Electrolyzer Model Research Articles

A control-oriented comprehensive model of PEM electrolyzer considering double-layer capacitance

The modeling of electrochemical and thermal characteristics of proton exchange membrane (PEM) electrolyzer is significant in the hydrogen production process. However, the calculation of electrode impedance and double-layer capacitance during operation is not accurate enough currently, and the electrothermal coupling characteristics of hydrogen production devices are not fully considered. In this paper, the multi-stage equivalent circuit of the PEM electrolyzer is designed using electrochemical impedance spectroscopy (EIS) and the time-constant fitting method. In addition, according to the temperature control system of the actual hydrogen production device, the electro-thermal model of the PEM electrolyzer is established, in which the fuzzy PID control is used to maintain the temperature stability. Moreover, the electrical characteristics and temperature characteristics are simulated in different time scales. Finally, compared to the existing models, the proposed model is more accurate, and it indicates that the proposed model has better accuracy against the existing models.

Less is more: Optimisation of variable catalyst loading in CO[formula omitted] electroreduction

The electrochemical conversion of CO2 is a promising method of carbon-neutral chemical production. However, commercial realisation in aqueous electrolytes is challenging, due to competition with the hydrogen evolution reaction (HER), and the propensity for CO2 to participate in the carbonate equilibrium reactions. These two phenomena are linked through OH− ions, as both the by-product of the catalytic reactions and the culprit behind the parasitic carbonate reactions. By reducing the local catalyst loading where the CO2 concentration is low, the HER is decreased more than the reactions that are dependent on CO2 as a reactant. Therefore, it is possible to improve reaction selectivity and reactant utilisation while reducing the capital cost of catalyst. We demonstrate this theory through an analytical solution of a 1D flow electrolyser model. We extend this to a comprehensive model of a contemporary gas-diffusion electrode (GDE) setup. We find that the operation costs are dominated by the electrolyser power consumption and, to a lesser degree, the cost of CO2 and its recovery at the anode. We numerically obtain the catalyst loading profiles that maximise operating profit. The optimisation process reveals that profits are maximised for high gas flow rates, and consequently, low single pass conversions, where the CO2 concentration is as high as possible. However, when lower gas flow rates are used for practical reasons, variable catalyst loadings are shown to lead to significant operational improvements, especially in the production of higher C products that require a greater number of electrons transferred. The model is made freely available in MATLAB and its use is encouraged in determining the applicability of variable catalyst loading to future experimental setups.

Numerical study of proton exchange membrane water electrolyzer performance based on catalyst layer agglomerate model

In this work, a two-dimensional two-phase model of proton exchange membrane water electrolyzer (PEMWE) is developed, in which the catalyst layer (CL) is represented using agglomerate model. The effects of CL composition, porous transport layer (PTL) material properties and operating conditions on PEMWE performance are investigated. The results indicate that small size of catalyst agglomerate around 0.25 μm would benefit PEMWE performance. Appropriate increase of catalyst loading, porosity and ionomer volume fraction in the CL improves PEMWE performance, but their further increment leads to high mass transfer resistance, limiting the improvement of electrolyzer performance. The porosity and ionomer volume fraction of the catalyst layer are suggested to be lower than 0.5 and 0.6, respectively. The catalyst loading should be lower than 1.5 mg cm−2 when the CL porosity is higher than 0.3. The PTLs with high permeability, porosity and low contact angle is beneficial for the gas–liquid two-phase flow and avoiding the overheat and water shortage in the electrolyzer. Increasing the inlet velocity accelerates the bubble removal process, but might results in significant temperature drop, degrading the PEMWE performance. The most suitable temperature of inlet liquid is around 353.15 K. The results provide important guidance for the optimization design of high-performance PEMWE.

Energy consumption model of flow-through electrolyzer considering mass transfer overpotential for hydrogen production from alkaline water splitting

Flow-through electrolyzer can improve the efficiency of hydrogen production from alkaline water splitting and determining the optimal electrolyte velocity through electrode pores is crucial for reducing energy consumption. In this study, an energy consumption model of flow-through electrolyzer considering mass transfer overpotential (Emass) has been developed. The model of Emass due to gas hold-up (ϕ) in the electrolyzer accounts for the density, viscosity, surface tension, linear velocity, and current density. The model-predicted value is in good agreement with the experimental results, which indicated that the increase of velocity effectively reduces ϕ and Emass. Then, Voltage-Current curve models combining reversible voltage, activation overpotential, ohmic overpotential, and Emass are developed. Based on this, an energy consumption model, combining both consumption from electrolyzer and pumps, is established to evaluate the overall energy consumption of hydrogen production. It can be calculated the Emass at 400 mA cm−2, 6 M KOH, 353 K can be reduced from 0.363 V to 0.048 V if the circulation velocity rises from 0.001 m s−1 to 0.1 m s−1. The model predicts that total energy consumption is 4.36 kWh Nm−3 with energy consumption for pump being 0.02 kWh Nm−3 at 400 mA cm−2 and 0.063 m s−1.

Optimal Design and Operation of Electrolytic Hydrogen Production and Storage System for Solar Photovoltaic Power Smoothing

Even though the increasing penetration of solar photovoltaic (PV) energy into the electric grid can reduce the carbon emission of power generation, the intermittency and variability of renewable solar energy lead to frequent and steep ramping operations of conventional fossil fuel power plants. Hydrogen production via water electrolysis using solar power can serve as a controllable load and provide a short/long duration energy storage to mitigate the grid fluctuations (i.e., PV smoothing) and improve the resiliency of power grid. The generated green hydrogen will be further stored under high pressure for subsequent utilizations (e.g., hydrogen fuel cell electric vehicle refueling).Polymer electrolyte membrane (PEM) electrolyzer with high efficiency and quick dynamic response is used to generate hydrogen [1,2]. The capacity factors of PV field and PEM electrolyzer can affect the performance of PV smoothing on the cloudy day. Even though PEM electrolyzers directly producing high pressure hydrogen are more energy efficient than ambient pressure electrolyzers followed by mechanical compression, higher pressure leads to more undesired hydrogen back diffusion to the oxygen side, which causes lower hydrogen production efficiency, cell degradation, and safety risk of hydrogen explosion limit [3,4]. Optimal design and operation of electrolyzer under fluctuating solar power are formulated based on an integrated hydrogen-based energy storage system (renewable solar coupled with green hydrogen production and storage). Different PV smoothing scenarios as well as optimal size and operation conditions of the PEM electrolyzer are investigated.The high-fidelity dynamic model of a PEM electrolyzer cell/stack is established with consideration of two-dimensional (“through-plane” and “in-plane”) mass/heat transfer coupled with electrochemical kinetics. The electrochemical reactions are considered using Butler-Volmer kinetics with varying surface molar concentrations of components. Maxwell-Stefan diffusion equation is adopted to calculate the gas-phase species molar concentration in the backing and catalyst layers. Hydrogen permeation back through membrane is included with consideration of both diffusion and convective transports as a function of operational pressure.To evaluate the transient response of the PEM electrolyzer stack, real-time PV data based on an Orlando Utilities Commission (OUC) solar farm is smoothed using the developed power signal control algorithm. The optimal PV smoothing control algorithm and the electrochemical dynamic stack model show the effectiveness of hydrogen-based energy storage system in smoothing the PV signal to improve the grid stability and flexibility.[1] Kumar, S.S. and Himabindu, V., 2019. Hydrogen production by PEM water electrolysis–A review. Materials Science for Energy Technologies, 2(3), pp.442-454.[2] Götz, M., Lefebvre, J., Mörs, F., Koch, A.M., Graf, F., Bajohr, S., Reimert, R. and Kolb, T., 2016. Renewable Power-to-Gas: A technological and economic review. Renewable energy, 85, pp.1371-1390.[3] Trinke, P., Bensmann, B., Reichstein, S., Hanke-Rauschenbach, R. and Sundmacher, K., 2016. Hydrogen permeation in PEM electrolyzer cells operated at asymmetric pressure conditions. Journal of The Electrochemical Society, 163(11), p.F3164.[4] Scheepers, F., Stähler, M., Stähler, A., Rauls, E., Müller, M., Carmo, M. and Lehnert, W., 2020. Improving the efficiency of PEM electrolyzers through membrane-specific pressure optimization. Energies, 13(3), p.612.

Techno-economic assessment of waste heat recovery for green hydrogen production: a simulation study

AbstractThe demand for hydrogen as a green energy carrier is increasing as energy sources shift towards sustainable solutions. Alkaline electrolysers offer a clean method to produce hydrogen, though their limited efficiency results in significant energy loss. This study explores the potential to enhance electrolyser efficiency through waste heat recovery. It examines the technical and economic aspects of using excess heat from an alkaline electrolyser, powered by surplus renewable energy, as a feed-in source for district heating. Utilising a simulation framework for renewable power plants, the study integrates a validated electrolyser model. The analysis focuses on the impact of heat utilisation and heat sales on system efficiency, economic viability, and hydrogen pricing. Findings show improved efficiency with heat supply, especially for smaller electrolyser configurations. Heat sales lead to a slight reduction in hydrogen costs and the study demonstrates their viability for smaller electrolysers. Additionally, it highlights the need for an advanced cooling strategy for larger systems. Overall, the results underscore the potential of integrating electrolysis with district heating, offering valuable insights for future renewable-powered energy systems.

On the viability of electrochemical carbon dioxide in-situ resource utilization to produce chemical feedstocks on Mars

The long-term, crewed exploration of Mars is a priority for both national and private space entities. Given economical constraints on the mass sent off-world from Earth, in situ resource utilization (ISRU) through ultra-low temperature CO2-H2O electrolyzer technology that is fed using the Martian atmosphere’s CO2 (∼95 %) and the subsurface Martian water cycle (enabled by perchlorate salts that depress the Martian brine’s freezing point to < 213 K) has been proposed as a pathway towards fuel and chemical feedstock. Herein we applied a validated, computationally frugal electrolyzer model to a Martian CO2-H2O electrolyzer and examined its viability. Through a judicious combination of catalysts, such electrolyzers could produce O2, CO, HCHO, CH3OH, CH4, C2H4, and C2H5OH even at ambient Martian temperatures (∼237 K). Our modeling herein shows the theoretical production of these key resources in acidic electrolyzers to be at a scalable rate of 0.052 – 1.13 g per cm2 per day of CO, 0.0004 – 0.086 g per cm2 per day of CH3OH, 0.001–0.048 g per cm2 per day of CH4, 0.0164 – 0.171 g per cm2 per day of C2H4, 0.008 – 0.0125 g per cm2 per day of C2H5OH. A range of catalyst candidates were examined for product selectivity, energy efficiency and throughput. Ambient temperature CO2-H2O electrolysis is shown to be an energy efficient approach to chemical feedstocks needed for the sustained exploration of Mars and beyond. This model can inform future astronaut life support device development for NASA and other space faring entities.

Mathematical modeling of an integrated photovoltaic-assisted PEM water electrolyzer system for hydrogen production

This work provides a new mathematical model of photovoltaic (PV) solar panels integrated with proton exchange membrane (PEM) water electrolyzer cells for optimal hydrogen production. The proposed mathematical model evaluates the operating temperature of the PV solar panel and PEM water electrolyzer and the effect of membrane thickness on hydrogen production performance. In the model results, when the operating temperature of the PEM water electrolyzer increased from 25 °C to 80 °C, the hydrogen flow rate of about 1.44 and 1.82 mL/min at 2 A/cm2, respectively. Moreover, the maximum flow rate of hydrogen produced in a 7-cell and 14-cell PV-assisted PEM water electrolyzer stack is around 349.98 mL/min and 699.91 mL/min, respectively. The total efficiency of the integrated PV-assisted PEM water electrolyzer stack is around 6.0–6.5%, depending on the solar irradiance values. This mathematical model significantly contributes to green hydrogen production using the integrated PV-assisted PEM water electrolyzer system. Moreover, the mathematical model of PV-assisted PEM water electrolyzer will be a pioneer in determining the hydrogen production potential of the PEM water electrolyzer systems.

An Electrolyzer Model for Power System Operation Optimization Over Broad Temperature Range

An Electrolyzer Model for Power System Operation Optimization Over Broad Temperature Range

Techno-economic analysis of the effect of a novel price-based control system on the hydrogen production for an offshore 1.5 GW wind-hydrogen system

The cost of green hydrogen production is very dependent on the price of electricity. A control system that can schedule hydrogen production based on forecast wind speed and electricity price should therefore be advantageous for large-scale wind-hydrogen systems. This work presents a novel price-based control system integrated in a techno-economic analysis of hydrogen production from offshore wind. A polynomial regression model that predicts wind power production from wind speed input was developed and tested with real-world datasets from a 2.3 MW floating offshore wind turbine. This was combined with a mathematical model of a PEM electrolyzer and used to simulate hydrogen production. A novel price-based control system was developed to decide when the system should produce hydrogen and when it should sell electricity to the grid. The model and control system can be used in real-world wind-hydrogen systems and require only the forecast wind speed, electricity price and selling price of hydrogen as inputs. 11 test scenarios based on 10 years of real-world wind speed and electricity price data are proposed and used to evaluate the effect the price-based control system has on the levelized cost of hydrogen (LCOH). Both current and future (2050) costs and technologies are used, and the results show that the novel control system lowered the LCOH in all scenarios by 10–46%. The lowest LCOH achieved with current technology and costs was 6.04 $/kg H2. Using the most optimistic forecasts for technology improvements and cost reductions in 2050, the model estimated a LCOH of 0.96 $/kg H2 for a grid-connected offshore wind farm and onshore hydrogen production, 0.82 $/kg H2 using grid electricity (onshore) and 4.96 $/kg H2 with an off-grid offshore wind-hydrogen system. When the electricity price from the period 2013–2022 was used on the 2050 scenarios, the resulting LCOH was approximately twice as high.

Intellectual control of the electrolysis process in the production of caustic soda

This article is based on the modeling of the operating mode of the membrane electrolyzer in the production of caustic soda through a neural network. In the course of work, a neural network model of the operation of the electrolyzer element was developed. Neural network software was used to create and train neural networks. The purpose of this work is to create an accurate model of the electrolyzer element using the following tasks was to create: the process of designing optimal structures of neural networks and their training, creating an electrolyzer model by training neural networks, as well as processing the modeling results. As a result of this work, a neural network model was developed, which allows to quickly and accurately calculate the result of the operation of the electrolyzer under any initial conditions.

Advancing Fundamental Understanding of Electrolyzers for Cost-Effective Green H2 Production

Reaching net-zero by 2050 is critical to limit global warming to below 2°C by 2100. Renewable energy will play a vital role in this transition, and one of the key challenges is to deploy them at a multi-GW scale. TotalEnergies’ Hydrogen R&D department is committed to developing green H2 production and storage technologies to meet this challenge.In this talk, we will focus on alkaline electrolysis, which has been around for over a century but still presents significant challenges for GW-scale projects. We will discuss how our research can improve the efficiency, durability, and cost-effectiveness of alkaline electrolyzers. For instance, we will demonstrate using a simplified electrolyzer model that a good understanding of the kinetics of ageing phenomena can drastically impact the H2 production cost and the maintenance philosophy of an industrial plant. Based on these observations, we will propose a methodology to refine this understanding, and to better grasp the effect of intermittent operation of the electrolyzer on its ageing. Finally, we will highlight some fundamental findings made by academia that we believe could be good to explore to increase alkaline electrolyzer performance.In conclusion, there is a need to increase the dialogue between industry and academia to tackle the challenges of green H2 production at the multi-GW scale. By working together, industry and academia can develop more efficient and cost-effective green H2 production technologies, bringing us closer to achieving our ambitious multi-GW scale targets.

Modeling Contact Resistance and Water Transport within a Cathode Liquid-Fed Proton Exchange Membrane Electrolyzer

Conventional proton-exchange membrane (PEM) water electrolyzers use thicker membranes (>175 μm) than their PEM fuel cell counterparts (<25 μm), which reduces hydrogen crossover but also reduces electrolyzer efficiency due to the increased resistance. Reduction of hydrogen crossover is critical in conventional systems to avoid buildup of hydrogen in the anode above the lower flammability limit. New concepts for operating PEM water electrolyzers are emerging, such as the patented concept involving liquid water supply at the cathode while operating the anode with air, which reduces the safety concern related to hydrogen crossover using thin membranes. Experimental work has demonstrated the viability of this approach, but open questions remain regarding the interplay between water transport, water consumption, and cell performance, as well as identifying the components and material properties that enable high performance. In this work, a physics-based computational model of a cathode-fed PEM water electrolyzer was developed. The model highlights the importance of limiting contact resistance and explores the effect of cell compression on non-uniformity of current distributions. Sensitivity studies found that membranes up to 50 μm thick can be used without significant water transport limitations.

Coordinated Control Strategy for System of Hydrogen Production from Renewable Energy Considering Regulating Characteristics of Electrolyzers

As a low-carbon and clean form of energy development and utilization, renewable energy hydrogen production technology has received widespread attention. However, under traditional control strategies, the electrolyzers are generally operated at rated power, and their ability to participate in the system of hydrogen production from renewable energy and grid regulation is not fully utilized. Therefore, this article proposes a coordinated control strategy for the system of hydrogen production from renewable energy that considers the regulation characteristics of electrolyzers. Firstly, models of each unit are established, and based on this, the working characteristics of the electrolyzer are analyzed through electrolyzer model simulation. Then, control strategies for each unit were designed, and the additional response control module is added to the control strategy of the electrolyzers to alleviate the fluctuation of DC bus voltage. Finally, through analysis, this coordinated control strategy has been proven to be effective.

Effect of a Large Proton Exchange Membrane Electrolyser on Power System Small-Signal Angular Stability

The dynamics of electrical systems have changed significantly with the increasing penetration of non-conventional loads such as hydrogen electrolysers. As a result, detailed investigations are required to quantify and characterize these loads’ effects on the dynamic response of interconnected synchronous machines after being subjected to a disturbance. Many studies have focused on the effects of conventional static and dynamic loads. However, the impact of hydrogen electrolysers on the stability of power systems’ rotor angles is rarely studied. This paper assesses the effect of proton exchange membrane (PEM) electrolysers on small-disturbance rotor-angle stability. Dynamic modelling and the control of a PEM electrolyser as a load are first studied to achieve this. Then, the proposed electrolyser model is tested in the Amercoeur plant, which is part of the Belgian power system, to study its effect on the small-signal rotor-angle stability. Two approaches are considered to examine this impact: an analytical approach and time-domain simulations. The analytical approach consists of establishing a state-space model of the Belgian test system through linearisation around an operating point of the non-linear differential and the algebraic equations of the synchronous generators, the PEM electrolyser, the loads, and the network. The obtained state-space model allows for the determination of the eigenvalues, which are useful to evaluate the effect of the PEM electrolyser on the small-signal rotor-angle stability. This impact is investigated by examining the movement of the eigenvalues in the left complex half-plane. The obtained results show that the PEM electrolyser affects the electromechanical modes of synchronous machines by increasing their oscillation frequencies. The results also show that the effect of the electrolyser on these modes can be improved by adjusting the inertial constant and the damping coefficient of the synchronous machines. These results are consolidated through time-domain simulations using the software Matlab/Simscape from the version MatlabR2022a-academic use from Mathworks.

Optimization of membrane thickness for proton exchange membrane electrolyzer considering hydrogen production efficiency and hydrogen permeation phenomenon

Reducing the membrane thickness of Proton exchange membrane (PEM) electrolyzer was found to efficiently promote the hydrogen production rate. However, it can also aggravate the phenomenon of hydrogen permeation, leading to an increased hydrogen content on the anode side and posing a risk of explosions. Thus, optimal design of the membrane thickness of PEM electrolyzer systems is crucial to ensure both safe and efficient hydrogen production. In this paper, we propose two optimization problems for the membrane thicknesses, aiming at achieving a balance between the hydrogen content on the anode side and the hydrogen production rate under constant and varying power input conditions. First, the theoretical model of a PEM electrolyzer is established, and a photovoltaic-PEM electrolyzer system is considered to provide varying power input conditions. Then, the two optimization problems are formulated and resolved using the sequential quadratic programming (SQP) and particle swarm optimization (PSO) algorithms, respectively. Our results reveal that the optimal membrane thickness decreases as the constant input power increases. This suggests that high/low power inputs require thin/thick membranes. For varying power input, we collected one year of solar radiation intensity data from four different regions in China. The findings demonstrate that the selection of the optimal membrane thickness depends not only on the average solar radiation intensity but also on its seasonal variations. By applying these strategies, we effectively optimize the membrane thickness in PEM electrolyzer systems, thereby enhancing the efficiency and safety of hydrogen production. The outcomes provide valuable insights for selecting the appropriate membrane thickness in regions with varying solar radiation intensities and accounting for seasonal variations in solar radiation.

Holistic and dynamic mathematical model for the assessment of offshore green hydrogen generation and electrolyser design optimisation

The decarbonisation of the energy system will imply the use of unexplored locations and technologies. In this sense, generation of green H2 in far-offshore farms may be an alternative. However, the offshore green H2 generation potential is commonly assessed by using constant conversion rates. This paper presents a holistic and dynamic mathematical model coupling the aero-hydrodynamic model with the polymer electrolyte membrane (PEM) electrolyser model. The model enables a more accurate and comprehensive analysis of the realistic H2 generation capacity considering the power-to-gas system efficiency. First, the model of the PEM electrolyser is validated and a wide sensitivity analysis is computed in order to report the impact of the operational conditions. Then, H2 production is assessed focused on (i) the stack performance and (ii) the system performance. The system performance results in a efficiency reduction of up to 10% in the case of FOWTs and up to 70% in WECs due to the fluctuations of the power signal. Hence, results highlight the need for a holistic system assessment instead of focusing on the stack. Finally, transient effects are considered, concluding that in highly fluctuating applications, such as renewables, external heat sources may improve the performance of the system.

Extended load flexibility of utility-scale P2H plants: Optimal production scheduling considering dynamic thermal and HTO impurity effects

Flexible power-to-hydrogen (P2H) production enables the admittance of renewable energies on a utility scale and provides the connected electrical power system with ancillary regulatory services. To extend the flexibility and thus improve the profitability of green hydrogen production, this paper presents an optimal production scheduling approach for utility-scale P2H plants composed of multiple alkaline electrolyzers. Unlike existing works, this work discards the conservative constant steady-state constraints and first leverages the dynamic thermal and hydrogen-to-oxygen (HTO) impurity crossover processes of the electrolyzers to improve flexibility. Doing this optimizes their effects on the loading range and energy conversion efficiency. The proposed multiphysics-aware scheduling model is formulated as mixed-integer linear programming (MILP). It coordinates the electrolyzers’ operation state transitions and load allocation subject to comprehensive thermodynamic and mass transfer constraints. A decomposition-based solution method, SDM-GS-ALM, is adopted to address the scalability issue for scheduling large-scale P2H plants composed of tens of electrolyzers. With an experiment-verified dynamic electrolyzer model, case studies show that the proposed method remarkably improves the hydrogen output and profit of P2H production powered by either solar or wind energy compared to the existing scheduling approach.

Efficient integration of alkaline water electrolyzer – A model predictive control approach for a sustainable low-carbon district heating system

District heating systems can utilize renewable energy sources and waste heat from industrial processes, making them a cost-effective heating solution. This paper integrates an electrolyzer technology into district heating system to improve energy efficiency and reduce greenhouse gas emissions by a power to hydrogen and heat model. To accurately predict the electrolyzer’s electrochemical and thermal dynamic behavior, an advanced electrolyzer model is developed. The proposed model presents a dynamic approach implemented in model predictive control to optimize electrolyzer performance and reduce power fluctuations. By managing on–off cycles, degradation costs, temperature, and efficiency of the electrolyzer, the proposed model aims to harness waste heat generated during electrolysis, and store hydrogen in a hydrogen storage tank to manage renewable fluctuations. The district heating system utilizes electric, natural gas, and hydrogen boilers along with waste heat recovered from the electrolyzer to meet energy demands. The proposed model promotes sustainability and efficiency of district heating systems by utilizing renewable energy sources and effectively managing the electrolyzer. Case studies demonstrate the model's advantages and effectiveness, with results indicating that the optimal strategy utilizes recovered waste heat to satisfy approximately 10% of the heat demand, achieving an average electrolyzer efficiency of 90% and further enhancing sustainability.

Dynamic parameter estimation of the alkaline electrolysis system combining Bayesian inference and adaptive polynomial surrogate models

Utility-scale hydrogen production via alkaline electrolysis (AEL) is a promising pathway toward the decarbonization of the power, transportation, and chemical industries. The efficiency, load flexibility, and operational safety of the AEL system are subject to electrochemical, thermal, and mass transfer dynamics, and the corresponding parameters, including overvoltage coefficients, heat capacities and resistances of the stack and lye-gas separators, thickness and permeability of the diaphragm, etc. The community has developed many models to depict these dynamic behaviors. However, due to the lack of a comprehensive parameter estimation method, these models are generally tuned manually in industrial applications, which can be inaccurate and cannot fit their time-varying nature. To fill this gap, we present a fast and accurate parameter estimation method for the AEL system. Specifically, to address the difficulties of strong nonlinearity of the dynamic electrolyzer models and correlation between different parameters, a Bayesian inference-based Markov chain Monte Carlo method is proposed. To reduce the computing time for online estimation, data-driven adaptive polynomial surrogate models are established to replace repeated time-domain simulations of the electrolyzer model so that estimation can be finished within a few minutes. Experiments on a 5 Nm3/hr-rated AEL system validate the proposed method. Compared with the existing Kalman filter variants, the estimation error is reduced by at most 71.1% in terms of RMSE and NRMSE. In addition, the proposed method provides approaches to fault diagnosis and global sensitivity analysis for operating and designing AEL systems.