4.6 Article

Design, Modeling, and Model-Free Control of Permanent Magnet-Assisted Synchronous Reluctance Motor for e-Vehicle Applications

Journal

SUSTAINABILITY
Volume 14, Issue 9, Pages -

Publisher

MDPI
DOI: 10.3390/su14095423

Keywords

electric vehicle; inverter; permanent magnet-assisted synchronous reluctance motor; PMa-SynRM; model-free control; traction drive

Funding

  1. King Mongkut's University of Technology North Bangkok (KMUTNB)

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This paper presents model-free control approaches for permanent magnet-assisted synchronous reluctance motors (PMa-SynRMs) drive. The proposed control technique improves the ability to determine the behavior of the state-variable system during both fixed-point and transient operations. Mathematical models of PMa-SynRM were developed in a linear model form to identify known and unknown parts. The intelligent proportional-integral (iPI) controller was used to correct modeling errors and uncertainties, achieving excellent results compared to traditional PI and model-based controls under transient operating conditions.
This paper describes the model-free control approaches for permanent magnet-assisted (PMa) synchronous reluctance motors (SynRMs) drive. The important improvement of the proposed control technique is the ability to determine the behavior of the state-variable system during both fixed-point and transient operations. The mathematical models of PMa-SynRM were firstly written in a straightforward linear model form to show the known and unknown parts. Before, the proposed controller, named here the intelligent proportional-integral (iPI), was applied as a control law to fix some unavoidable modeling errors and uncertainties of the motor. Lastly, a dSPACE control platform was used to realize the proposed control algorithm. A prototype 1-kW test bench based on a PMa-SynRM machine was designed and realized in the laboratory to test the studied control approach. The simulation using MATLAB/Simulink and experimental results revealed that the proposed control achieved excellent results under transient operating conditions for the motor drive's cascaded control compared to traditional PI and model-based controls.

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