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Fault Detection Technique Based On Clustering Approach of Artificial Intelligence in Electric Vehicle Converters

机译:基于人工智能聚类的电动汽车变频器故障检测技术

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An on-board health monitoring system to diagnose the vehicle while it is in operation; is a necessity to propose electric vehicles (EVs) as a robust replacement of the internal combustion engine (ICE) ones. This paper proposes an efficient, simple and reliable fault detection technique of an open circuit fault in voltage source inverters (VSI), as a case study. It is based on semi-clustering approach, which compares a gate-driving signal (as a reference) to the actual VSI output voltage, trained in many different scenarios. Simulink simulation model and a laboratory prototype are built to prove the validity of the proposed technique. Results are presented and discussed to confirm coherence of proposed methodologies.
机译:车载健康监测系统,可在车辆运行时对其进行诊断;提出电动汽车(EV)作为内燃机(ICE)的强大替代品的必要性。本文提出了一种有效,简单,可靠的电压源逆变器(VSI)开路故障检测技术,以案例研究为例。它基于半群集方法,该方法将栅极驱动信号(作为参考)与实际VSI输出电压进行比较,并在许多不同的情况下对其进行了训练。建立Simulink仿真模型和实验室原型以证明所提出技术的有效性。提出并讨论了结果,以确认所提出方法的连贯性。

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