PLC Technology Under the New Energy Vehicle Motor Drive System Fault Detection Research

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Yi Zhang, Chunli Liao, Yi Zhang, Minglai Liu, Zhanjiao She


With the burgeoning adoption of electric vehicles (EVs) and the imperative for robust fault detection systems within their motor drive systems, this research delves into the application of Programmable Logic Controller (PLC) technology for fault detection. The advent of new energy vehicles necessitates advanced monitoring and diagnostic systems to ensure operational safety, efficiency, and longevity of the vehicle's motor drive components. PLC technology offers a versatile platform capable of real-time monitoring, data analysis, and adaptive control, making it an attractive candidate for fault detection in EV motor drive systems. This study systematically investigates the integration of PLC technology into the fault detection framework for new energy vehicle motor drives. Through a comprehensive literature review, existing methodologies and techniques for fault detection in motor drive systems are analyzed, highlighting their limitations and areas for improvement. Subsequently, the research proposes a novel approach leveraging PLCs for fault detection, incorporating features such as sensor data acquisition, signal processing, and algorithm implementation. Experimental validation of the proposed PLC-based fault detection system is conducted using a prototype EV motor drive setup. Performance metrics including detection accuracy, response time, and reliability are assessed under various fault scenarios, demonstrating the efficacy and robustness of the developed system. Furthermore, the scalability and adaptability of the PLC-based approach are evaluated to ascertain its potential for integration into commercial EV platforms.

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