Regenerative Fuel Cell-Battery-Supercapacitor Hybrid Power System Modeling and Improved Rule-Based Energy Management for Vehicle Application
Publication: Journal of Energy Engineering
Volume 146, Issue 6
Abstract
This paper focuses on a proton-exchange membrane (PEM) fuel cell/electrolyzer-based regenerative hybrid power system modeling and energy management for automotive application. In the regenerative hybrid power system, the fuel cell acts as the main power, and the battery, supercapacitor, and electrolyzer consist of a hybrid energy storage system (HESS) to provide and/or reclaim the extra power. To effectively distribute the hybrid power, the load power demand of the automobile is handled by using the wavelet transform based on the power change rate. The supercapacitor copes with the high power change rate load demand, and the low-slope portion is balanced by the fuel cell/electrolyzer and battery. To reduce the fuel consumption online, an improved rule-based energy management strategy (EMS) depending on dynamic programming (DP) allocation of fuel cell power and battery state of charge (SOC) is developed, and an electrolyzer operation strategy is also designed. The numerical simulation is implemented to test the proposed rule-based EMS, and the results indicate that the real-time control keeping 93.8% fuel consumption performance compared with the off-line global optimization solution in a given driving cycle.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
Some or all data, models, or code generated or used during the study are proprietary or confidential in nature and may only be provided with restrictions (the models of the PEM fuel cell and PEM electrolyzer are restricted).
Acknowledgments
This work was supported by the China Postdoctoral Science Foundation (Grant No. 2019M650505), the Qishan Scholar Program of Fuzhou University (Grant No. XRC-1643), and the Open Project Program of Key Laboratory of Industrial Automation Control Technology and Information Processing (Fuzhou University) (Grant No. 2018-FZU-KF10).
References
Abdin, Z., C. J. Webb, and E. M. Gray. 2015. “Modelling and simulation of a proton exchange membrane (PEM) electrolyser cell.” Int. J. Hydrogen Energy 40 (39): 13243–13257. https://doi.org/10.1016/j.ijhydene.2015.07.129.
Ahmadi, S., S. M. T. Bathaee, and A. H. Hosseinpour. 2018. “Improving fuel economy and performance of a fuel-cell hybrid electric vehicle (fuel-cell, battery, and ultra-capacitor) using optimized energy management strategy.” Energy Convers. Manage. 160 (Mar): 74–84. https://doi.org/10.1016/j.enconman.2018.01.020.
Bai, Y., H. He, J. Li, S. Li, Y. X. Wang, and Q. Yang. 2019. “Battery anti-aging control for a plug-in hybrid electric vehicle with a hierarchical optimization energy management strategy.” J. Cleaner Prod. 237 (Jan): 117841. https://doi.org/10.1016/j.jclepro.2019.117841.
Bambang, R. T., A. S. Rohman, C. J. Dronkers, R. Ortega, and A. Sasongko. 2014. “Energy management of fuel cell/battery/supercapacitor hybrid power sources using model predictive control.” IEEE Trans. Ind. Inf. 10 (4): 1992–2002. https://doi.org/10.1109/TII.2014.2333873.
Chen, J., and Q. Song. 2018. “A decentralized dynamic load power allocation strategy for fuel cell/supercapacitor-based APU of large more electric vehicles.” IEEE Trans. Ind. Electron. 66 (2): 865–875. https://doi.org/10.1109/TIE.2018.2833031.
Chitsaz, A., M. A. Haghghi, and J. Hosseinpour. 2019. “Thermodynamic and exergoeconomic analyses of a proton exchange membrane fuel cell (PEMFC) system and the feasibility evaluation of integrating with a proton exchange membrane electrolyzer (PEME).” Energy Convers. Manage. 186 (Apr): 487–499. https://doi.org/10.1016/j.enconman.2019.03.004.
del Real, A., A. Arce, and C. Bordons. 2007. “Development and experimental validation of a PEM fuel cell dynamic model.” J. Power Sources 173 (1): 310–324. https://doi.org/10.1016/j.jpowsour.2007.04.066.
El-Zonkoly, A. M. 2019. “Optimal energy management in smart grids including different types of aggregated flexible loads.” J. Energy Eng. 145 (5): 04019015. https://doi.org/10.1061/(ASCE)EY.1943-7897.0000613.
Fathy, A., H. Rezk, and A. M. Nassef. 2019. “Robust hydrogen-consumption-minimization strategy based Salp swarm algorithm for energy management of fuel cell/supercapacitor/batteries in highly fluctuated load condition.” Renewable Energy 139 (Aug): 147–160. https://doi.org/10.1016/j.renene.2019.02.076.
Görgün, H. 2006. “Dynamic modelling of a proton exchange membrane (PEM) electrolyzer.” Int. J. Hydrogen Energy 31 (1): 29–38. https://doi.org/10.1016/j.ijhydene.2005.04.001.
Guo, H., L. L. Wang, X. L. Yi, F. Ye, and C. F. Ma. 2019. “Simulation of mode-switching methods’ effect on mass transfer in a unitized regenerative fuel cell.” J. Energy Eng. 145 (1): 04018071. https://doi.org/10.1061/(ASCE)EY.1943-7897.0000589.
Gürbüz, H., H. Akçay, İ. H. Akçay, and S. Demirtürk. 2018. “Experimental study on operating characteristics of on-board PEMe hydrogen generator integrated with a SI engine.” J. Energy Eng. 144 (5): 04018055. https://doi.org/10.1061/(ASCE)EY.1943-7897.0000569.
Han, Y., Q. Li, T. Wang, W. Chen, and L. Ma. 2017. “Multisource coordination energy management strategy based on SOC consensus for a PEMFC–battery–supercapacitor hybrid tramway.” IEEE Trans. Veh. Technol. 67 (1): 296–305. https://doi.org/10.1109/TVT.2017.2747135.
He, H., S. Quan, and Y.-X. Wang. 2020. “Hydrogen circulation system model predictive control for polymer electrolyte membrane fuel cell-based electric vehicle application.” Int. J. Hydrogen Energy 45 (39): 20382–20390. https://doi.org/10.1016/j.ijhydene.2019.12.147.
Hsu, R. C., S. M. Chen, W. Y. Chen, and C. T. Liu. 2016. “A reinforcement learning based dynamic power management for fuel cell hybrid electric vehicle.” In Proc., 2016 Joint 8th Int. Conf. on Soft Computing and Intelligent Systems (SCIS) and 17th Int. Symp. on Advanced Intelligent Systems (ISIS), 460–464. New York: IEEE. https://doi.org/10.1109/SCIS-ISIS.2016.0104.
Ibrahim, M., S. Jemei, N. Y. Steiner, D. Hissel, and G. Wimmer. 2015. “Selection of mother wavelet and decomposition level for energy management in electrical vehicles including a fuel cell.” Int. J. Hydrogen Energy 40 (45): 15823–15833. https://doi.org/10.1016/j.ijhydene.2015.06.055.
Jiang, H., L. Xu, J. Li, Z. Hu, and M. Ouyang. 2019. “Energy management and component sizing for a fuel cell/battery/supercapacitor hybrid powertrain based on two-dimensional optimization algorithms.” Energy 177 (Jun): 386–396. https://doi.org/10.1016/j.energy.2019.04.110.
Jiao, K., and X. Li. 2011. “Water transport in polymer electrolyte membrane fuel cells.” Prog. Energy Combust. Sci. 37 (3): 221–291. https://doi.org/10.1016/j.pecs.2010.06.002.
Kélouwani, S., K. Agbossou, and R. Chahine. 2005. “Model for energy conversion in renewable energy system with hydrogen storage.” J. Power Sources 140 (2): 392–399. https://doi.org/10.1016/j.jpowsour.2004.08.019.
Li, C., L. Guo, and H. Zhang. 2018. “Numerical simulation and process optimization of production from dimethyl ether steam reforming.” J. Energy Eng. 144 (3): 04018020. https://doi.org/10.1061/(ASCE)EY.1943-7897.0000533.
Ning, Q., D. Xuan, and Y. Kim. 2010. “Modeling and control strategy development for fuel cell hybrid vehicles.” Int. J. Automot. Technol. 11 (2): 229–238. https://doi.org/10.1007/s12239-010-0029-x.
Oldham, K. B. 2008. “A Gouy–Chapman–Stern model of the double layer at a (metal)/(ionic liquid) interface.” J. Electroanal. Chem. 613 (2): 131–138. https://doi.org/10.1016/j.jelechem.2007.10.017.
Peng, J., H. He, and R. Xiong. 2017. “Rule based energy management strategy for a series–parallel plug-in hybrid electric bus optimized by dynamic programming.” Appl. Energy 185: 1633–1643. https://doi.org/10.1016/j.apenergy.2015.12.031.
Pukrushpan, J. T., A. G. Stefanopoulou, and H. Peng. 2004. “Control of fuel cell breathing.” IEEE Control Syst. Mag. 24 (2): 30–46. https://doi.org/10.1109/MCS.2004.1275430.
Reddy, N. P., D. Pasdeloup, M. K. Zadeh, and R. Skjetne. 2019. “An intelligent power and energy management system for fuel cell/battery hybrid electric vehicle using reinforcement learning.” In Proc., IEEE Transportation Electrification Conf. and Expo, 1–6. New York: IEEE. https://doi.org/10.1109/ITEC.2019.8790451.
Sabri, M. F., K. A. Danapalasingam, and M. F. Rahmat. 2016. “A review on hybrid electric vehicles architecture and energy management strategies.” Renewable Sustainable Energy Rev. 53 (Jan): 1433–1442. https://doi.org/10.1016/j.rser.2015.09.036.
Sadeghi, S., and M. Ameri. 2014. “Multiobjective optimization of PV-Bat-SOFC hybrid system: Effect of different fuels used in solid oxide fuel cell.” J. Energy Eng. 140 (2): 04013022. https://doi.org/10.1061/(ASCE)EY.1943-7897.0000170.
Tani, A., M. B. Camara, and B. Dakyo. 2012. “Energy management based on frequency approach for hybrid electric vehicle applications: Fuel-cell/lithium-battery and ultracapacitors.” IEEE Trans. Veh. Technol. 61 (8): 3375–3386. https://doi.org/10.1109/TVT.2012.2206415.
Wang, C., M. H. Nehrir, and S. R. Shaw. 2005. “Dynamic models and model validation for PEM fuel cells using electrical circuits.” IEEE Trans. Energy Convers. 20 (2): 442–451. https://doi.org/10.1109/TEC.2004.842357.
Wang, C., R. Xiong, H. He, Y. Zhang, and W. Shen. 2019a. “Comparison of decomposition levels for wavelet transform based energy management in a plug-in hybrid electric vehicle.” J. Cleaner Prod. 210 (Feb): 1085–1097. https://doi.org/10.1016/j.jclepro.2018.11.082.
Wang, Y., Z. Sun, and Z. Chen. 2019b. “Energy management strategy for battery/supercapacitor/fuel cell hybrid source vehicles based on finite state machine.” Appl. Energy 254 (Nov): 113707. https://doi.org/10.1016/j.apenergy.2019.113707.
Wang, Y.-X., K. Ou, and Y.-B. Kim. 2015. “Modeling and experimental validation of hybrid proton exchange membrane fuel cell/battery system for power management control.” Int. J. Hydrogen Energy 40 (35): 11713–11721. https://doi.org/10.1016/j.ijhydene.2015.03.073.
Wang, Y.-X., K. Ou, and Y.-B. Kim. 2017. “Power source protection method for hybrid polymer electrolyte membrane fuel cell/lithium-ion battery system.” Renewable Energy 111 (Oct): 381–391. https://doi.org/10.1016/j.renene.2017.03.088.
Wu, W., B. N. Chuang, J. J. Hwang, C. K. Lin, and S. B. Yang. 2019. “Techno-economic evaluation of a hybrid fuel cell vehicle with on-board MeOH-to- processor.” Appl. Energy 238 (Mar): 401–412. https://doi.org/10.1016/j.apenergy.2019.01.089.
Xuan, D. J., Z. Shi, J. Chen, C. Zhang, and Y.-X. Wang. 2020. “Real-time estimation of state-of-charge in lithium-ion batteries using improved central difference transform method.” J. Cleaner Prod. 252 (Apr): 119787. https://doi.org/10.1016/j.jclepro.2019.119787.
Yan, M., M. Li, H. He, J. Peng, and C. Sun. 2018. “Rule-based energy management for dual-source electric buses extracted by wavelet transform.” J. Cleaner Prod. 189 (10): 116–127. https://doi.org/10.1016/j.jclepro.2018.04.054.
Yang, Z., K. Jiao, Z. Liu, Y. Yin, and Q. Du. 2020. “Investigation of performance heterogeneity of PEMFC stack based on 1+1D and flow distribution models.” Energy Convers. Manage. 207 (Mar): 112502. https://doi.org/10.1016/j.enconman.2020.112502.
Zhang, R., J. Tao, and H. Zhou. 2018. “Fuzzy optimal energy management for fuel cell and supercapacitor systems using neural network based driving pattern recognition.” IEEE Trans. Fuzzy Syst. 27 (1): 45–57. https://doi.org/10.1109/TFUZZ.2018.2856086.
Zhou, Y., A. Ravey, and M. C. Péra. 2019. “A survey on driving prediction techniques for predictive energy management of plug-in hybrid electric vehicles.” J. Power Sources 412 (Feb): 480–495. https://doi.org/10.1016/j.jpowsour.2018.11.085.
Zhou, Y., A. Ravey, and M. C. Péra. 2020. “Multi-mode predictive energy management for fuel cell hybrid electric vehicles using Markov driving pattern recognizer.” Appl. Energy 258 (Jan): 114057. https://doi.org/10.1016/j.apenergy.2019.114057.
Information & Authors
Information
Published In
Journal of Energy Engineering
Volume 146 • Issue 6 • December 2020
Copyright
© 2020 American Society of Civil Engineers.
History
Received: Feb 29, 2020
Accepted: Jun 26, 2020
Published online: Sep 4, 2020
Published in print: Dec 1, 2020
Discussion open until: Feb 4, 2021
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.