Direct Torque Control of SRM Drive for Electric Vehicle by Using ANN-LSTM Controllers

Electric vehicle technologies are tremendously increasing day by day due to their advantageous and flexibility. Numerous control strategies of electric drive are using in electric vehicle and among them Switched Reluctance Motor (SRM) based novel electric drives are developing recently. At the same time, flexible and precious controllers must be used in the electric drive to obtain smooth operation of the vehicle. Among may, Artificial Neural Network (ANN) based Long Short Term Memory (LSTM) controllers are producing accurate outputs under many operating and critical conditions as compared with ordinary controllers such as PI, Fuzzy etc. A Direct Torque Control (DTC) is implemented by using ANN-LSTM controllers in this paper for electric vehicle. The electric vehicle which utilizes a 6/4 SRM fed by four batteries is considered in this paper to implement an efficient control mechanism. A novel converter topology is suggested to efficiently drive the SRM for electric vehicle applications. Ripples on the torque of the SRM will be reduced by proposed method and enhanced the significance of ANN-LSTM controllers. The proposed converter configuration allows for the use of four battery systems, reducing the charging time of the batteries as compared with conventional structure. Detailed control algorithms and models are implemented using the MATLAB/Simulink platform. Comprehensive results are presented along with a thorough explanation of the proposed system.