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To study the state of health (SOH) of the proton exchange membrane fuel cell (PEMFC), a novel hybrid method combining the advantages of both the model-based and data-driven methods is proposed. Firstly, the model-based method is proposed based on the voltage degradation model to estimate the variation trend, and three parameters reflecting the performance degradation are selected. Secondly, the data-driven (long short-term memory (LSTM)) method is presented to estimate the variation fluctuation. Moreover, the core step of the hybrid method is returning the results of the LSTM method to the power degradation model as the “observation” and modifying related parameters to improve the estimation accuracy. Finally, the sliding window method is applied to solve the problem of the data increase with the increase of the operating time. The results show that the power estimation is better than the current estimation for the SOH estimation.

High-powered and modularity is the trend for fuel cell systems. Similar to the evolution from single-cylinder to multi-cylinder in conventional internal combustion engines, fuel cell systems shall also follow this developing process. Compared to single-stack fuel cell systems, multi-stack fuel cell systems (MFCS) can enhance the system maximum output power and improve the system performance. To achieve modular design and improve the performance of high-powered MFCS, a MFCS stacks allocation optimization algorithm based on genetic algorithms is proposed in this paper. First, remaining useful life (RUL) and efficiency are choosing as an integrated optimization index, the decision model for MFCS stacks allocation is developed. Then, a heavy-duty commercial vehicle was used as an example to match the vehicle power train parameters. The genetic algorithm is used to solve the global optimal stacks allocation scheme for the vehicle in a specific application scenario.

To study the cold start of muti-stack fuel cell system (MFCS), a novel thermal management subsystem structure and corresponding cold start strategies are proposed. Firstly, leveraging the distinctive configuration of the MFCS that can be sequentially initiated, we augmented the existing thermal management subsystem with the incorporation of two additional collection valves and two bypass diverter valves, which affords an increased degree of flexibility in the formulation of cold-start strategies. Secondly, we innovatively propose a hierarchical auxiliary heating cold start strategy and an average auxiliary heating cold start tailored for MFCS consisting of power levels of 20 kW, 70 kW, and 120 kW. Furthermore, we have developed a controller to address temperature control challenges during the start-up process.