SENSORLESS DTC OF 8/6 POLE SRM DRIVE FOR ELECTRIC VEHICLE USING ANN IN MATLAB SIMULINK 

This MATLAB Simulink model features sensor less Direct Torque Control (DTC) using an Artificial Neural Network (ANN) controller for precise speed and torque control of an 8/6 pole Switched Reluctance Motor (SRM). 

This advanced simulation model implements an 8/6 pole Switched Reluctance Motor (SRM) drive controlled via Direct Torque Control (DTC) using an ANN-based controller. The system estimates motor speed through mathematical equations, eliminating the need for external sensors, making it suitable for cost-effective and efficient electric vehicle applications. It responds effectively under variable speed and torque conditions and uses Space Vector Modulation (SVM) for switching the converter.

Key Features:

• Sensorless control of 8/6 pole SRM drive for electric vehicle applications

• ANN-based controller integrated into DTC architecture

• Speed estimation using mathematical models (no external sensor required)

• Space Vector Modulation (SVM) used for switching control

• Dynamic testing with variable speed and torque conditions

• Accurate torque and flux control using DTC strategy 

Note

Tested Version: MATLAB/Simulink R2022b. Please ensure you are using this version (or a compatible one) to avoid errors. 

After Payment Delivery:

• Complete MATLAB Simulink model .slx file

• A readme file for step-by-step guide for simulation

• A license file 

Ideal for students, researchers, and engineers working on electric vehicle technologies, control systems, and intelligent motor drives. 

This model demonstrates an advanced, sensorless ANN-based control strategy for SRM motors in EV applications.