贫数据条件下燃料电池汽车故障分类方法

Fault Classification Methods for Fuel Cell Vehicles under Poor Data Conditions

燃料电池汽车是未来汽车工业可持续发展的重要方向,但现存燃料电池整车相关的测试评价标准尚未对燃料电池汽车存在的故障类型及其分类进行深入研究,缺乏统一故障分级分类方案。为改善该问题,提出一套完善的燃料电池汽车故障模式的分级分类评价指标以统一相关故障等级,重点研究在缺乏数据条件下的燃料电池汽车故障分类方法。基于因子分析法和模糊集理论,提出一种针对燃料电池汽车在贫数据条件下的故障模式分类评价方法,为燃料电池汽车故障等级的分类提供指导意见。

Fuel cell vehicle(FCV)is an important direction for the sustainable development of the automotive industry in the future.However,existing test and evaluation standards for FCVs have not thoroughly examined the types of faults and their classification.There is a lack of a unified fault grading classification scheme.To solve this issue,a comprehensive set of grading classification evaluation indicators for FCV faults is proposed to standardize the levels of related faults.The focus is on researching methods for classifying FCV faults in the case of lack of data.Based on factor analysis and fuzzy set theory,a fault mode classification evaluation method for FCVs under data scarcity conditions is proposed,offering guidance for the classification of FCV fault levels.