-Woon Lee Sang Bin Lee |
Copyright Year | 2010 |
Description | Author affiliation: Korea University, Anam-Dong, Seoul, Korea (Sang Bin Lee) || Mokpo National Maritime University, 571-2 Chukkyo-Dong, Mokpo-City, Korea (Kwang-Woon Lee) |
Abstract | Operation of interior permanent magnet synchronous motors (PMSM) at the maximum torque per ampere (MTPA) operating point requires knowledge of the exact values of machine parameters such as the inductances and back-EMF constant, which depend on saturation and temperature variations. On-line estimation of the machine parameters may not be suitable for practical applications due to the requirement of intensive computation. The objective of this paper is to present a simple MTPA operating point tracking control strategy for vector controlled PMSM drives with slow dynamic loads. The proposed method searches for the MTPA operating point by modulating the current phase angle and observing the variation in the power command. The current angle modulation strategy is designed to sense the influence of load variations in the power command. Therefore, the proposed method can track the MTPA operating point of the PMSM independent of load variations. Experimental results are presented to show the effectiveness of the proposed method. |
Starting Page | 24 |
Ending Page | 28 |
File Size | 140019 |
Page Count | 5 |
File Format | |
ISBN | 9781424449866 |
DOI | 10.1109/SPEEDAM.2010.5544955 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2010-06-14 |
Publisher Place | Italy |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Magnetic flux Permanent Magnet Synchronous Motor Permanent magnet motors Torque control Tracking Control Stators Automatic control Load management Maximum Torque per Ampere (MTPA) Temperature control Optical sensors Motion control Saturation magnetization |
Content Type | Text |
Resource Type | Article |
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