НЕЛІНІЙНЕ КЕРУВАННЯ СТРУМОМ ЛУЖНОГО ЕЛЕКТРОЛІЗЕРА ДЛЯ ВИРОБНИЦТВА ВОДНЮ З УРАХУВАННЯМ ОБМЕЖЕННЯ НАПРУГИ ПЕРЕТВОРЮВАЧА

Антон Торопов; Лілія Торопова; Михайло Гайко

doi:10.20535/1813-5420.3.2026.364565

Vol. · Issue 3 · 2026 Oct 12, 2026 TECHNOLOGIES AND EQUIPMENT IN ENERGY

NONLINEAR CURRENT CONTROL OF AN ALKALINE ELECTROLYZER FOR HYDROGEN PRODUCTION, TAKING INTO ACCOUNT THE VOLTAGE LIMITATION OF THE CONVERTER

Anton Toropov Corresponding National Technical University of Ukraine «Igor Sikorsky Kyiv Polytechnic Institute», Ukraine

Liliia Toropova National Technical University of Ukraine «Igor Sikorsky Kyiv Polytechnic Institute», Ukraine

Mykhailo Haiko National Technical University of Ukraine «Igor Sikorsky Kyiv Polytechnic Institute», Ukraine

Pages76-82 PublishedOct 12, 2026 LicenseOpen Access

PDF (Ukrainian)

VOL · ISS 3 · 2026 85 View issue

Abstract

A nonlinear mathematical model of the current stabilization system is constructed, taking into account the power limitation of the converter, the inertia of the polarizing EMF and the change in conductivity when electrolysis is heated. As a result, a mathematical model was obtained in deviations from the operating parameters of the electrolyzer in the form of a system of nonlinear differential equations of the third order. Further, to optimize the operation of the electrolyzer, it is proposed to use a regulator that ensures the extremization of the quality functionality at a minimum of dynamic error. Due to the presence of significant linearity of the "constraint" type, the problem of an optimal regulator for different regions of the phase space was solved. Then there was the "stitching" of the obtained solutions by presenting variations in the parameters of linear-quadratic regulators in the form of new control variables. For this purpose, a modified Hamilton-Jacobi-Bellman equation was compiled and the problem of optimal change in the parameters of the current regulator was solved. As a result, a nonlinear control law was obtained as a function of state variables, which are deviations from the specified values of the electrolyzer parameters. The advantages of the nonlinear regulator have been tested by the digital modeling method.

Keywords

#electrolyzer #current stabilization #linear-quadratic regulator #nonlinear control #Hamilton-Jacobi-Bellman equation

References

Boychenko, S., Koshyl, P., Shkilniuk, I., Danilin, O., & Diedov, M. (2026). Ohliad tekhnolohii vyrobnytstva, transportuvannia, zberihannia ta statsionarnoho vykorystannia zelenoho vodniu. Stan i perspektyvy. Systemni doslidzhennia v enerhetytsi, 1(85), 33–51. https://doi.org/10.15407/srenergy2026.01.033
Christensen, A. H. D., Cantisani, N., You, S., & Jørgensen, J. B. (2025). Nonlinear model predictive control for dynamic operation of an alkaline electrolyzer. IFAC-PapersOnLine, 59(6), 433–438. https://doi.org/10.1016/j.ifacol.2025.07.184
Guilbert, D., & Vitale, G. (2019). Dynamic emulation of a PEM electrolyzer by time constant based exponential model. Energies, 12(4), Article 750. https://doi.org/10.3390/en12040750
Kudin, V., & Kolachny, I. (1998). Synthesis of suboptimal nonlinear regulator by immersion method. Journal of Electrical Engineering, 49(1–2), 11–15.
Nagpure, T., & Chen, Z. (2016). Control-oriented modeling of ionic polymer-metal composite enabled hydrogen gas production. International Journal of Hydrogen Energy, 41(16), 6619–6629. https://doi.org/10.1016/j.ijhydene.2016.03.055
Niknezhadi, A., Allué-Fantova, M., Kunusch, C., & Ocampo-Martínez, C. (2011). Design and implementation of LQR/LQG strategies for oxygen stoichiometry control in PEM fuel cells based systems. Journal of Power Sources, 196(9), 4277–4282. https://doi.org/10.1016/j.jpowsour.2010.11.059
Qi, R., Li, J., Lin, J., Song, Y., Wang, J., Cui, Q., Qiu, Y., Tang, M., & Wang, J. (2022). Design of the PID temperature controller for an alkaline electrolysis system with time delays. arXiv. https://doi.org/10.48550/arXiv.2210.00801
Reimann, A., Kohlenbach, P., Röntzsch, L., & Schneider, C. (2025). Development and validation of a quasi-2D electrolysis stack model with a focus on dynamic thermal behavior. International Journal of Hydrogen Energy, 118, 457–471. https://doi.org/10.1016/j.ijhydene.2025.03.225
Yang, J., Zhang, J., Liu, M., Sun, J., & Shangguan, Z. (2024). Dynamic simulation and performance analysis of alkaline water electrolyzers for renewable energy-powered hydrogen production. Energies, 17(19), Article 4915. https://doi.org/10.3390/en17194915

License

CCBY 4.0

Creative Commons Attribution 4.0 International

This work is openly licensed — share and adapt freely with attribution to the authors and the journal. View license terms ↗

Previous in issue EXPERIMENTAL STUDY OF THE DEAD-TIME COMPENSATION ALGORITHM FOR GAN HEMT BASED INVERTER FOR AC ELECTRIC DRIVES Next in issue HIGH-RESPONSE DC MICROMOTORS: AN ANALYTICAL METHODOLOGY FOR SELECTING MAGNETIC LOADINGS AND ARMATURE ARCHITECTURE BY THE ELECTROMECHANICAL TIME-CONSTANT CRITERION

§ 06 — Related

[1] Boychenko, S., Koshyl, P., Shkilniuk, I., Danilin, O., & Diedov, M. (2026). Ohliad tekhnolohii vyrobnytstva, transportuvannia, zberihannia ta statsionarnoho vykorystannia zelenoho vodniu. Stan i perspektyvy. Systemni doslidzhennia v enerhetytsi, 1(85), 33–51. https://doi.org/10.15407/srenergy2026.01.033

[2] Christensen, A. H. D., Cantisani, N., You, S., & Jørgensen, J. B. (2025). Nonlinear model predictive control for dynamic operation of an alkaline electrolyzer. IFAC-PapersOnLine, 59(6), 433–438. https://doi.org/10.1016/j.ifacol.2025.07.184

[3] Guilbert, D., & Vitale, G. (2019). Dynamic emulation of a PEM electrolyzer by time constant based exponential model. Energies, 12(4), Article 750. https://doi.org/10.3390/en12040750

[4] Kudin, V., & Kolachny, I. (1998). Synthesis of suboptimal nonlinear regulator by immersion method. Journal of Electrical Engineering, 49(1–2), 11–15.

[5] Nagpure, T., & Chen, Z. (2016). Control-oriented modeling of ionic polymer-metal composite enabled hydrogen gas production. International Journal of Hydrogen Energy, 41(16), 6619–6629. https://doi.org/10.1016/j.ijhydene.2016.03.055

[6] Niknezhadi, A., Allué-Fantova, M., Kunusch, C., & Ocampo-Martínez, C. (2011). Design and implementation of LQR/LQG strategies for oxygen stoichiometry control in PEM fuel cells based systems. Journal of Power Sources, 196(9), 4277–4282. https://doi.org/10.1016/j.jpowsour.2010.11.059

[7] Qi, R., Li, J., Lin, J., Song, Y., Wang, J., Cui, Q., Qiu, Y., Tang, M., & Wang, J. (2022). Design of the PID temperature controller for an alkaline electrolysis system with time delays. arXiv. https://doi.org/10.48550/arXiv.2210.00801

[8] Reimann, A., Kohlenbach, P., Röntzsch, L., & Schneider, C. (2025). Development and validation of a quasi-2D electrolysis stack model with a focus on dynamic thermal behavior. International Journal of Hydrogen Energy, 118, 457–471. https://doi.org/10.1016/j.ijhydene.2025.03.225

[9] Yang, J., Zhang, J., Liu, M., Sun, J., & Shangguan, Z. (2024). Dynamic simulation and performance analysis of alkaline water electrolyzers for renewable energy-powered hydrogen production. Energies, 17(19), Article 4915. https://doi.org/10.3390/en17194915

NONLINEAR CURRENT CONTROL OF AN ALKALINE ELECTROLYZER FOR HYDROGEN PRODUCTION, TAKING INTO ACCOUNT THE VOLTAGE LIMITATION OF THE CONVERTER

Abstract

Keywords

References

License

Similar articles in this journal

NUMERICAL SIMULATION OF PHASE CHANGE PROCESSES IN A HORIZONTAL THERMAL ENERGY STORAGE UNIT WITH OPTIMIZED TUBE LAYOUT AND FINNED SURFACES

EXPERIMENTAL STUDY OF THE DEAD-TIME COMPENSATION ALGORITHM FOR GAN HEMT BASED INVERTER FOR AC ELECTRIC DRIVES

HIGH-RESPONSE DC MICROMOTORS: AN ANALYTICAL METHODOLOGY FOR SELECTING MAGNETIC LOADINGS AND ARMATURE ARCHITECTURE BY THE ELECTROMECHANICAL TIME-CONSTANT CRITERION