Numerical Study and Design Optimization of Geometry Parameters of Tesla Valve Flow Fields for Proton Exchange Membrane Fuel Cell

Flow field design in proton exchange membrane fuel cells (PEMFCs) is a critical issue, as it plays an important role in governing reactant transport dynamics and cell performance. In this work, numerical studies of a single Tesla-valve flow field were conducted. The influence of loop radius, channel angle, and channel height on the performance of PEMFCs were fully explored. Then, aiming to maximize the output current density, this study optimized the Tesla-valve flow field configuration through a framework that integrates Gaussian process modeling with a Genetic Algorithm (GA). The approach efficiently identifies the optimal geometric parameters, highlighting effective synergy between the surrogate model and intelligent evolutionary optimization for enhanced performance. Simulation results show that the current density at 0.4 V and the highest power density have been improved by more than 10% compared to the baseline design for both forward and reverse flow. The optimized Tesla valve design has been compared with conventional parallel and serpentine flow fields of the same flow area. Results show that, despite the larger pressure drop for the single channel case—which is due to the insufficient length of the serpentine channel—the Tesla-valve flow field demonstrated superior performance in other metrics, including current and power density, under both flow directions.