Artificial Neural Network based Power Control in High-Speed SRM Systems with Single-Phase H- Bridge Rectifier

Artificial Neural Network based  Power Control in High-Speed SRM Systems with Single-Phase H- Bridge Rectifier

Jogeswar Karakamitla,  Inala Venkata Lokesh, Dakkumalla Akhil, Katari Devendra

Department of Electrical and Electronics Engineering, Seshadri Rao Gudlavalleru Engineering College,

Krishna district, Andhra Pradesh

Abstract— This paper presents the design and implementation of an intelligent high-speed Switched Reluctance Motor (SRM) drive using a single-phase H-Bridge rectifier and Artificial Neural Network (ANN) based controller. The ANN is trained to regulate both input power and motor excitation in real-time, improving speed stability and reducing torque ripple. The system employs a DC-link capacitor to smooth the rectified output and feeds the SRM through an asymmetric converter. Experimental results confirm enhanced dynamic response, minimal total harmonic distortion (THD), and energy-efficient performance even under varying load conditions. The system is well-suited for low-cost, high-speed electric drive applications.

Keywords—Switched Reluctance Motor, H-Bridge Rectifier, Artificial Neural Network, Speed Control, THD, DC-Link, ANN Controller