Transport electrification is a trend research topic and one of the biggest nowadays challenges. This paper discusses intelligent hybrid electric vehicle (HEV) control using direct torque control (DTC) based genetic algorithm (GA). An optimized estimator is used to control the electric vehicle (EV) using direct torque control technique. A proposed cost function was used along with DTC-SVM based genetic algorithm to provide a self-tuning for the three used vehicle regulators. By taking into account an international driving cycle and the external environment variables at play, an electric vehicle is put through realistic load circumstances. The EV responds well to the various control strategies that have been applied to it, according to the simulation findings, which are adequate. Also the use of evolutionary techniques has contributed significantly in minimizing torque and speed ripples during the tuning process. The obtained results using GA-DTC control approach have shown their superiority when compared to classical DTC and fuzzy logic based direct torque control as it will be seen throughout this paper.


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    Title :

    Intelligent Control of PMSM-Driven Electric Vehicles Using Fuzzy Logic and Genetic Algorithm


    Contributors:


    Publication date :

    2023-09-01


    Size :

    683064 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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