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An improved ANFIS model predictive current control approach for minimizing torque and current ripples in PMSM-driven electric vehicle

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Abstract

Electric Vehicles (EVs) are anticipated to dominate passenger car transportation, playing a pivotal role in advancing sustainable mobility. However, with the increasing enthusiasm for EVs, impediments endure within the realm of power transmission. This is especially evident in addressing challenges related to minimizing torque ripple and implementing advanced control techniques in traction for high-performance and efficient operation of EVs. Numerous control algorithms for motor drives have been developed in the recent past but face challenges in attaining effective control under varying drive cycles of EVs. To tackle these challenges, motor drive control algorithms integrate various control techniques, including field orientation control, model predictive control, intelligent control, etc. This paper proposes an innovative online-tuned MPCC algorithm based on the adaptive neuro-fuzzy inference system (ANFIS). The traditional proportional–integral (PI) controller is replaced with an adapted ANFIS algorithm, and the tuning of ANFIS parameters is achieved by leveraging the error between the reference and adjustable models through a hybrid training algorithm. The proposed novel control technique improves the dynamic speed response of permanent magnet synchronous motor drives EVs. This improvement is realized by replacing the PI-HCC controller with an ANFIS controller coupled with MPCC. A laboratory prototype of the proposed control technique for EVs has been developed, and a comparative analysis of ANFIS-MPCC techniques with other known control techniques has been presented. This paper also demonstrates the importance of choosing optimal motor control techniques for torque ripple minimization and improving the overall performance of EVs.

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Authors and Affiliations

  1. Department of Electrical Engineering, Centre of Excellence for EVRT, Delhi Technological University, Delhi, 110042, India

    Brijendra Sangar, Madhusudan Singh & Mini Sreejeth

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  1. Brijendra Sangar
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  2. Madhusudan Singh
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  3. Mini Sreejeth
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Sangar, B., Singh, M. & Sreejeth, M. An improved ANFIS model predictive current control approach for minimizing torque and current ripples in PMSM-driven electric vehicle. Electr Eng (2024). https://doi.org/10.1007/s00202-024-02346-3

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