Online Monitoring of Fuel Cell Electrochemical Impedance Spectrum with Multi-stages Multi-sine Signals Based on DC–DC Converter

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Abstract
Advanced sensors based on electrochemical impedance spectrum (EIS) are essential for fuel cell system state estimation, fault diagnosis, and health management. However, traditional EIS methods are unsuitable for real-time state management due to high costs, large sizes, and long acquisition times, limiting their online industrial application. To enhance onboard EIS application, this study proposes a novel multistage and multisine injection method to improve wideband frequency sweeping, balancing EIS quality, and measurement time using a four-phase floating-interleaving parallel dc–dc converter prototype with EIS injection functions. In addition, a fuel cell coupled with a four-phase floating-interleaving parallel dc–dc equivalent circuit model is established for comprehensive performance analysis in impedance calculation with different excitation methods. Experimental validation showed an impedance magnitude error within 3.2% from 1 kHz to 0.1 Hz, and the implementation reduces EIS measurement time from 900 s to approximately 150 s. Furthermore, a case study on fuel cell EIS sensitivity under dynamic conditions indicates that the proposed prototype can capture dynamic EIS variations using local multifrequency points.
Funding Information
  • Shanghai Academic/Technology Research Leader (22XD1423800)

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