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Implementation of the MTPA and MTPV control with online parameter identification for a high speed IPMSM used as traction drive

Authors: Quoc Khanh Nguyen; Matthias Petrich; Jorg Roth-Stielow;

Implementation of the MTPA and MTPV control with online parameter identification for a high speed IPMSM used as traction drive

Abstract

In this paper, the problem of how to implement the MTPA/MTPV control for an energy efficient operation of a high speed Interior Permanent Magnet Synchronous Motor (IPMSM) used as traction drive is considered. This control method depends on the inductances L d , L q , the flux linkage ΨPM and the stator resistance R s which might vary during operation. The parameter variation causes miscalculation of the set point currents I d and I q for the inner current control system and thus a wrong torque will be set. Consequently the IPMSM will not be operating in the optimal operation point which yields to a reduction of the total energy efficiency and the performance. As a consequence, this paper proposes the implementation of the the Recursive Least Square Estimation (RLS) for a high speed and high performance IPMSM. With this online identification method the variable parameters are estimated and adapted to the MTPA and MTPV control strategy.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
24
Top 10%
Top 10%
Top 10%
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