Concepedia

Publication | Open Access

Operating condition optimization of heavy-duty truck PEM fuel cell for enhanced performance and durability

14

Citations

41

References

2025

Year

Abstract

Since the truck industries adopt fuel cell hybrid system to cope with greenhouse gas regulation, the long-term durability of hydrogen fuel cell system is paid more attention. Different from passenger vehicles, operation of heavy-duty truck requires medium to heavy load for general driving conditions. This study employs response surface methodology (RSM) to determine optimal operating conditions for long term durability. Firstly, the stack simulation model with degradation capability is developed that supports RSM for optimization. The variables include operating fuel cell temperature (T), anode stoichiometry (Sa), cathode stoichiometry (Sc), anode relative humidity (RH a ), and cathode relative humidity (RH c ). Output power and degradation rate , were identified as objective functions. Response surface analysis demonstrated the interaction between design parameters and the output power and degradation rate of the PEMFC stack . This analysis reveals that the performance and durability of PEMFCs are highly influenced by the interplay of key operating parameters, including temperature, stoichiometry, and relative humidity. Optimal performance is achieved by maintaining a balance of moderate temperature (65–70 °C), intermediate stoichiometric ratios, and relative humidity levels (50–60%). To minimize degradation, it is crucial to operate under moderate temperatures, balanced stoichiometry, and high humidity levels, which help alleviate thermal stress, dehydration, and oxidative damage . The identified optimal conditions for maximizing power output while minimizing the degradation rate are T = 71.5 °C, Sa = 1.2, Sc = 3.0, RHa = 100%, and RHc = 72.7%, resulting in an estimated lifetime of 10,328 h. • Sensitivity analysis of operating conditions was analyzed. • Interactive effects of the operating conditions was comprehensively analyzed. • RSM and PEMFC model were combined to perform a multi-objective optimization.

References

YearCitations

Page 1