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Research Article

Investigation on ANFIS-GA controller for speed control of a BLDC fed hybrid source electric vehicle

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  • @ARTICLE{10.4108/ew.4965,
        author={P. Jagadish Babu and A. Geetha},
        title={Investigation on ANFIS-GA controller for speed control of a BLDC fed hybrid source electric vehicle},
        journal={EAI Endorsed Transactions on Energy Web},
        volume={11},
        number={1},
        publisher={EAI},
        journal_a={EW},
        year={2024},
        month={1},
        keywords={PV, Battery Pack, ANFIS, GA, H6, VSI, BLDC Motor},
        doi={10.4108/ew.4965}
    }
    
  • P. Jagadish Babu
    A. Geetha
    Year: 2024
    Investigation on ANFIS-GA controller for speed control of a BLDC fed hybrid source electric vehicle
    EW
    EAI
    DOI: 10.4108/ew.4965
P. Jagadish Babu1, A. Geetha1,*
  • 1: SRM Institute of Science and Technology
*Contact email: geethaa2@srmist.edu.in

Abstract

The BLDC (Brushless DC Motor) is utilized in electric vehicles, space missions, and mechanical applications. Neural Network Inference System reduces torque ripple for hybrid electric vehicle (PV-Battery) along with BLDC drive to achieve efficient speed performance and stability. A hybrid input source methodology is thus put forwarded to drive the stator currents giving exactly the expressed electromagnetic torque and counter-EMF harmonics. The torque and speed control technique are directed to neural network interference system, and H6 Voltage Source Inverter (H6 VSI) drives BLDC with a gate pulse signal. We examine how an ANFIS-GA torque controller may eliminate BLDC torque ripples under uninterrupted hybrid power supply in this work. MATLAB (Simulink) results show that Genetic Algorithm (GA) improves training of ANFIS better with varying set speed conditions. The ANFIS-GA controller outperforms challenging controllers under various BLDC motor driving load conditions, proving its efficiency.

Keywords
PV, Battery Pack, ANFIS, GA, H6, VSI, BLDC Motor
Received
2023-11-02
Accepted
2024-01-21
Published
2024-01-29
Publisher
EAI
http://dx.doi.org/10.4108/ew.4965

Copyright © 2024 J. Jagadish Babu et al., licensed to EAI. This is an open access article distributed under the terms of the CC BYNC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.

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