Integrating Fault Detection and Output Regulation in Electric Vehicle Power Converters

Converters are essential for the operation of electric vehicles, acting as vital components that regulate the flow of electrical power and guarantee efficient functionality. Converters in electric cars can be costly and bulky and generate heat, with potential efficiency losses, complexity, reliability concerns, and maintenance requirements impacting performance and design. This work introduces a fault diagnosis technique specifically designed for nonisolated converters. The multi-port converter is proposed for the fault diagnosis approach. The fault diagnosis approach applies to any nonisolated converter, where open circuit fault, short circuit fault, and load variations are analyzed. A Python-based approach is initiated to analyze specific fault conditions during converter operation. The proposed approach is confirmed by performing the simulation in Matlab. The approach utilizes Python for data analysis and fault detection, aiming to improve the reliability of power converters in renewable energy applications. A solar photovoltaic-fed converter serves as a testing platform for this work. The developed methodology is evaluated on a multi-port converter, demonstrating that fault diagnosis and output regulation can be integrated without affecting individual performance. This approach can be adopted by any converter that utilizes a capacitor in the output port.