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https://doi.org/10.4271/2021-0...
Conference object . 2021 . Peer-reviewed
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Evaluation of Model Predictive Control for IPMSM Using High-Fidelity Electro-Thermal Model of Inverter for Electric Vehicle Applications

Authors: Zhaksylyk, Assel; Rauf, Abdul-Mannan; Chakraborty, Sajib; El Baghdadi, Mohamed; Geury, Thomas; Ciglaric, Stanko; Hegazy, Omar;

Evaluation of Model Predictive Control for IPMSM Using High-Fidelity Electro-Thermal Model of Inverter for Electric Vehicle Applications

Abstract

This paper presents a high-fidelity electro-thermal model of a half-bridge that consists of IGBTs and anti-parallel diodes. The model calculates and estimates the half-bridge voltages, currents, switching and conduction losses considering the operating temperature and current conditions. Moreover, this model is suitable for varying switching frequency operation. The electro-thermal model can be used as an evaluation tool to analyze the performance of control strategies for traction inverter from efficiency, temperature and component stress point of view. In this paper performance of Direct Torque Model Predictive Control (DTMPC) of an Interior Permanent Magnet Synchronous Motor (IPMSM) is evaluated in comparison with Indirect Field Oriented Control (IFOC) with sinusoidal pulse width modulation (PWM). The inverter model and the MPC are both implemented in C-Mex for rapid execution. The MPC algorithm implemented in this research tracks torque reference while using Maximum-Torque-Per-Ampere (MTPA) strategy and minimizing switching losses. Both control systems are able to follow the speed reference. The MPC shows a decrease in losses compared to IFOC when tested with low-speed and high-speed parts of the WLTC profile.

Country
Belgium
Related Organizations
Keywords

switches, Mathematical models, traction, Electric Vehicles, control systems

  • BIP!
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    citations
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    4
    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.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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citations
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!
4
Top 10%
Top 10%
Average
Green