Zhongliang LI, Professor of Electrical Engineering and Automation

Zhongliang LI

Professor of Electrical Engineering and Automation (Professeur des universités)
SHARPAC team, Energy Department, FEMTO-ST Institute, Université Marie et Louis Pasteur · Belfort, France

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I study how fuel cells and water electrolysers respond to changes in load and how they age. My group combines experiments, physical models and machine learning to diagnose losses and design controls that extend system lifetime.

Curriculum vitae

Academic appointments

  • Since September 2026 · Professor of Electrical Engineering and Automation (Professeur des universités), Université Marie et Louis Pasteur, Belfort. SHARPAC team, Energy Department, FEMTO-ST Institute.
  • September 2022 – August 2026 · Junior Professor Chair (Chaire de professeur junior), UFR STGI, Sciences & Énergies, Belfort. Research on modelling, diagnosis and control of PEM water electrolysers.
  • 2016–2022 · Maître de conférences, Faculty of Sciences, Aix-Marseille Université, LIS laboratory. During this appointment I held a CNRS research delegation at FEMTO-ST (2020–2021).
  • 2016 · Postdoctoral researcher, Université de Franche-Comté, Belfort.
  • 2015–2016 · Postdoctoral researcher, École nationale supérieure de mécanique et des microtechniques (ENSMM), Belfort.

Education

  • 2014 · PhD in Automatic Control, Aix-Marseille Université. Thesis: Data-driven fault diagnosis for PEMFC systems.
  • 2011 · MSc in Electrical Engineering, Tsinghua University, Beijing.
  • 2009 · BSc in Electrical Engineering, Tsinghua University, Beijing.

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Research themes and facilities

Hydrogen systems under changing loads

How can an electrolyser follow a variable power supply without shortening its useful life? My group studies this question in proton exchange membrane (PEM) water electrolysers and the related problem of durability in fuel cells. We combine experiments, models of heat and mass transport, and control theory to connect what can be measured at the stack terminals to what is happening inside a cell.

Measurements, models and control

  • Diagnosis and prognosis. We use impedance spectra, polarisation curves, temperature and magnetic-field measurements to study losses, detect faults and track ageing.
  • Physics-informed modelling. We combine electrochemical and transport equations with experimental data to estimate internal states and predict performance as the load changes.
  • Control and energy management. We study how to share power between stacks, schedule maintenance, and control converters in hydrogen systems, renewable microgrids and hybrid electric vehicles.

Experimental facilities

In Belfort, we test models on PEM electrolyser benches, including the 2 kW PIELIZ platform. Alongside these experiments, the group uses rapid control prototyping, hardware-in-the-loop testing and the FCLAB fuel cell and electrolyser facilities.

Software and models

AlphaPEM. Developed within the ANR DEAL project, with Raphaël Gass as principal contributor, this open-source Python model resolves gas and two-phase water transport across a PEM fuel cell. It can simulate internal water saturation, voltage transients and impedance spectra. Read the software paper.

Fuel cell catalyst degradation. Walid Touil’s doctoral work connects platinum catalyst degradation to stack operation and voltage performance. The model makes it possible to compare how different operating histories affect degradation. Read the modelling paper.

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Projects and grants

PEM electrolyser projects

PEMPIRE · Clean Hydrogen Partnership, 2026–2028. At Université Marie et Louis Pasteur, we study how component ageing affects cell performance and how accelerated tests can support lifetime prediction.

Multi-Hero · ANR PRC 2025, principal investigator. FEMTO-ST and LCPME combine local measurements of membrane electrode assemblies with long-term tests to explain why different parts of an electrolyser age at different rates.

DuraPEME · ANR PRC 2023, principal investigator. We use accelerated stress tests and physics-informed models to connect material degradation to electrolyser lifetime.

DIAMAG · EIPHI BFC, 2024–2027, co-principal investigator. With Stefan Giurgea and colleagues, I am developing magnetic sensors for non-intrusive, real-time electrolyser diagnosis.

 

Other grants and collaborations

  • 2024 · Jeunes Talents France–Chine. Research stay at Huairou National Laboratory, China.
  • 2023–2027 · MFC-DEPLOY (ANR PRC). Scientific lead for FEMTO-ST on post-prognostic decisions for multi-stack fuel cell systems.
  • 2023–2025 · ANR Tremplin-ERC. Fuel cell research, principal investigator.
  • 2022–2026 · Junior Professor Chair. PEM electrolyser modelling and control, principal investigator.

Earlier projects

2021-2024 - Région Sud - AMULTI (Analyse et amélioration de la durabilité des piles à combustible par modélisation et contrôle multi-échelles)  - PI

2020-2024 - ANR JCJC - DEAL (Durability enhancement of fuel cell electric vehicles by exploring multi-level learning based control) - PI

2020 - CNRS cellule énergie PEPS - GIALE (Gestion optimale de l'énergie assistée par l'IA sur le cycle de vie complet du m-CHP à pile à combustible) - PI

2020-2024 - EU H2020 - VPP4ISlands (Virtual Power Plant for Interoperable and Smart isLANDS) - WP co-leader

2019-2022 - Université Grenoble Alpes Du pronostic de la durée de vie de piles à combustibles au pronostic de systèmes énergétiques en réseau - Scientific partner & PhD co-supervisor

2017-2020 - LITTLE HORSE Company (CIFRE contract) - Contrôle et optimisation d’un système hybride nomade à base de sources renouvelables pour la production de l’énergie électrique - Co-PI

2015-2019 - European Commission - GIANTLEAP (Improves Automation of Non-polluting Transportation with Lifetime Extension of Automotive PEM fuel cells) - Participant (postdoc)

2014-2016 - ADEME - PRODIG (PROnostic de Durée de vIe et Garantie de service de systèmes piles à combustible) - Participant (postdoc)

2010-2014 - ANR - DIAPASON 2 (DIAgnostic de Pile à combustible Pour Applications automobiles et Stationaires sans instrumentatiON) - Participant (PhD)

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Research team and alumni

Research group

Postdoctoral researchers

Idriss SINAPAN, "Characterization and multi-modal modelling of bubble effects on PEM electrolyzer performance", began in 2026.09.

Doctoral researchers

Emre KARAYEL, "Multi-scale degradation modelling of next-generation PEM electrolyzers considering BOP dynamics", began in 2026.10.

Baturalp GERS, "Multi-scale in-operando characterizations for electrolyzers", began in 2026.01.

Zhuang TIAN, "Fuel cell modelling and control", began in 2024.11.

Fan YANG, "Magnetic field measurement based diagnosis for electrolyzers", began in 2024.02.

Zhiwen CHEN, "electrolyzer multiphysics modelling", began in 2024.02.

Simone PIEROBON, "Hybrid degradation modelling for PEM electrolyzers", began in 2024.10.

QiAn HE, “Health inspection for energy management and maintenance of multi-stack fuel cell systems”, began in 2024.10.

Feng HAN, “Fuel cell prognostics and energy management”, began in 2023.11.

Graduate students

Vacant.

Former group members

Postdoctoral researchers

(Post-doc) Jian ZUO, “Degradation analysis and lifetime extension for fuel cells applied in heavy-duty vehicles”, 2023.1 - 2026.3.

(Post-doc) Xin WANG, "Development of robust EIS implementable converters for PEM electrolyzers", 2024.7 - 2026.5.

(Post-doc) Islam ZERROUGUI, "AST tests and electrolyzer system control", 2025.10 - 2026.8.

(Post-doc) Zhigen NIE, « Trajectory planning and control for automated connected vehicles », 2019-2021

(Post-doc) Ali BAWAB, "Non-intrusive diagnostics of electrochemical devices through efficient inverse modeling", 2024.12 - 2025.11.

Doctoral researchers

(PhD) Nicolas VIGNAL, “Hybrid multiscale degradation modelling for PEMWEs”, defended in 2025.

(PhD) Islam ZERROUGUI, “Degradation mitigation control for PEMWEs”, defended in 2025.

(PhD) Walid TOUIL, « Durability enhancement control for fuel cells », defended in 2024.

(PhD) Raphaël GASS, « Durability modelling of fuel cells », defended in 2024.

(PhD) Liang GUO, “Health and Energy managements for EVs”, defended 2023.

(PhD) Chu WANG, “Data-driven prognostics for fuel cell systems”, defended in 2023.

(PhD) Jian ZUO, “Development of a Fuel Cell Prognosis Approach in the Context of a Local Energy Grid”, defended in 2022.

(PhD) Majdi SAIDI, “Contrôle et optimisation d’un système hybride nomade à base de sources renouvelables pour la production énergétique”, defended in 2021.

Graduate students

(MEng) Thomas Balmes, "Implementation of control and characterization tools for electrolyzers", 2026.

(MEng) Serdar KUCUK, "Realisation of double loop water circulation system", 2025.

(MEng) Bertrand SAWADOGO, "Contribution to the realization of an electrolyzer test bench", 2024.

(MEng) Loqmane RECHAM, "Realisation of magnetic field sensors for electrolyzer diagnosis", 2024.

(MSc) Xuelu WANG, « Health-aware EMS » defended in 2022.
(MSc) Ossama RAFIK, « Degradation modelling and adaptive EMS » defended in 2022.
(MSc) Jie SUN, « Design of electric circuit for wireless vehicle chargers », defended in 2021.
(MSc) Walid TOUIL, « MPC based EMS for FC hybrid vehicles », defended in 2021.
(MSc) Zakaria BENZINE, « Diagnostic des moteurs électriques à base de données ». 2020.
(MSc) Adrien DE BISSCHOP, Titre : Modélisation et analyse de données d’une électrode d’électromyographie Bipolaire sur sonde uro-dynamique, 2020
(MSc) Moustapha NIANE, “Fault diagnosis for fuel cells using partial model data-driven methods”, Defended in July 2013.
(MSc) Taher MARZOUGUI, “Support Vector Machine and its application for fault diagnosis”, Defended in July 2013.
(MSc) Nasr-eddine ELOBI, “Modeling solar energy potential using eclarement data”, Defended in July 2017.
(MEng) Yuxuan FEI, “AI-Assisted EMS for fuel cell based CHPs”, 2022.
(MEng) Raphael GASS, “Mass transfer modelling for fuel cells”, Defended in September 2021.
(MEng) Fouad BILAL, « Collection des données pour un système micro-cogénération ». 2021.
(MEng) Jérémy ARREOU, « Collection des données pour un système micro-cogénération ». 2021
(MEng) Jiaqi ZHANG, “Design of a hybrid renewable energy system in consideration of its energy management”, Defended in September 2019.
(MEng) Lin JIN, “Co-management of energy generation and load for a hybrid energy system”, Defended in September 2019.
(MEng) Zihan ZHU, “Energy management strategy for fuel cell hybrid vehicles using deep reinforcement learning”, Began in October 2018.
(MEng) Dongrui LYU, “Realizing robust fuel cell prognostic through online model learning”, Began in February 2019.
 

Joining the group

If you are interested in a PhD, postdoctoral position or research visit, consult the group news for advertised opportunities or email Zhongliang Li with your research interests and the type of position you are seeking. For international funding, see Campus France’s guide to doctoral funding. Applicants considering a China Scholarship Council doctorate or research visit can also consult the CSC–Centrale programme and get in touch before preparing an application.

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Publications and talks

Selected reading

Browse the bibliography: Book chapter · Journal articles · Conference papers · Patents · PhD thesis · Master’s thesis · Invited talks

Book chapter

[B1] Z. Li, PEM Electrolyzers: From Modeling to Control. Online scientific book, evolving edition. https://brucelee6.github.io/PEMbook/intro.html

[B2] L. Renato, Z. Li, C. Azzaro-Pantel, “Methodologies in multi-MW capacity sizing and operability infrastructure,” chapter 4 in Hydrogen Infrastructure: Multi-Megawatt Sizing Approaches, Methodologies, and Case Studies, M. Marrony and A. Leon (eds.). In preparation; publication scheduled for July 2026.

[B3] Z. Li, Z. Zheng, F. Gao, “Diagnosis and prognosis of proton exchange membrane fuel cells,” chapter 10 in Electrical Systems 2: From Diagnosis to Prognosis, ISTE/Wiley, 2020. ISBN: 9781786306081.

Journal articles

2014

[J1] Z. Li, R. Outbib, D. Hissel, S. Giurgea, “Data-driven diagnosis of PEM fuel cell: A comparative study,” Control Engineering Practice, vol. 28, pp. 1–12, 2014.

[J2] Z. Li, S. Giurgea, R. Outbib, D. Hissel, “Online Diagnosis of PEMFC by Combining Support Vector Machine and Fluidic Model,” Fuel Cells, vol. 14, pp. 448–456, 2014.

2015

[J3] Z. Li, R. Outbib, S. Giurgea et al., “Fault detection and isolation for Polymer Electrolyte Membrane Fuel Cell systems by analyzing cell voltage generated space,” Applied Energy, vol. 148, pp. 260–272, 2015.

[J4] Z. Li, R. Outbib, S. Giurgea, D. Hissel, “Diagnosis for PEMFC Systems: A Data-Driven Approach with the Capabilities of Online Adaptation and Novel Fault Detection,” IEEE Transactions on Industrial Electronics, vol. 62, no. 8, pp. 5164–5174, 2015.

2016

[J5] Z. Li, R. Outbib, S. Giurgea et al., “Online implementation of SVM based fault diagnosis strategy for PEMFC systems,” Applied Energy, vol. 164, pp. 284–293, 2016.

2018

[J6] Z. Li, Z. Zheng, R. Outbib, “A prognostic methodology for power MOSFETs under thermal stress using echo state network and particle filter,” Microelectronics Reliability, vols. 88–90, pp. 350–354, 2018.

[J7] C. Liu, R. Ma, H. Bai, Z. Li et al., “Hybrid modeling of power electronic system for hardware-in-the-loop application,” Electric Power Systems Research, vol. 163, pp. 502–512, 2018.

[J8] R. Ma, T. Yang, E. Breaz, Z. Li et al., “Data-driven proton exchange membrane fuel cell degradation predication through deep learning method,” Applied Energy, vol. 231, pp. 102–115, 2018.

[J9] R. Ma, E. Breaz, Z. Li et al., “Co-Oxidation Modeling for a Syngas-Supplied Microtubular Solid Oxide Fuel Cell,” IEEE Transactions on Industry Applications, vol. 54, no. 5, pp. 4917–4926, 2018.

[J10] R. Ma, Z. Li, E. Breaz et al., “Numerical Stiffness Analysis for Solid Oxide Fuel Cell Real-time Simulation Applications,” IEEE Transactions on Energy Conversion, vol. 33, no. 4, pp. 1917–1928, 2018.

[J11] C. Liu, X. Guo, R. Ma, Z. Li et al., “A System-Level FPGA-Based Hardware-in-the-Loop Test of High-Speed Train,” IEEE Transactions on Transportation Electrification, vol. 4, no. 4, pp. 912–921, 2018.

2019

[J12] Z. Li, R. Outbib, S. Giurgea, D. Hissel, “Fault diagnosis for PEMFC systems in consideration of dynamic behaviors and spatial inhomogeneity,” IEEE Transactions on Energy Conversion, vol. 34, no. 1, pp. 3–11, 2019.

[J13] C. Liu, R. Ma, H. Bai, Z. Li, F. Gechter, F. Gao, “FPGA-Based Real-time Simulation of High-Power Electronic System with Nonlinear IGBT Characteristics,” IEEE Journal of Emerging and Selected Topics in Power Electronics, vol. 7, no. 1, pp. 41–51, 2019.

[J14] Z. Li, R. Outbib, S. Giurgea et al., “Fault diagnosis for fuel cell systems: A data-driven approach using high-precise voltage sensors,” Renewable Energy, vol. 135, pp. 1435–1444, 2019.

[J15] Z. Li, C. Cadet, R. Outbib, “Diagnosis for PEMFC based on magnetic measurements and data-driven approach,” IEEE Transactions on Energy Conversion, vol. 34, no. 2, pp. 964–972, 2019.

[J16] R. Ma, Z. Li, E. Breaz et al., “Data-Fusion Prognostics of Proton Exchange Membrane Fuel Cell Degradation,” IEEE Transactions on Industry Applications, vol. 55, no. 4, pp. 4321–4331, 2019.

[J17] Z. Li, Z. Zheng, L. Xu, X. Lu, “A review of the applications of fuel cells in microgrids: opportunities and challenges,” BMC Energy, vol. 1, 2019.

2020

[J18] Z. Li, Z. Zheng, R. Outbib, “Adaptive prognostic of fuel cells by implementing ensemble Echo State Networks in time varying model space,” IEEE Transactions on Industrial Electronics, vol. 67, no. 1, pp. 379–389, 2020.

[J19] Z. Nie, Z. Li, W. Wang et al., “Gain-scheduling control of dynamic lateral lane change for automated and connected vehicles based on multi-points preview,” IET Intelligent Transport Systems, vol. 14, no. 10, pp. 1338–1349, 2020.

[J20] Y. Xie, J. Zou, Z. Li, F. Gao, C. Peng, “A novel deep belief network and extreme learning machine based performance degradation prediction method for proton exchange membrane fuel cell,” IEEE Access, vol. 8, pp. 176661–176675, 2020.

2022

[J21] C. Wang, Z. Li, R. Outbib et al., “Symbolic deep learning based prognostics for dynamic operating proton exchange membrane fuel cells,” Applied Energy, vol. 305, 117918, 2022.

[J22] M. Yue, Z. Li, R. Roche et al., “Degradation identification and prognostics of proton exchange membrane fuel cell under dynamic load,” Control Engineering Practice, vol. 118, 104959, 2022.

[J23] C. Wang, Z. Li, R. Outbib et al., “A novel long short-term memory networks-based data-driven prognostic strategy for proton exchange membrane fuel cells,” International Journal of Hydrogen Energy, vol. 47, no. 18, pp. 10395–10408, 2022.

[J24] M. Saidi, Z. Li, S. Ben Elghali, R. Outbib, “Realization of the optimal sizing of local hybrid photovoltaic and wind energy systems with load scheduling capacity,” International Journal of Energy Research, 2022.

[J25] J. Zuo, C. Cadet, Z. Li, et al., “Post-prognostics decision-making strategy for load allocation on a stochastically deteriorating multi-stack fuel cell system,” Journal of Risk and Reliability, 2022.

[J26] C. Wang, M. Dou, Z. Li*, et al., “A fusion prognostics strategy for fuel cells operating under dynamic conditions,” eTransportation, vol. 12, 100166, 2022. DOI: 10.1016/j.etran.2022.100166.

[J27] H. Wang, A. Gaillard, Z. Li, R. Roche, D. Hissel, “Multiple-Fuel Cell Module Architecture Investigation: A Key to High Efficiency in Heavy-Duty Electric Transportation,” IEEE Vehicular Technology Magazine, vol. 17, no. 3, pp. 94–103, 2022. DOI: 10.1109/MVT.2022.3179801.

2023

[J28] C. Wang, M. Dou, Z. Li*, R. Outbib, D. Zhao, J. Zuo, Y. Wang, B. Liang, P. Wang, “Data-driven prognostics based on time-frequency analysis and symbolic recurrent neural network for fuel cells under dynamic load,” Reliability Engineering & System Safety, vol. 233, 109123, 2023. DOI: 10.1016/j.ress.2023.109123.

[J29] L. Guo, Z. Li*, R. Outbib, F. Gao, “Function approximation reinforcement learning of energy management with the fuzzy REINFORCE for fuel cell hybrid electric vehicles,” Energy & AI, vol. 13, 100246, 2023. DOI: 10.1016/j.egyai.2023.100246.

[J30] Z. Nie, Z. Li, W. Wang et al., “Robust gain-scheduling control of dynamic lateral obstacle avoidance for connected and automated vehicles,” International Journal of Automotive Technology, vol. 24, no. 1, pp. 63–78, 2023. DOI: 10.1007/s12239-023-0007-8.

2024

[J31] J. Zuo, N. Yousfi Steiner, Z. Li*, D. Hissel, “Health management review for fuel cells: Focus on action phase,” Renewable and Sustainable Energy Reviews, vol. 201, 114613, 2024. DOI: 10.1016/j.rser.2024.114613.

[J32] Y. Ao, Z. Li, S. Laghrouche, D. Depernet, D. Candusso, K. Zhao, “Stack-level diagnosis of proton exchange membrane fuel cell by the distribution of relaxation times analysis of electrochemical impedance spectroscopy,” Journal of Power Sources, vol. 603, 234420, 2024. DOI: 10.1016/j.jpowsour.2024.234420.

[J33] R. Gass, Z. Li*, R. Outbib, S. Jemei, D. Hissel, “A Critical Review of Proton Exchange Membrane Fuel Cells Matter Transports and Voltage Polarisation for Modelling,” Journal of The Electrochemical Society, vol. 171, no. 3, 034511, 2024. DOI: 10.1149/1945-7111/ad305a.

[J34] J. Zuo, C. Cadet, Z. Li*, C. Bérenguer, R. Outbib, “A deterioration-aware energy management strategy for the lifetime improvement of a multi-stack fuel cell system subject to a random dynamic load,” Reliability Engineering & System Safety, vol. 241, 109660, 2024. DOI: 10.1016/j.ress.2023.109660.

2025

[J35] J. Zuo, N. Yousfi Steiner, Z. Li*, D. Hissel, “Interpreting full-frequency impedance spectrum for PEM electrolyzers: Distribution of relaxation times-based modeling,” Applied Energy, vol. 394, 126185, 2025. DOI: 10.1016/j.apenergy.2025.126185.

[J36] C. Wang, S. Zhang, P. Wang, Z. Chen, Z. Li, R. Outbib, Z. Lv, X. Li, M. Dou, B. Liang, “Reversible degradation detection-identification-avoidance and deep-learning co-driven fuel cell remaining useful life prediction,” International Journal of Hydrogen Energy, vol. 145, 2025. DOI: 10.1016/j.ijhydene.2025.05.422.

[J37] J. Zuo, N. Yousfi Steiner, Z. Li*, D. Hissel, “Quantitative investigation of internal polarization in a proton exchange membrane water electrolyzer stack using distribution of relaxation times,” Applied Energy, vol. 386, 125543, 2025. DOI: 10.1016/j.apenergy.2025.125543.

[J38] K. Jiang, H. Jiang, Z. Liang, L. Zhang, G. Lu, Z. Li*, Z. Liu, “An automated, intelligent and efficient approach to design flow fields of proton exchange membrane fuel cells: A concept for future,” Chemical Engineering Journal, vol. 523, 168164, 2025. DOI: 10.1016/j.cej.2025.168164.

[J39] I. Zerrougui, Z. Li*, D. Hissel, “Physics-Informed Neural Network for modeling and predicting temperature fluctuations in proton exchange membrane electrolysis,” Energy & AI, vol. 20, 100474, 2025. DOI: 10.1016/j.egyai.2025.100474.

[J40] Y. Sun, H. Wang, R. Li, B. Hu, J. Fang, Y. Lei, Z. Li, D. Hissel, “A Low-Cost High-Accuracy Online Electrochemical Impedance Spectroscopy Measurement Strategy for Fuel Cell Electric Vehicle Application,” IEEE Transactions on Instrumentation and Measurement, vol. 74, 9003512, pp. 1–12, 2025. DOI: 10.1109/TIM.2025.3557105.

[J41] I. Zerrougui, Z. Li*, D. Hissel, “Investigating bubble impacts on PEM electrolysis performance through enhanced multiphysics modeling,” International Journal of Hydrogen Energy, vol. 98, 2025. DOI: 10.1016/j.ijhydene.2024.12.017.

[J42] J. Zuo, N. Yousfi Steiner, Z. Li*, C. Cadet, C. Bérenguer, D. Hissel, “Optimal Postprognostics Decision-Making for Multistack Fuel Cells in Transportation: Toward Joint Load Allocation and Maintenance Scheduling,” IEEE Transactions on Transportation Electrification, vol. 11, no. 1, pp. 2456–2466, 2025. DOI: 10.1109/TTE.2024.3423404.

[J43] I. Zerrougui, Z. Li*, D. Hissel, “Toward optimal operations of long-lifetime PEM electrolysis: Degradation mechanisms, modeling, diagnostics, and control,” International Journal of Hydrogen Energy, vol. 193, 152297, 2025. DOI: 10.1016/j.ijhydene.2025.152297.

[J44] W. Touil, Z. Li*, R. Outbib, D. Hissel, S. Jemei, “A system-level modeling framework for predicting Pt catalyst degradation in proton exchange membrane fuel cells,” Journal of Power Sources, vol. 625, 235628, 2025. DOI: 10.1016/j.jpowsour.2024.235628.

[J45] R. Gass, Z. Li*, R. Outbib, S. Jemei, D. Hissel, “An advanced 1D physics-based model for PEM hydrogen fuel cells with enhanced overvoltage prediction,” International Journal of Hydrogen Energy, vol. 97, 2025. DOI: 10.1016/j.ijhydene.2024.11.374.

[J46] R. Gass, Z. Li*, R. Outbib, S. Jemei, D. Hissel, “AlphaPEM: An open-source dynamic 1D physics-based PEM fuel cell model for embedded applications,” SoftwareX, vol. 29, 102002, 2025. DOI: 10.1016/j.softx.2024.102002.

[J47] J. Zuo, N. Yousfi Steiner, Z. Li*, D. Hissel, “Degradation root cause analysis of PEM fuel cells using distribution of relaxation times,” Applied Energy, vol. 378, 124762, 2025. DOI: 10.1016/j.apenergy.2024.124762.

[J48] J. Zuo, N. Yousfi Steiner, Z. Li*, C. Cadet, C. Bérenguer, D. Hissel, “Reinforcement learning-based maintenance scheduling for a stochastic deteriorating fuel cell considering stack-to-stack heterogeneity,” Reliability Engineering & System Safety, vol. 256, 110700, 2025. DOI: 10.1016/j.ress.2024.110700.

2026

[J49] X. Wang, Z. Li*, Z. Zheng, D. Hissel, “A dynamic electrochemical impedance spectroscopy extraction method for PEM water electrolyzers considering time resolution”. Applied Energy, 426, 128647. DOI: 10.1016/j.apenergy.2026.128647

[J50] J. Zuo, N. Yousfi Steiner, Z. Li*, H. Lv, D. Yang, D. Hissel, “Quantifying degradation in hydrogen fuel cells: A holistic approach combining in situ and ex situ characterizations,” Renewable Energy, vol. 263, 125515, 2026. DOI: 10.1016/j.renene.2026.125515.

[J51] I. Zerrougui, Z. Li, D. Hissel, “Self-loop physics-informed neural network for model predictive control of PEM electrolyzers,” Journal of Process Control, vol. 161, 103707, 2026. DOI: 10.1016/j.jprocont.2026.103707.

[J52] R. Louli, S. Giurgea, I. Salhi, A. Badji, S. Laghrouche, Z. Li, A. Djerdir, “Optimized multiphysics model for a Proton Exchange Membrane Water Electrolyzer,” Renewable Energy, vol. 256, 124452, 2026. DOI: 10.1016/j.renene.2025.124452.

[J53] Z. Tian, Z. Li*, R. Outbib, D. Zhou, “Real-Time Multiphysics Modeling of Automotive Fuel Cells: A Method Based on Multilevel Cyclic Iteration and Orthogonal List-Conjugate Gradient,” IEEE Transactions on Transportation Electrification, vol. 12, no. 1, pp. 1814–1825, 2026. DOI: 10.1109/TTE.2025.3634271.

[J54] J. Zuo, N. Yousfi Steiner, X. Wang, Z. Li*, D. Hissel, "Electrochemical impedance spectroscopy for proton exchange membrane fuel cells: From implementation to application", Applied Energy, vol. 427, Part F, 2027. https://doi.org/10.1016/j.apenergy.2026.129127.

Conference papers

International conferences

[CI1] Z. Li, X. Sun, J. Chai, “Proportional power sharing control for parallel-connected inverters,” Electric Utility Deregulation and Restructuring and Power Technologies (DRPT), Qingdao, pp. 1647–1651, 2011.

[CI2] Z. Li, R. Outbib, S. Giurgea, D. Hissel, “Diagnosis of PEMFC by using statistical analysis,” Integrated Modeling and Analysis in Applied Control and Automation (IMAACA), Vienna, pp. 191–198, 2012.

[CI3] Z. Li, S. Giurgea, R. Outbib, D. Hissel, “Online Diagnosis of PEMFC by Combining Support Vector Machine and Fluidic Model,” International Conference on Fundamentals and Developments of Fuel Cells (FDFC), Karlsruhe, paper 069, 2013.

[CI4] Z. Li, R. Outbib, D. Hissel, S. Giurgea, “Online diagnosis of PEMFC by analyzing individual cell voltages,” European Control Conference (ECC), Zurich, pp. 2439–2444, 2013.

[CI5] Z. Li, R. Outbib, D. Hissel, S. Giurgea, “Diagnosis of PEMFC by using data-driven parity space strategy,” European Control Conference (ECC), Strasbourg, pp. 1268–1273, 2014.

[CI6] Z. Li, S. Giurgea, R. Outbib, D. Hissel, “Fault diagnosis and novel fault type detection for PEMFC system based on Spherical-Shaped Multiple-class Support Vector Machine,” Advanced Intelligent Mechatronics (AIM), Besançon, pp. 1628–1633, 2014.

[CI7] Z. Li, S. Giurgea, R. Outbib, D. Hissel, “Fault detection and isolation of PEMFC system: a classification approach,” International Discussion on Hydrogen Energy and Applications (IDHEA), Nantes, p. 49, 2014.

[CI8] Z. Li, R. Outbib, S. Giurgea, D. Hissel, S. Jemei, A. Giraud, S. Rosini, “Online implementation of SVM based fault diagnosis strategy for PEMFC systems,” International Conference on Fundamentals and Developments of Fuel Cells (FDFC), Toulouse, paper 048, 2015.

[CI9] Z. Li, S. Jemei, R. Gouriveau et al., “Remaining useful life estimation for PEMFC in dynamic operating conditions,” Vehicular Power and Propulsion Conference (VPPC), Hangzhou, pp. 1–6, 2016.

[CI10] Z. Li, R. Outbib, “PHM oriented behavior modeling for PEM fuel cell systems via Delayed Feedback Reservoir Computing Model,” Integrated Modeling and Analysis in Applied Control and Automation (IMAACA), Barcelona, 2017.

[CI11] Z. Li, S. Ben Elghali, R. Outbib, “Energy management for hybrid energy storage systems: a comparison of current tracking control methods,” 43rd Annual Conference of the IEEE Industrial Electronics Society (IECON), Beijing, pp. 7128–7133, 2017.

[CI12] M. Saidi, Z. Li, R. Outbib et al., “Realizing optimum design of a hybrid renewable energy system using multi-objective evolutionary algorithm,” Integrated Modeling and Analysis in Applied Control and Automation (IMAACA), Budapest, 2018.

[CI13] Z. Li, Z. Zheng, R. Outbib, “A Prognostic Methodology for Power MOSFETs Under Thermal Stress Using Echo State Network and Particle Filter,” 29th European Symposium on Reliability of Electron Devices, Failure Physics and Analysis (ESREF), Aalborg, 2018.

[CI14] M. Saidi, S. Ben Elghali, Z. Li, R. Outbib et al., “Optimal Sizing of Mobile Hybrid Off-Grid Multi-Sources Installation,” 45th Annual Conference of the IEEE Industrial Electronics Society (IECON), Lisbon, pp. 2434–2439, 2019.

[CI15] M. Saidi, Z. Li, S. Ben Elghali, R. Outbib, “Optimal Sizing of hybrid grid-connected energy system with demand side scheduling,” 45th Annual Conference of the IEEE Industrial Electronics Society (IECON), Lisbon, pp. 2209–2214, 2019.

[CI16] J. Zuo, C. Cadet, Z. Li et al., “Post-prognostics decision making for multi-stacks fuel cell system based on a load-dependent degradation model,” Fifth European Conference of the Prognostics and Health Management Society (PHMe), online, 2020.

[CI17] M. Yue, Z. Li, R. Roche et al., “A Feature-based Prognostics Strategy For PEM Fuel Cell Operated Under Dynamic Conditions,” Prognostics and Health Management Conference (PHM), Besançon, pp. 122–127, 2020. DOI: 10.1109/PHM-Besancon49106.2020.00026.

[CI18] C. Wang, Z. Li, R. Outbib et al., “Proton Exchange Membrane Fuel Cells Prognostic Strategy Based on Navigation Sequence Driven Long Short-term Memory Networks,” 46th Annual Conference of the IEEE Industrial Electronics Society (IECON), Singapore, pp. 3969–3974, 2020.

[CI19] C. Wang, Z. Li, R. Outbib et al., “A Hybrid Prognostics Approach for Proton Exchange Membrane Fuel Cells under Dynamic Operating Conditions,” 34th International Electric Vehicle Symposium and Exhibition (EVS34), Nanjing, 2021.

[CI20] J. Zuo, C. Cadet, Z. Li et al., “Post-Prognostics Decision Making Strategy to Manage the Economic Lifetime of a Two-Stack PEMFC System,” Annual Reliability and Maintainability Symposium (RAMS), online, pp. 1–7, 2021.

[CI21] L. Guo, Z. Li, R. Outbib, “Reinforcement Learning based Energy Management for Fuel Cell Hybrid Electric Vehicles,” 47th Annual Conference of the IEEE Industrial Electronics Society (IECON), online, pp. 1–6, 2021.

[CI22] J. Zuo, C. Cadet, Z. Li et al., “A dynamic load allocation strategy for a stochastically deteriorating multi-stack fuel cell system,” European Safety and Reliability Association, 2022.

[CI23] L. Guo, Z. Li, R. Outbib, “Fuzzy REINFORCE: A Fuzzy Policy Gradient Reinforcement Learning based Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles,” 3rd International Conference on Energy and AI, Belfort, 2022.

[CI24] J. Zuo, C. Cadet, Z. Li, et al., Fuel Cell Stochastic Deterioration Modeling for Energy Management in a Multi-stack System, 2022 13th International Conference on Reliability, Maintainability, and Safety (ICRMS), Kowloon, Hong Kong, 2022. DOI: 10.1109/ICRMS55680.2022.9944566.

[CI25] W. Touil, Z. Li, R. Outbib, et al., Model predictive control energy management strategy of fuel cell hybrid electric vehicle, IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society, Brussels, Belgium, 2022. DOI: 10.1109/IECON49645.2022.9968429.

[CI26] L. Guo, Z. Li and R. Outbib, Fuzzy Rule Value Reinforcement Learning based Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles, IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society, Brussels, Belgium, 2022. DOI: 10.1109/IECON49645.2022.9968966.

[CI27] C. Wang, Z. Li, R. Outbib et al., A hybrid method for remaining useful life prediction of fuel cells under variable loads, 2022 10th International Conference on Systems and Control (ICSC), Marseille, France, 2022. DOI: 10.1109/ICSC57768.2022.9993918.

[CI28] L. Guo, Z. Li and R. Outbib, A Lifetime Extended Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles via Self-Learning Fuzzy Reinforcement Learning, 2022 10th International Conference on Systems and Control (ICSC), Marseille, France, 2022. DOI: 10.1109/ICSC57768.2022.9993916.

[CI29] L. Guo, Z. Li and R. Outbib, An Unbiased Fuzzy Double Q-Learning based Energy Management for Fuel Cell Hybrid Electric Vehicles, 2023 IEEE 32nd International Symposium on Industrial Electronics (ISIE), 2023. DOI: 10.1109/ISIE51358.2023.10227988.

[CI30] W. Touil, Z. Li, R. Outbib et al. , A dual-scale modelling framework for predicting catalyst degradation in Polymer Electrolyte Fuel Cells, 9th International Conference on Fundamentals & Development of Fuel Cells FDFC2023.

[CI31] R. Gass, Z. Li, R. Outbib, et al., A dynamic 1D+1D physical model of the PEMFC hydrogen stack for embedded systems, 9th International Conference on Fundamentals & Development of Fuel Cells FDFC2023.

[CI32] I. Zerrougui, Z. Li, D. Hissel, Comprehensive Modeling and Analysis of Bubble Dynamics and its Impact on PEM Water Electrolysis Performance, 9th International Conference on Fundamentals & Development of Fuel Cells FDFC2023.

[CI33] R. Gass, Z. Li, A 1-D 2-phase control-oriented mass transfer model of PEM fuel cells, 7th CAA International Conference on Vehicular Control and Intelligence (CVCI2023), Changsha, 2023. DOI: 10.1109/CVCI59596.2023.10397331.

[CI34] V. Natesan, R. Succoja and Z. Li, "Optimization and Performance Evaluation of Open Cathode Multi-Stack PEM Fuel Cell Systems," 2024 IEEE Transportation Electrification Conference and Expo (ITEC), Chicago, IL, USA, 2024. DOI: 10.1109/ITEC60657.2024.10599008.

[CI35] W. Touil, Z. Li, R. Outbib, et al., Control oriented modeling of integrated catalyst and membrane degradation in PEM fuel cells, 2024 IEEE Transportation Electrification Conference and Expo (ITEC), Chicago, IL, USA, 2024. DOI: 10.1109/ITEC60657.2024.10598861.

[CI36] L. Kumar, J. Chen, X. Li and Z. Li, Air Supply Control for PEM Fuel Cells Under Hamiltonian Framework: A Segmentation Approach, 2024 3rd

[CI37] Z. Li, J. Chen, Comparative study of reinforcement learning and optimal control based energy management strategies for fuel cell vehicles, 3rd Conference on Fully Actuated System Theory and Applications (FASTA), Shenzhen, China, 2024.

[CI38] S. Zhang, C. Wang, Z. Chen, Z. Lv, X. Li, R. Di, Z. Li, P. Wang, "A Reversible Degradation Adaptive Avoidance-Driven Echo State Network: Application to Fuel Cell Prognostics," 2024 IEEE 7th International Electrical and Energy Conference (CIEEC), Harbin, China, 2024. DOI: 10.1109/CIEEC60922.2024.10583806.

[CI39] I. Zerrougui, Z. Li and D. Hissel, "Robust Thermal Management in PEM Electrolysis: A Two-Loop Control Strategy," 2025 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), Hangzhou, China, 2025. DOI: 10.1109/AIM64088.2025.11175797.

[CI40] Q. He, Z. Li, N. Yousfi-Steiner et al., "Dual-scale 1-D model for degradation assessment in proton exchange membrane fuel cells," 2025 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), Hangzhou, China, 2025. DOI: 10.1109/AIM64088.2025.11175738.

[CI41] N. Vignal, Z. Li, B. Latour, D. Hissel, “Physics-based Electrochemical Model of a Proton Exchange Membrane Water Electrolyzer,” 11th IFAC/IEEE International Conference on Control, Decision and Information Technologies (CoDIT 2025) / Split, Croatia.

[CI42] R. Tittarelli, S. Pierobon, Z. Li, U. Razafison, Instationnary multiphysic 1D numerical method for water electrolysers, The European Conference on Numerical Mathematics and Advanced Applications (ENUMATH) 2025.

[CI43] Z. Tian, Z. Li , R. Outbib, et al., Two-Dimensional Degradation Model of PEM Fuel Cells Considering Pt Catalyst Evolution for Health-Aware Energy Management, IECON 2025 –51st Annual Conference of the IEEE, 2025.

National conferences

[CN1] R. Gass, Z. Li, R. Outbib et al., Un modèle physique 1D+ 1D dynamique de la pile à hydrogène PEMFC pour des systèmes embarqués, 3ème Réunion Plénières de la Fédération Hydrogène (FRH2) du CNRS 2023. [Conference communication.]

[CN2] W. Touil, Z. Li, R. Outbib, et al. , A Dual-Scale Modeling Framework for Predicting Platinum Degradation in Polymer Electrolyte Fuel Cells, 3ème Réunion Plénières de la Fédération Hydrogène (FRH2) du CNRS 2023. [Conference communication.]

[CN3] R. Gass, Z. Li, R. Outbib, et al., AlphaPEM: un modèle de pile à combustible PEM 1D dynamique et open-source pour des applications embarquées, 4ème Réunion Plénières de la Fédération Hydrogène (FRH2) du CNRS 2024. [Conference communication.]

[CN4] N. Vignal, Z. Li, B. Latour, D. Hissel, Modélisation multiphysique d’un stack d’un électrolyseur de type PEM, 4ème Réunion Plénières de la Fédération Hydrogène (FRH2) du CNRS 2024. [Conference communication.]

[CN5] N. Vignal, Z. Li, B. Latour, D. Hissel, “Modélisation et validation basée sur la physique d’un stack d’un électrolyseur de type PEM,” 6ème Symposium de Génie Electrique (SGE 2025) / Toulouse, France. [Conference communication.]

[CN6] Q. He, Z. Li, N.Y. Steiner, et al., Dual-scale modeling of proton-exchange membrane fuel cell for degradation assessment, 6ème Symposium de Génie Electrique (SGE 2025) / Toulouse, France. [Conference communication.]

[CN7] S. Pierobon, R. Tittarelli, Z. Li, Multiscale and Multiphysics 1D Modeling of Polymer Electrolyte Membrane Water Electrolysers, 6ème Symposium de Génie Electrique (SGE 2025) / Toulouse, France. [Conference communication.]

[CN8] S. Pierobon, R. Tittarelli, Z. Li, F. Druart, “Multiscale and Multiphysics 1D Modeling of a PEM Water Electrolyser,” 5ème Réunion Plénières de la Fédération Hydrogène (FRH2) du CNRS 2025. [Conference communication.]

[CN9] Q. He, Z. Li, F. Harel, et al., “1-D fuel cell model identification and observer design,” 5ème Réunion Plénières de la Fédération Hydrogène (FRH2) du CNRS 2025. [Conference communication.]

Patents


[P1] X. Wang, Z. Li, Z. Zheng, D. Hissel, “A novel multiphase DC-DC converter with online electrochemical impedance spectroscopy function.” Positive patentability assessment.

[P2] S. Faivre, F. Gustin, D. Hissel, F. Harel, Z. Li, “Method and system for diagnosing the operating state of an electrochemical system in real-time, and electrochemical system incorporating this diagnostic system.” FR3067124A1 / WO2018220115A1, 2018.

Technical tutorials

[T1] R. Gass, Z. Li, R. Outbib, S. Jemei, D. Hissel, “Spectromètre d’impédance à faible coût pour caractériser des dispositifs électrochimiques,” Techniques de l’Ingénieur, Innovations en énergie. 2017, vol. TH10, n° RE193 (link). 

[T2] X. Wang, Z. Li*, Z. Zheng, D. Hissel, “Spectromètre d’impédance à faible coût pour caractériser des dispositifs électrochimiques,” Techniques de l’Ingénieur, 2026 (link). 

PhD thesis


Data-driven fault diagnosis for PEMFC systems (PhD thesis, PDF).

Master’s thesis


Research on the control strategy of parallel-connected inverters in a microgrid.

Invited talks

[I1] “Data-driven diagnosis and control methodologies and applications in fuel cells”, International excellent young-scholar WEISHI forum, Invited by Beihang University, 05/2017, Beijing, China.

[I2] “Control of fuel cell systems: issues and solutions”, Seminar in School of Astronautics, Harbin Institute of Technology, Invited by Prof. Ligang WU, 10/2017, Harbin, China.

[I3] “Control of fuel cell systems: issues and solutions”, International excellent young-scholar TELI forum, Invited by Beijing Institute of Technology, 11/2017, Beijing, China.

[I4] “Data-driven fault diagnosis and control of fuel cell systems”, Beijing Jiaotong University, Invited by Prof. Zhongsheng HOU, 11/2017, Beijing, China.

[I5] “Modeling and control of fuel cell systems”, Seminar in Northwest Polytechnical University, Invited by Prof. Dongdong ZHAO, 04/2019, Xi’an, China.

[I6] “Data-driven fault diagnosis and prognosis of fuel cell systems”, Seminar in South China University of Technology, Invited by Department of Electrical Engineering, 04/2019, Guangzhou, China.

[I7] “Data-driven fault diagnosis and prognosis of fuel cell systems”, Seminar in State Key Lab of Industrial Control Tech., Zhejiang University, Invited by Prof. Jian CHEN, 04/2019, Hangzhou, China.

[I8] “Diagnosis and prognosis of complex systems”, Seminar in Laboratory of Health Services and Reliability of Mechatronic Systems in Beihang University, Invited by Prof. Shaoping WANG, 12/2019, Beijing, Chine.

[I9] “Energy management strategy for hybrid electric vehicles”, Webinar in Zhengzhou University, invited by Prof. Chen LIU, 08/2020, Online.

[I10] “System-level fuel research on fuel cell durability”, Seminar in lab MADIREL of Aix-Marseille University, Invited by Prof. Phillipe KNAUTH, 01/2020, Marseille France.

[I11] “Diagnosis, prognosis and fault tolerant control for fuel cell systems”, Tutorial (4 hours) in the 45th Annual Conf. of the IEEE IES, 10/2020, Online.

[I12] "Prognostics and health management (PHM) for fuel cell systems", panel talk, 5th European Conference of the PHM Society, virtual conference.

[I13] "Reinforcing fuel cell performance by applying AI methods", invited seminar, AI Days AMU-IBM” session for “green mobility”, Marseille, France 

[I14] "Hydrogen and fuel cell technology in Europe", plenary presentation,1st Global online forum of Overseas Automotive Engineers, online. 

[I15] “AI-guided energy management for fuel cell micro-CHPs”, 2021 edition of the CNRS energy symposium, Invited by CNRS Energy cell, 02/2021, Paris, France.

[I16] “AI-assisted prognostics and health management for fuel cells”, Seminar in CNRS, Invited by Dr. Liang LIU from LCPME, 30/09/2022, Nancy, France.

[I17] "Multiscale degradation modelling for fuel cell catalyst degradation", Invited Seminar at China’s National Huairou Laboratory, 08/2023, Beijing, China.

[I18] "Hydrogen and fuel cell industries: status and perspectives", Plenary presentation Tsinghua Alumni annual conference, 10/2024, Laussane, Switzerland. 

[I20] "Hydrogen and fuel cell industries: status and perspectives", Plenary presentation Tsinghua Alumni annual conference, 10/2024, Laussane, Switzerland. 

[I21] "Energy management strategy for hybrid electric vehicles", Short course in IEEE Transportation Electrification Conference (ITEC 2024).

[I22] "AI for fuel cell fault diagnosis and prognosis", Short course in China’s National Huairou Lab’ summer school, 08/2024, Beijing, China.

[I23] "How to develop a fuel cell multiphysics model for control",  Panel talk, 1st Applied Energy Discovery Workshops (APEN Disco) (~100 participants), 09/2025, Cardiff, UK. 

[I24] "Modelling to support control development for hydrogen fuel cells", Invited Seminar at Southern University of Science and Technology (SUSTech), 07/2025, Shenzhen, China.

[I25] "Hydrogen production and use in French Polynesia", Plenary talk, 1st Workshop on “Energetic Transition in French Polynesia”, 09/2025, French Polynesia.

[I26] "Control-oriented modelling for electrolyzers and fuel cells", Invited seminar, 07/2026, Jilin University, Jilin, China.

[I27] "Control-oriented modelling for electrolyzers and fuel cells", Invited seminar, 07/2026, Xi'An Technology University, Xi'An, China.

[I28] "Multiscale modelling for electrolyzers and fuel cells", Invited seminar, 10/2026, Chrono-environnement Lab, Besançon, France.

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Contact and visiting address

Zhongliang Li
SHARPAC team, Energy Department, FEMTO-ST Institute
13 rue Ernest Thierry-Mieg, 90010 Belfort Cedex, France

zhongliang.li@umlp.fr · zhongliang.li@femto-st.fr
Former university address: zhongliang.li@univ-fcomte.fr

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