Construction and Mining Technology of Fuel Cell Vehicle Database

To address the fragmented collection and inefficient analysis of road test data hindering fuel cell vehicle (FCV) reliability assessment, this project develops a unified road test database and integrated software platform. The core innovation lies in establishing robust data correlation mechanisms: 1) A multi-protocol data layer captures and standardizes heterogeneous system-level data using edge computing and SQLite persistence, adhering to ISO 23828 standards. 2) A damage equivalence-based three- layer correlation strategy quantitatively links actual user conditions to FC system damage. This integrates multi- objective optimization (NSGA-II) and load frequency sensitivity analysis—identifying component resonance bands through frequency-domain spectra—to enhance test field damage reproducibility by >40%. 3) The platform enables closed-loop validation via a "material-component-vehicle" digital twin, dynamically associating material aging data with real-time vehicle monitoring to refine correlation models. This database-driven approach provides foundational support for accelerated testing and system reliability evaluation..