A Multi functional DC-DC Converter-Based Smart Energy Management System Using Neural Network Approach for Electric Vehicle Applications

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Abstract

This article introduces a new multi functional DC-DC converter-based smart energy management system utilizing Solar PV and Wind sources for Electric Vehicle applications. To promote efficient battery charging, discharging, and enhanced protection from faults, an artificial neural network (ANN) approach is incorporated. The primary feature of the ANN controller is to detect faults in the EV battery for timely intervention. In comparison with existing topologies, the proposed converter can efficiently operate under dynamic conditions and promotes better stability. In addition, the operating principle, modes of operation, design analysis, and control strategy have also been incorporated. The performance of the proposed system is evaluated through MATLAB Simulink software. Furthermore, to validate the system’s performance, a 1kW hardware prototype was built, developed, and tested to verify the effectiveness and feasibility of the system.

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