IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v206y2017icp458-474.html
   My bibliography  Save this article

Energy optimization of fuel cell system by using global extremum seeking algorithm

Author

Listed:
  • Bizon, Nicu

Abstract

This paper presents a real-time optimization method and demonstrates its application to a Proton Exchange Membrane Fuel Cell (PEMFC) system. The optimization function was defined as mix of two performance indicators, the FC net power and the Fuel Consumption Efficiency, using the appropriate weighting coefficients. The weighting coefficients will modify the optimization surface and many extreme could appear on plateau of the optimization surface. The Global Extremum Seeking (GES) algorithm proposed here as real-time optimization method will locate and track the global maximum point and related to this will be established the optimal fueling rates for the PEMFC system under a given load. In this study four strategies will be tested, including the Static Feed-Forward (sFF) control strategy as reference. The optimal operating conditions were sought at different levels of load and the gaps between these four strategies were estimated. For example, in comparison with the PEMFC system controlled by the sFF strategy, the GES operation of the PEMFC system could increase the energy efficiency with 1–2.1%, depending on the FC current level and values used for the weighting coefficients. If the PEMFC system operates under variable load profile, the Fuel Consumption Efficiency could also increase with more than 0.54W/lpm for GES&LF-based optimization strategy in comparison with the sFF strategy. The effectiveness of GES&LF-based optimization strategy was shown considering a FC Hybrid Power Source under variable load profile.

Suggested Citation

  • Bizon, Nicu, 2017. "Energy optimization of fuel cell system by using global extremum seeking algorithm," Applied Energy, Elsevier, vol. 206(C), pages 458-474.
    • Handle: RePEc:eee:appene:v:206:y:2017:i:c:p:458-474
    DOI: 10.1016/j.apenergy.2017.08.097
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261917311170
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2017.08.097?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Sulaiman, N. & Hannan, M.A. & Mohamed, A. & Majlan, E.H. & Wan Daud, W.R., 2015. "A review on energy management system for fuel cell hybrid electric vehicle: Issues and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 802-814.
    2. Castaings, Ali & Lhomme, Walter & Trigui, Rochdi & Bouscayrol, Alain, 2016. "Comparison of energy management strategies of a battery/supercapacitors system for electric vehicle under real-time constraints," Applied Energy, Elsevier, vol. 163(C), pages 190-200.
    3. Hou, Cong & Ouyang, Minggao & Xu, Liangfei & Wang, Hewu, 2014. "Approximate Pontryagin’s minimum principle applied to the energy management of plug-in hybrid electric vehicles," Applied Energy, Elsevier, vol. 115(C), pages 174-189.
    4. Matraji, Imad & Laghrouche, Salah & Jemei, Samir & Wack, Maxime, 2013. "Robust control of the PEM fuel cell air-feed system via sub-optimal second order sliding mode," Applied Energy, Elsevier, vol. 104(C), pages 945-957.
    5. Ettihir, K. & Boulon, L. & Agbossou, K., 2016. "Optimization-based energy management strategy for a fuel cell/battery hybrid power system," Applied Energy, Elsevier, vol. 163(C), pages 142-153.
    6. Bizon, Nicu, 2014. "Tracking the maximum efficiency point for the FC system based on extremum seeking scheme to control the air flow," Applied Energy, Elsevier, vol. 129(C), pages 147-157.
    7. Li, Junqiu & Jin, Xin & Xiong, Rui, 2017. "Multi-objective optimization study of energy management strategy and economic analysis for a range-extended electric bus," Applied Energy, Elsevier, vol. 194(C), pages 798-807.
    8. Bizon, N., 2010. "On tracking robustness in adaptive extremum seeking control of the fuel cell power plants," Applied Energy, Elsevier, vol. 87(10), pages 3115-3130, October.
    9. Zhang, Pei & Yan, Fuwu & Du, Changqing, 2015. "A comprehensive analysis of energy management strategies for hybrid electric vehicles based on bibliometrics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 88-104.
    10. Wieczorek, Maciej & Lewandowski, Mirosław, 2017. "A mathematical representation of an energy management strategy for hybrid energy storage system in electric vehicle and real time optimization using a genetic algorithm," Applied Energy, Elsevier, vol. 192(C), pages 222-233.
    11. Peng, Jiankun & He, Hongwen & Xiong, Rui, 2017. "Rule based energy management strategy for a series–parallel plug-in hybrid electric bus optimized by dynamic programming," Applied Energy, Elsevier, vol. 185(P2), pages 1633-1643.
    12. Zou, Yuan & Liu, Teng & Liu, Dexing & Sun, Fengchun, 2016. "Reinforcement learning-based real-time energy management for a hybrid tracked vehicle," Applied Energy, Elsevier, vol. 171(C), pages 372-382.
    13. Yu, Huilong & Tarsitano, Davide & Hu, Xiaosong & Cheli, Federico, 2016. "Real time energy management strategy for a fast charging electric urban bus powered by hybrid energy storage system," Energy, Elsevier, vol. 112(C), pages 322-331.
    14. Olatomiwa, Lanre & Mekhilef, Saad & Ismail, M.S. & Moghavvemi, M., 2016. "Energy management strategies in hybrid renewable energy systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 821-835.
    15. Han, Jaeyoung & Yu, Sangseok & Yi, Sun, 2017. "Adaptive control for robust air flow management in an automotive fuel cell system," Applied Energy, Elsevier, vol. 190(C), pages 73-83.
    16. Zahraee, S.M. & Khalaji Assadi, M. & Saidur, R., 2016. "Application of Artificial Intelligence Methods for Hybrid Energy System Optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 617-630.
    17. Bizon, Nicu, 2013. "Energy harvesting from the FC stack that operates using the MPP tracking based on modified extremum seeking control," Applied Energy, Elsevier, vol. 104(C), pages 326-336.
    18. Cai, Y. & Ouyang, M.G. & Yang, F., 2017. "Impact of power split configurations on fuel consumption and battery degradation in plug-in hybrid electric city buses," Applied Energy, Elsevier, vol. 188(C), pages 257-269.
    19. Ramos-Paja, Carlos Andrés & Spagnuolo, Giovanni & Petrone, Giovanni & Mamarelis, Emilio, 2014. "A perturbation strategy for fuel consumption minimization in polymer electrolyte membrane fuel cells: Analysis, Design and FPGA implementation," Applied Energy, Elsevier, vol. 119(C), pages 21-32.
    20. Wang, Hong & Huang, Yanjun & Khajepour, Amir & Song, Qiang, 2016. "Model predictive control-based energy management strategy for a series hybrid electric tracked vehicle," Applied Energy, Elsevier, vol. 182(C), pages 105-114.
    21. Bizon, Nicu & Radut, Marin & Oproescu, Mihai, 2015. "Energy control strategies for the Fuel Cell Hybrid Power Source under unknown load profile," Energy, Elsevier, vol. 86(C), pages 31-41.
    22. Das, Vipin & Padmanaban, Sanjeevikumar & Venkitusamy, Karthikeyan & Selvamuthukumaran, Rajasekar & Blaabjerg, Frede & Siano, Pierluigi, 2017. "Recent advances and challenges of fuel cell based power system architectures and control – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 10-18.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yutao Chen & Nazar Rozkvas & Mircea Lazar, 2020. "Driving Mode Optimization for Hybrid Trucks Using Road and Traffic Preview Data," Energies, MDPI, vol. 13(20), pages 1-18, October.
    2. Bizon, Nicu, 2019. "Real-time optimization strategies of Fuel Cell Hybrid Power Systems based on Load-following control: A new strategy, and a comparative study of topologies and fuel economy obtained," Applied Energy, Elsevier, vol. 241(C), pages 444-460.
    3. Song, Dongran & Tu, Yanping & Wang, Lei & Jin, Fangjun & Li, Ziqun & Huang, Chaoneng & Xia, E & Rizk-Allah, Rizk M. & Yang, Jian & Su, Mei & Hoon Joo, Young, 2022. "Coordinated optimization on energy capture and torque fluctuation of wind turbines via variable weight NMPC with fuzzy regulator," Applied Energy, Elsevier, vol. 312(C).
    4. Nicu Bizon & Mihai Oproescu, 2018. "Experimental Comparison of Three Real-Time Optimization Strategies Applied to Renewable/FC-Based Hybrid Power Systems Based on Load-Following Control," Energies, MDPI, vol. 11(12), pages 1-32, December.
    5. Bizon, Nicu, 2018. "Effective mitigation of the load pulses by controlling the battery/SMES hybrid energy storage system," Applied Energy, Elsevier, vol. 229(C), pages 459-473.
    6. Bizon, Nicu, 2019. "Efficient fuel economy strategies for the Fuel Cell Hybrid Power Systems under variable renewable/load power profile," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    7. Bizon, Nicu, 2019. "Fuel saving strategy using real-time switching of the fueling regulators in the proton exchange membrane fuel cell system," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    8. Bizon, Nicu, 2019. "Hybrid power sources (HPSs) for space applications: Analysis of PEMFC/Battery/SMES HPS under unknown load containing pulses," Renewable and Sustainable Energy Reviews, Elsevier, vol. 105(C), pages 14-37.
    9. Alessandro Serpi & Mario Porru, 2019. "Modelling and Design of Real-Time Energy Management Systems for Fuel Cell/Battery Electric Vehicles," Energies, MDPI, vol. 12(22), pages 1-21, November.
    10. Frangopoulos, Christos A., 2018. "Recent developments and trends in optimization of energy systems," Energy, Elsevier, vol. 164(C), pages 1011-1020.
    11. Ioan-Sorin Sorlei & Nicu Bizon & Phatiphat Thounthong & Mihai Varlam & Elena Carcadea & Mihai Culcer & Mariana Iliescu & Mircea Raceanu, 2021. "Fuel Cell Electric Vehicles—A Brief Review of Current Topologies and Energy Management Strategies," Energies, MDPI, vol. 14(1), pages 1-29, January.
    12. Ahmed M. Ali & Dirk Söffker, 2018. "Towards Optimal Power Management of Hybrid Electric Vehicles in Real-Time: A Review on Methods, Challenges, and State-Of-The-Art Solutions," Energies, MDPI, vol. 11(3), pages 1-24, February.
    13. Daeichian, Abolghasem & Ghaderi, Razieh & Kandidayeni, Mohsen & Soleymani, Mehdi & Trovão, João P. & Boulon, Loïc, 2021. "Online characteristics estimation of a fuel cell stack through covariance intersection data fusion," Applied Energy, Elsevier, vol. 292(C).
    14. Bizon, Nicu, 2018. "Optimal operation of fuel cell/wind turbine hybrid power system under turbulent wind and variable load," Applied Energy, Elsevier, vol. 212(C), pages 196-209.
    15. Banaja Mohanty & Rajvikram Madurai Elavarasan & Hany M. Hasanien & Elangovan Devaraj & Rania A. Turky & Rishi Pugazhendhi, 2022. "Parameters Identification of Proton Exchange Membrane Fuel Cell Model Based on the Lightning Search Algorithm," Energies, MDPI, vol. 15(21), pages 1-19, October.
    16. Mohsen Kandidayeni & Alvaro Macias & Loïc Boulon & João Pedro F. Trovão, 2020. "Online Modeling of a Fuel Cell System for an Energy Management Strategy Design," Energies, MDPI, vol. 13(14), pages 1-17, July.
    17. Bizon, Nicu & Thounthong, Phatiphat, 2018. "Real-time strategies to optimize the fueling of the fuel cell hybrid power source: A review of issues, challenges and a new approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 1089-1102.
    18. Fathy, Ahmed & Rezk, Hegazy & Nassef, Ahmed M., 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, Elsevier, vol. 139(C), pages 147-160.
    19. Nicu Bizon & Phatiphat Thounthong, 2021. "A Simple and Safe Strategy for Improving the Fuel Economy of a Fuel Cell Vehicle," Mathematics, MDPI, vol. 9(6), pages 1-29, March.
    20. Nicu Bizon & Valentin Alexandru Stan & Angel Ciprian Cormos, 2019. "Optimization of the Fuel Cell Renewable Hybrid Power System Using the Control Mode of the Required Load Power on the DC Bus," Energies, MDPI, vol. 12(10), pages 1-15, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bizon, Nicu, 2019. "Real-time optimization strategies of Fuel Cell Hybrid Power Systems based on Load-following control: A new strategy, and a comparative study of topologies and fuel economy obtained," Applied Energy, Elsevier, vol. 241(C), pages 444-460.
    2. Nicu Bizon & Mihai Oproescu, 2018. "Experimental Comparison of Three Real-Time Optimization Strategies Applied to Renewable/FC-Based Hybrid Power Systems Based on Load-Following Control," Energies, MDPI, vol. 11(12), pages 1-32, December.
    3. Bizon, Nicu & Thounthong, Phatiphat, 2018. "Real-time strategies to optimize the fueling of the fuel cell hybrid power source: A review of issues, challenges and a new approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 1089-1102.
    4. Bizon, Nicu, 2019. "Efficient fuel economy strategies for the Fuel Cell Hybrid Power Systems under variable renewable/load power profile," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    5. Bizon, Nicu, 2019. "Fuel saving strategy using real-time switching of the fueling regulators in the proton exchange membrane fuel cell system," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    6. Nicu Bizon & Phatiphat Thounthong, 2021. "A Simple and Safe Strategy for Improving the Fuel Economy of a Fuel Cell Vehicle," Mathematics, MDPI, vol. 9(6), pages 1-29, March.
    7. Bizon, Nicu, 2019. "Hybrid power sources (HPSs) for space applications: Analysis of PEMFC/Battery/SMES HPS under unknown load containing pulses," Renewable and Sustainable Energy Reviews, Elsevier, vol. 105(C), pages 14-37.
    8. Li, Yuehua & Pei, Pucheng & Ma, Ze & Ren, Peng & Huang, Hao, 2020. "Analysis of air compression, progress of compressor and control for optimal energy efficiency in proton exchange membrane fuel cell," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    9. Feroldi, Diego & Carignano, Mauro, 2016. "Sizing for fuel cell/supercapacitor hybrid vehicles based on stochastic driving cycles," Applied Energy, Elsevier, vol. 183(C), pages 645-658.
    10. Xiong, Rui & Cao, Jiayi & Yu, Quanqing, 2018. "Reinforcement learning-based real-time power management for hybrid energy storage system in the plug-in hybrid electric vehicle," Applied Energy, Elsevier, vol. 211(C), pages 538-548.
    11. Liu, Hanwu & Lei, Yulong & Fu, Yao & Li, Xingzhong, 2022. "A novel hybrid-point-line energy management strategy based on multi-objective optimization for range-extended electric vehicle," Energy, Elsevier, vol. 247(C).
    12. Xiong, Rui & Duan, Yanzhou & Cao, Jiayi & Yu, Quanqing, 2018. "Battery and ultracapacitor in-the-loop approach to validate a real-time power management method for an all-climate electric vehicle," Applied Energy, Elsevier, vol. 217(C), pages 153-165.
    13. Chen, Zheng & Hu, Hengjie & Wu, Yitao & Zhang, Yuanjian & Li, Guang & Liu, Yonggang, 2020. "Stochastic model predictive control for energy management of power-split plug-in hybrid electric vehicles based on reinforcement learning," Energy, Elsevier, vol. 211(C).
    14. Lian, Renzong & Peng, Jiankun & Wu, Yuankai & Tan, Huachun & Zhang, Hailong, 2020. "Rule-interposing deep reinforcement learning based energy management strategy for power-split hybrid electric vehicle," Energy, Elsevier, vol. 197(C).
    15. Lopez Lopez, Guadalupe & Schacht Rodriguez, Ricardo & Alvarado, Victor M. & Gomez-Aguilar, J.F. & Mota, Juan E. & Sandoval, Cinda, 2017. "Hybrid PEMFC-supercapacitor system: Modeling and energy management in energetic macroscopic representation," Applied Energy, Elsevier, vol. 205(C), pages 1478-1494.
    16. Nicu Bizon & Alin Gheorghita Mazare & Laurentiu Mihai Ionescu & Phatiphat Thounthong & Erol Kurt & Mihai Oproescu & Gheorghe Serban & Ioan Lita, 2019. "Better Fuel Economy by Optimizing Airflow of the Fuel Cell Hybrid Power Systems Using Fuel Flow-Based Load-Following Control," Energies, MDPI, vol. 12(14), pages 1-17, July.
    17. Zhuang, Weichao & Zhang, Xiaowu & Li, Daofei & Wang, Liangmo & Yin, Guodong, 2017. "Mode shift map design and integrated energy management control of a multi-mode hybrid electric vehicle," Applied Energy, Elsevier, vol. 204(C), pages 476-488.
    18. Fengqi Zhang & Lihua Wang & Serdar Coskun & Hui Pang & Yahui Cui & Junqiang Xi, 2020. "Energy Management Strategies for Hybrid Electric Vehicles: Review, Classification, Comparison, and Outlook," Energies, MDPI, vol. 13(13), pages 1-35, June.
    19. Wang, Yue & Zeng, Xiaohua & Song, Dafeng & Yang, Nannan, 2019. "Optimal rule design methodology for energy management strategy of a power-split hybrid electric bus," Energy, Elsevier, vol. 185(C), pages 1086-1099.
    20. Zhuang, Weichao & Li (Eben), Shengbo & Zhang, Xiaowu & Kum, Dongsuk & Song, Ziyou & Yin, Guodong & Ju, Fei, 2020. "A survey of powertrain configuration studies on hybrid electric vehicles," Applied Energy, Elsevier, vol. 262(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:206:y:2017:i:c:p:458-474. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.