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  11. An Improved Finite Set Model Predictive Control Of Srm Drive Based On A Voltage Vectors Strategy For Low Torque Ripple

An improved finite set model predictive control of SRM drive based on a voltage vectors strategy for low torque ripple

Deepak Mohanraj1, Devakirubakaran S2, Praveen Kumar Balachandran3,4

  • 1Department of Electrical and Electronics Engineering, KIT-Kalaignarkarunanidhi Institute of Technology, Kannampalayam post, Coimbatore, Tamil Nādu, 641402, India.

Heliyon
|November 7, 2024

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View abstract on PubMed

Summary
This summary is machine-generated.

This study introduces an enhanced Finite Set-Model Predictive Control (FS-MPC) for Switched Reluctance Motors (SRMs) in electric vehicles. The new method significantly reduces torque ripple, improving performance for EV applications.

Area of Science:

  • Electrical Engineering
  • Control Systems
  • Electric Vehicle Technology

Background:

  • Switched Reluctance Motors (SRMs) offer robust structures and fault tolerance, making them suitable for electric vehicles (EVs).
  • Existing Model Predictive Control (MPC) methods for SRMs suffer from high torque ripples due to issues in sector partitioning, Voltage Vector (VV) selection, and weighting factors.
  • Torque ripple is a significant limitation in SRM performance for EV applications.

Purpose of the Study:

  • To propose and validate an enhanced Finite Set-Model Predictive Control (FS-MPC) strategy for Switched Reluctance Motors (SRMs).
  • To significantly reduce torque ripple in SRM drives for improved electric vehicle (EV) performance.
  • To analyze the torque ripple performance of an analytical model of a non-linear SRM machine.

Main Methods:

Keywords:
Cost functionDynamic modellingModel predictive controlSwitched reluctance motor drive

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  • Developed a novel FS-MPC strategy for a non-linear SRM analytical model.
  • Derived proposed Voltage Vectors (VVs) based on rotor position-dependent sector partitioning.
  • Designed a single cost function incorporating a weighting factor for optimal control signal selection to smooth torque.

Main Results:

  • The enhanced FS-MPC achieved a calculated torque ripple of 9%.
  • Simulation studies and experimental validation on a four-phase 8/6 SRM drive confirmed the effectiveness of the proposed method.
  • The method demonstrated superior performance in reducing torque ripple compared to flux ripple reduction.

Conclusions:

  • The proposed FS-MPC is well-suited for reducing torque ripple in SRM drives.
  • The enhanced control strategy offers improved performance for electric vehicle (EV) applications.
  • Experimental results validate the analytical findings and the real-time implementation feasibility.
torque ripple