Fault classification methods for fuel cell vehicles under poor data conditions

Fuel cell vehicles (FCVs) represent a significant direction for the sustainable development of the automotive industry. However, current testing and evaluation standards for FCVs have not thoroughly explored fault types and classifications, leading to the absence of a unified fault grading classification scheme. To address this gap, this paper proposes a comprehensive set of grading classification evaluation indicators for FCV faults to standardize fault levels. Utilizing factor analysis and fuzzy set theory, a fault mode classification evaluation method for FCVs under conditions of data scarcity is developed, thereby guiding the classification of FCV fault levels.