Three-dimensional multi-field digital twin technology for proton exchange membrane fuel cells

In times of the commercialization process of proton exchange membrane fuel cells (PEMFCs), a full knowledge of in-situ state in PEMFCs is of critical significance to the in-situ operational process and the evaluation of material stage and potential damage. The conventional experimental observation and in-situ prediction models can only obtain very limited information while the computational fluid dynamics approach takes too long time to get the detailed information. To reach a full knowledge of PEMFC real-time state, a novel 3D multi-physics digital twin model for PEMFCs is proposed based on the proper orthogonal decomposition (POD) method. In the model, firstly, for one kind of PEMFC, 139 ex-situ snapshots are designed and simulated based on the three-dimensional two-phase non-isothermal numerical model with the assumption of liquid pressure continuity in the whole membrane electrode assembly. Then the modes of each field in snapshots are extracted by singular value decomposition method using Jacobi algorithm. Finally, the coefficients in the POD prediction equation are obtained by using the multivariate adaptive regression splines. The digital twin results of voltage, temperature, membrane water content and liquid water saturation fields are exhibited and analyzed. Results suggest that for the studied PEMFC, the digital twin technique can capture the global values and the local distribution characteristics of each above physical fields well in 0.913 s. The mean global deviations of the above four fields of 20 groups of random conditions within wide current density and operational condition ranges are 5.7 %, 1.3 %, 8.9 % and 12.0 % respectively. Even though the practical results can only be applied for the studied PEMFC, the proposed methodology has its general application range.