SRM 6/12 M-45 Motors Modeling with Bidirectional Gated Recurrent Unit Prediction System for Enhanced Torque and Speed in Electric Vehicles

Switched Reluctance Motor (SRM) is a type of reluctance motor where power is supplied to the stator windings rather than the rotor, removing the requirement for a commutator and streamlining the mechanical construction. Due to the doubly salient construction of SRMs, the rotor and stator both have prominent poles. SRMs include a bulky construction due to their doubly salient design and limited slot fill factor, which can reduce overall efficiency. Additionally, the rotor’s complex design may lead to manufacturing challenges and increased mechanical wear over time. To overcome these impacts, a newly developed SRM 6/12 M-45 design is presented in this research with the integration of AI to predict motor performance at any period. Initially 3[Formula: see text]SRM 6/12 M-45 model was developed, in which the rotor and stator are made from Cold Rolled Non-Oriented (CRNO) silicon steel, which provides high permeability and low core loss. The designed conical shape motor model undergoes Finite Element Method (FEM) analysis to evaluate parameters such as flux linkage, heat, power, efficiency, and torque ripple. A real-time dataset was generated from the FEM analysis, utilizing varied power levels, which was subsequently used to train the Bidirectional Gated Recurrent Unit (BiGRU) prediction model. The BiGRU analyzes the input data of flux linkage, power rating, heat, and frequency to predict the output of energy utilization ratio, torque, and speed. As a result, the SRM motor demonstrates a power loss of 2.05[Formula: see text]W and a torque output of 33.069[Formula: see text]Nm. Additionally, the energy density value is 2830e[Formula: see text]004, the operating temperature is 1.0000e−009, and the surface charge density value is 1.7527e[Formula: see text]013 with the accuracy of 96% and precision of 96.84%. This integration of advanced materials, design techniques, and predictive modeling optimizes the SRM’s efficiency and reliability in Electric Vehicle (EV) applications.