Genetic Algorithm-Based Commutation Angle Control for Torque Ripple Mitigation in Switched Reluctance Motor Drives

Reis, Renata C.; Kimpara, Marcio Magri; Galotto, Jr., Luigi; Pinto, João Pereira

doi:10.1109/access.2023.3313436

Genetic Algorithm-Based Commutation Angle Control for Torque Ripple Mitigation in Switched Reluctance Motor Drives

Journal Article · Fri Sep 08 04:00:00 EDT 2023 · IEEE Access

DOI:https://doi.org/10.1109/access.2023.3313436· OSTI ID:2000273

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Federal University of Mato Grosso do Sul, Campo Grande (Brazil)
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

This work addresses the application of the Genetic Algorithm (GA) technique to optimize the commutation angles of a 2 kW 8/6 switched reluctance machine (SRM). The primary goal is to reduce the well-known drawback of SRMs: the torque ripple. Firstly, the machine was modeled in Matlab /Simulink ® using lookup tables obtained via finite element method (FEM) simulations. Subsequently, the model was used to perform the GA routine aiming to find the optimal phase commutation angles that minimize the torque ripple factor. Notably, the torque performance of the SRM was significantly affected by the commutation angles during the search for the optimal solution. Afterwards, the GA results for four different operation points were verified experimentally through a developed drive platform with digital signal processor-based (DSP) control and an asymmetric bridge converter. As showed by the experiments, the proposed approach was suitable to reduce the torque ripple by more than 50% for one of the evaluated operating points. Furthermore, it was confirmed that the torque ripple mitigation led to acoustic noise improvement.

View Accepted Manuscript (DOE)

Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE; Brazilian National Council for Scientific and Technological Development (CNPq)

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 2000273

Journal Information:: IEEE Access, Journal Name: IEEE Access Journal Issue: 1 Vol. 11; ISSN 2169-3536

Publisher:: IEEECopyright Statement

Country of Publication:: United States

Language:: English

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Related Subjects

42 ENGINEERING
genetic algorithm
mathematical models
optimization
reluctance motors
rotors
switched reluctance motor
torque
torque measurement
torque ripple

Genetic Algorithm-Based Commutation Angle Control for Torque Ripple Mitigation in Switched Reluctance Motor Drives

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