Comprehensive dynamic multiphysics modeling and control strategy for hydrogen-in-oxygen suppression in alkaline water electrolysis

Alkaline water electrolysis technology is one of the key technical pathways for green hydrogen production, renewable power consumption and carbon emission reduction. The accurate prediction and control of hydrogen-in-oxygen (HTO) levels are critical for operational safety. In this study, a comprehensive dynamic system model covering all components and processes is established. This model integrates electrochemical reactions, gas–liquid two-phase flow, hydrogen/oxygen diffusion with mass transfer, phase equilibrium, and heat dissipation processes to predict system pressure, electrolyte/gas flow rates, temperature, and dynamic HTO responses, validated against startup, step, photovoltaic, and wind experiments. Four HTO contribution mechanisms, including concentration gradient-driven saturation diffusion, oversaturation diffusion in the stack, and unseparated gaseous hydrogen and dissolved hydrogen in the gas–liquid separators, are identified. The contributions of operational parameters to the four mechanisms are quantified. The effects of current density, temperature, lye flow rate, and system pressure on the HTO concentration are investigated. A safety operation map for current density versus pressure/flow rate is established, and the critical safety pressures and flow rates are determined. A feedforward control strategy based on pressure-flow coordinated regulation is developed to achieve active suppression of HTO exceedance risks during external current dynamics under various fluctuation conditions. The full-process multiphysics framework provides a transferable modeling basis for characterizing larger scale ALK systems and for informing their structural design and control optimization.