IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v86y2015icp139-151.html
   My bibliography  Save this article

Parameter extraction of different fuel cell models with transferred adaptive differential evolution

Author

Listed:
  • Gong, Wenyin
  • Yan, Xuesong
  • Liu, Xiaobo
  • Cai, Zhihua

Abstract

To improve the design and control of FC (fuel cell) models, it is important to extract their unknown parameters. Generally, the parameter extraction problems of FC models can be transformed as nonlinear and multi-variable optimization problems. To extract the parameters of different FC models exactly and fast, in this paper, we propose a transferred adaptive DE (differential evolution) framework, in which the successful parameters of the adaptive DE solving previous problems are properly transferred to solve new optimization problems in the similar problem-domains. Based on this framework, an improved adaptive DE method (TRADE, in short) is presented as an illustration. To verify the performance of our proposal, TRADE is used to extract the unknown parameters of two types of fuel cell models, i.e., PEMFC (proton exchange membrane fuel cell) and SOFC (solid oxide fuel cell). The results of TRADE are also compared with those of other state-of-the-art EAs (evolutionary algorithms). Even though the modification is very simple, the results indicate that TRADE can extract the parameters of both PEMFC and SOFC models exactly and fast. Moreover, the V–I characteristics obtained by TRADE agree well with the simulated and experimental data in all cases for both types of fuel cell models. Also, it improves the performance of the original adaptive DE significantly in terms of both the quality of final solutions and the convergence speed in all cases. Additionally, TRADE is able to provide better results compared with other EAs.

Suggested Citation

  • Gong, Wenyin & Yan, Xuesong & Liu, Xiaobo & Cai, Zhihua, 2015. "Parameter extraction of different fuel cell models with transferred adaptive differential evolution," Energy, Elsevier, vol. 86(C), pages 139-151.
    • Handle: RePEc:eee:energy:v:86:y:2015:i:c:p:139-151
    DOI: 10.1016/j.energy.2015.03.117
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544215004661
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2015.03.117?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. Wang, Yongqiang & Zhou, Jianzhong & Mo, Li & Zhang, Rui & Zhang, Yongchuan, 2012. "Short-term hydrothermal generation scheduling using differential real-coded quantum-inspired evolutionary algorithm," Energy, Elsevier, vol. 44(1), pages 657-671.
    2. Carton, J.G. & Lawlor, V. & Olabi, A.G. & Hochenauer, C. & Zauner, G., 2012. "Water droplet accumulation and motion in PEM (Proton Exchange Membrane) fuel cell mini-channels," Energy, Elsevier, vol. 39(1), pages 63-73.
    3. Zhang, Huifeng & Zhou, Jianzhong & Fang, Na & Zhang, Rui & Zhang, Yongchuan, 2013. "Daily hydrothermal scheduling with economic emission using simulated annealing technique based multi-objective cultural differential evolution approach," Energy, Elsevier, vol. 50(C), pages 24-37.
    4. Chakraborty, Uday K. & Abbott, Travis E. & Das, Sajal K., 2012. "PEM fuel cell modeling using differential evolution," Energy, Elsevier, vol. 40(1), pages 387-399.
    5. Fong, K.F. & Lee, C.K. & Chow, C.K. & Yuen, S.Y., 2011. "Simulation–optimization of solar–thermal refrigeration systems for office use in subtropical Hong Kong," Energy, Elsevier, vol. 36(11), pages 6298-6307.
    6. Gong, Wenyin & Cai, Zhihua, 2013. "Accelerating parameter identification of proton exchange membrane fuel cell model with ranking-based differential evolution," Energy, Elsevier, vol. 59(C), pages 356-364.
    7. Vaisakh, K. & Srinivas, L.R., 2010. "A genetic evolving ant direction DE for OPF with non-smooth cost functions and statistical analysis," Energy, Elsevier, vol. 35(8), pages 3155-3171.
    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. El-Hay, E.A. & El-Hameed, M.A. & El-Fergany, A.A., 2019. "Optimized Parameters of SOFC for steady state and transient simulations using interior search algorithm," Energy, Elsevier, vol. 166(C), pages 451-461.
    2. Gouda, Eid A. & Kotb, Mohamed F. & El-Fergany, Attia A., 2021. "Jellyfish search algorithm for extracting unknown parameters of PEM fuel cell models: Steady-state performance and analysis," Energy, Elsevier, vol. 221(C).
    3. Xu, Liangfei & Fang, Chuan & Hu, Junming & Cheng, Siliang & Li, Jianqiu & Ouyang, Minggao & Lehnert, Werner, 2017. "Parameter extraction of polymer electrolyte membrane fuel cell based on quasi-dynamic model and periphery signals," Energy, Elsevier, vol. 122(C), pages 675-690.
    4. Rashid, Kashif & Dong, Sang Keun & Mehran, Muhammad Taqi, 2017. "Numerical investigations to determine the optimal operating conditions for 1 kW-class flat-tubular solid oxide fuel cell stack," Energy, Elsevier, vol. 141(C), pages 673-691.
    5. Kandidayeni, M. & Macias, A. & Khalatbarisoltani, A. & Boulon, L. & Kelouwani, S., 2019. "Benchmark of proton exchange membrane fuel cell parameters extraction with metaheuristic optimization algorithms," Energy, Elsevier, vol. 183(C), pages 912-925.
    6. 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.
    7. Petrone, Giovanni & Zamboni, Walter & Spagnuolo, Giovanni, 2019. "An interval arithmetic-based method for parametric identification of a fuel cell equivalent circuit model," Applied Energy, Elsevier, vol. 242(C), pages 1226-1236.
    8. Fathy, Ahmed & Elaziz, Mohamed Abd & Alharbi, Abdullah G., 2020. "A novel approach based on hybrid vortex search algorithm and differential evolution for identifying the optimal parameters of PEM fuel cell," Renewable Energy, Elsevier, vol. 146(C), pages 1833-1845.
    9. Priya, K. & Sathishkumar, K. & Rajasekar, N., 2018. "A comprehensive review on parameter estimation techniques for Proton Exchange Membrane fuel cell modelling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 121-144.
    10. Samuel Raafat Fahim & Hany M. Hasanien & Rania A. Turky & Abdulaziz Alkuhayli & Abdullrahman A. Al-Shamma’a & Abdullah M. Noman & Marcos Tostado-Véliz & Francisco Jurado, 2021. "Parameter Identification of Proton Exchange Membrane Fuel Cell Based on Hunger Games Search Algorithm," Energies, MDPI, vol. 14(16), pages 1-21, August.
    11. H. Eduardo Ariza & Antonio Correcher & Carlos Sánchez & Ángel Pérez-Navarro & Emilio García, 2018. "Thermal and Electrical Parameter Identification of a Proton Exchange Membrane Fuel Cell Using Genetic Algorithm," Energies, MDPI, vol. 11(8), pages 1-15, August.
    12. Yang, Bo & Guo, Zhengxun & Yang, Yi & Chen, Yijun & Zhang, Rui & Su, Keyi & Shu, Hongchun & Yu, Tao & Zhang, Xiaoshun, 2021. "Extreme learning machine based meta-heuristic algorithms for parameter extraction of solid oxide fuel cells," Applied Energy, Elsevier, vol. 303(C).
    13. Walter Zamboni & Giovanni Petrone & Giovanni Spagnuolo & Davide Beretta, 2019. "An Evolutionary Computation Approach for the Online/On-Board Identification of PEM Fuel Cell Impedance Parameters with A Diagnostic Perspective," Energies, MDPI, vol. 12(22), pages 1-19, November.
    14. Antonio Guarino & Giovanni Petrone & Walter Zamboni, 2019. "Improving the Performance of a Dual Kalman Filter for the Identification of PEM Fuel Cells in Impedance Spectroscopy Experiments," Energies, MDPI, vol. 12(17), pages 1-18, September.
    15. Mohamed Louzazni & Sameer Al-Dahidi & Marco Mussetta, 2020. "Fuel Cell Characteristic Curve Approximation Using the Bézier Curve Technique," Sustainability, MDPI, vol. 12(19), pages 1-23, October.
    16. Chakraborty, Uttara, 2016. "Fuel crossover and internal current in proton exchange membrane fuel cell modeling," Applied Energy, Elsevier, vol. 163(C), pages 60-62.
    17. Mohamed Ahmed Ali & Mohey Eldin Mandour & Mohammed Elsayed Lotfy, 2023. "Adaptive Estimation of Quasi-Empirical Proton Exchange Membrane Fuel Cell Models Based on Coot Bird Optimizer and Data Accumulation," Sustainability, MDPI, vol. 15(11), pages 1-20, June.
    18. Fathy, Ahmed & Rezk, Hegazy, 2022. "Political optimizer based approach for estimating SOFC optimal parameters for static and dynamic models," Energy, Elsevier, vol. 238(PC).
    19. Seleem, Sameh I. & Hasanien, Hany M. & El-Fergany, Attia A., 2021. "Equilibrium optimizer for parameter extraction of a fuel cell dynamic model," Renewable Energy, Elsevier, vol. 169(C), pages 117-128.
    20. Ahmed M. Agwa & Attia A. El-Fergany & Gamal M. Sarhan, 2019. "Steady-State Modeling of Fuel Cells Based on Atom Search Optimizer," Energies, MDPI, vol. 12(10), pages 1-14, May.
    21. Fathy, Ahmed & Rezk, Hegazy, 2018. "Multi-verse optimizer for identifying the optimal parameters of PEMFC model," Energy, Elsevier, vol. 143(C), pages 634-644.

    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. Gong, Wenyin & Cai, Zhihua, 2013. "Accelerating parameter identification of proton exchange membrane fuel cell model with ranking-based differential evolution," Energy, Elsevier, vol. 59(C), pages 356-364.
    2. Fofana, Daouda & Natarajan, Sadesh Kumar & Hamelin, Jean & Benard, Pierre, 2014. "Low platinum, high limiting current density of the PEMFC (proton exchange membrane fuel cell) based on multilayer cathode catalyst approach," Energy, Elsevier, vol. 64(C), pages 398-403.
    3. Sun, Zhe & Wang, Ning & Bi, Yunrui & Srinivasan, Dipti, 2015. "Parameter identification of PEMFC model based on hybrid adaptive differential evolution algorithm," Energy, Elsevier, vol. 90(P2), pages 1334-1341.
    4. Vitayasak, Srisatja & Pongcharoen, Pupong & Hicks, Chris, 2017. "A tool for solving stochastic dynamic facility layout problems with stochastic demand using either a Genetic Algorithm or modified Backtracking Search Algorithm," International Journal of Production Economics, Elsevier, vol. 190(C), pages 146-157.
    5. Xu, Liangfei & Fang, Chuan & Hu, Junming & Cheng, Siliang & Li, Jianqiu & Ouyang, Minggao & Lehnert, Werner, 2017. "Parameter extraction of polymer electrolyte membrane fuel cell based on quasi-dynamic model and periphery signals," Energy, Elsevier, vol. 122(C), pages 675-690.
    6. Xu, Shuhui & Wang, Yong & Wang, Zhi, 2019. "Parameter estimation of proton exchange membrane fuel cells using eagle strategy based on JAYA algorithm and Nelder-Mead simplex method," Energy, Elsevier, vol. 173(C), pages 457-467.
    7. Santhosh, Apoorva & Farid, Amro M. & Youcef-Toumi, Kamal, 2014. "Real-time economic dispatch for the supply side of the energy-water nexus," Applied Energy, Elsevier, vol. 122(C), pages 42-52.
    8. Priya, K. & Sathishkumar, K. & Rajasekar, N., 2018. "A comprehensive review on parameter estimation techniques for Proton Exchange Membrane fuel cell modelling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 121-144.
    9. Glotić, Arnel & Glotić, Adnan & Kitak, Peter & Pihler, Jože & Tičar, Igor, 2014. "Optimization of hydro energy storage plants by using differential evolution algorithm," Energy, Elsevier, vol. 77(C), pages 97-107.
    10. Rahnavard, Aylin & Rowshanzamir, Soosan & Parnian, Mohammad Javad & Amirkhanlou, Gholam Reza, 2015. "The effect of sulfonated poly (ether ether ketone) as the electrode ionomer for self-humidifying nanocomposite proton exchange membrane fuel cells," Energy, Elsevier, vol. 82(C), pages 746-757.
    11. Santhosh, Apoorva & Farid, Amro M. & Youcef-Toumi, Kamal, 2014. "The impact of storage facility capacity and ramping capabilities on the supply side economic dispatch of the energy–water nexus," Energy, Elsevier, vol. 66(C), pages 363-377.
    12. Gouda, Eid A. & Kotb, Mohamed F. & El-Fergany, Attia A., 2021. "Jellyfish search algorithm for extracting unknown parameters of PEM fuel cell models: Steady-state performance and analysis," Energy, Elsevier, vol. 221(C).
    13. Hickman, William & Muzhikyan, Aramazd & Farid, Amro M., 2017. "The synergistic role of renewable energy integration into the unit commitment of the energy water nexus," Renewable Energy, Elsevier, vol. 108(C), pages 220-229.
    14. El-Hay, E.A. & El-Hameed, M.A. & El-Fergany, A.A., 2019. "Optimized Parameters of SOFC for steady state and transient simulations using interior search algorithm," Energy, Elsevier, vol. 166(C), pages 451-461.
    15. Miao, Di & Chen, Wei & Zhao, Wei & Demsas, Tekle, 2020. "Parameter estimation of PEM fuel cells employing the hybrid grey wolf optimization method," Energy, Elsevier, vol. 193(C).
    16. Sayadi, Parvin & Rowshanzamir, Soosan & Parnian, Mohammad Javad, 2016. "Study of hydrogen crossover and proton conductivity of self-humidifying nanocomposite proton exchange membrane based on sulfonated poly (ether ether ketone)," Energy, Elsevier, vol. 94(C), pages 292-303.
    17. Nazari-Heris, M. & Mohammadi-Ivatloo, B. & Haghrah, A., 2017. "Optimal short-term generation scheduling of hydrothermal systems by implementation of real-coded genetic algorithm based on improved Mühlenbein mutation," Energy, Elsevier, vol. 128(C), pages 77-85.
    18. Tang, Xiongmin & Li, Zhengshuo & Xu, Xuancong & Zeng, Zhijun & Jiang, Tianhong & Fang, Wenrui & Meng, Anbo, 2022. "Multi-objective economic emission dispatch based on an extended crisscross search optimization algorithm," Energy, Elsevier, vol. 244(PA).
    19. Feng, Zhong-kai & Niu, Wen-jing & Cheng, Chun-tian, 2017. "Multi-objective quantum-behaved particle swarm optimization for economic environmental hydrothermal energy system scheduling," Energy, Elsevier, vol. 131(C), pages 165-178.
    20. Soroudi, Alireza, 2013. "Robust optimization based self scheduling of hydro-thermal Genco in smart grids," Energy, Elsevier, vol. 61(C), pages 262-271.

    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:energy:v:86:y:2015:i:c:p:139-151. 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.journals.elsevier.com/energy .

    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.