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T-S Fuzzy Model-based Fault Diagnosis of PEM Fuel Cell Engine

机译:基于T-S模糊模型的PEM燃料电池发动机故障诊断

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Proton exchange membrane fuel cell (PEMFC) technology has been greatly promoted in recent years, but the fault diagnosis and predictive maintenance are unneglectable issues in practical work. According to the safety and reliability requirement of 60 kW automotive fuel cell engine designed by our group, a fault diagnosis method based on T-S fuzzy model which is tuned and optimized thanks to particle swarm optimization is put forward in this paper. Its inputs include voltage, the lowest single cell voltage, current, temperature and air pressure, by setting the output threshold of T-S fuzzy model at 0.85, when the healthy degree and its variety rate are below 0.85 and 0.05 respectively, the flooding fault is distinguished, if the healthy degree is below 0.85 but its variety rate is above 0.05, drying of the proton membrane is on-line diagnosed successfully, which can provide a guidance to its real-time monitoring and optimized control in future.
机译:近年来,质子交换膜燃料电池(PEMFC)技术得到了极大的促进,但故障诊断和预测维护在实际工作中是不可输入的问题。根据我们组设计的60 kW汽车燃料电池发动机的安全性和可靠性要求,本文提出了基于T-S模糊模型的故障诊断方法,归功于粒子群优化进行了调整和优化。其输入包括电压,最低单电池电压,电流,温度和空气压力,通过设置0.85的TS模糊模型的输出阈值,当健康程度和其种类分别低于0.85和0.05时,洪水发生了区分,如果健康程度低于0.85,但其种类率高于0.05,质子膜的干燥成功诊断,可为其未来的实时监测和优化控制提供指导。

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