Charge-Consistent Estimation of Hydrogen Production in a Membraneless Alkaline Water Electrolyzer Using Time-Resolved Current Measurements

This study presents a phenomenological estimation framework for a membraneless alkaline water electrolyzer (MAWE), developed primarily from experimentally measured current signals and end-of-test mass-loss data. Thirteen KOH concentrations (5–35 g in 1 L deionized water) were investigated under a constant 12 V DC supply for 7200 s. The time-varying current was continuously recorded throughout each experiment, while the total gas production was determined from the net mass loss measured at the end of the electrolysis process. A time-resolved hydrogen-production representation was subsequently reconstructed from the measured current signal using Faraday’s law and constrained to be stoichiometrically consistent with the experimentally observed total mass loss. The term “charge-consistent” used throughout this study does not imply a new electrochemical principle, but rather refers to maintaining physical consistency between the experimentally measured current signal, Faraday-based charge transfer, and the experimentally observed end-of-test mass loss within the proposed phenomenological framework. Experimental results indicate that both the current response and the cumulative gas production exhibit a strong and distinctly nonlinear dependence on the KOH concentration. Two phenomenological modeling approaches were examined. The first is a static polynomial formulation describing the nonlinear relationship between the measured current signal and the reconstructed production rate. The second is a semi-empirical grey-box formulation in which the Faraday-based theoretical production term is corrected using an experimentally identified efficiency coefficient. Model performance was assessed using train/test data partitioning, residual analysis, autocorrelation functions, and Ljung–Box tests, demonstrating a high degree of internal charge consistency and macroscopic agreement with the reconstructed experimental representation. The proposed framework provides a reduced-order and experimentally accessible approach for representing reconstructed production behavior in MAWE systems without resorting to detailed multi-physics modeling or EIS-based characterization and offers a physically consistent baseline for comparison with more complex data-driven or control-oriented modeling strategies.