IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v312y2024ics0360544224032213.html
   My bibliography  Save this article

Unit prediction horizon H∞ based model predictive control for the fuel cell based plug-in hybrid electric vehicle with rule-based energy management system

Author

Listed:
  • Ahmed, Afaq
  • Ahmad, Iftikhar

Abstract

Plug-in hybrid electric vehicles (PHEVs) provide a good alternative in achieving better performance and in the reduction of harmful gas emissions. The hybrid energy storage system (HESS) and the integrated charging unit constitute the PHEV under consideration. To meet the load demands, the proposed HESS is a coupled system comprising a fuel cell, high energy density battery, and high-power density super-capacitor. On-board charging involves the utilization of a DC–DC buck converter and an uncontrolled rectifier and two buck-boost converters are utilized to facilitate a smooth transfer of energy. A rule-based supervisory controller has been implemented for different load conditions which takes into account the state of charge of energy sources and also the total power inflow of the power sources. A model predictive control (MPC) technique is implemented to ensure that PHEVs function smoothly in terms of regulation of DC bus voltage and tracking of current. Unit prediction horizon i.e. only one step ahead looking into the future is considered for the MPC to make it computationally less expensive. MPC is designed in such a way that its performance is close to our favorite linear controller which in our case is the H∞ controller. The inverse optimal control technique is used for determining the weight matrices of the cost function. The proposed controller has been simulated using MATLAB. Also, the performance comparison is made between the designed MPC and the non-linear control approach i.e. integral sliding mode control and integral backstepping-based control to show that it achieves comparable or superior performance to the non-linear controller. The real-time performance of H∞ based MPC is verified using controller hardware in the loop experimental setup.

Suggested Citation

  • Ahmed, Afaq & Ahmad, Iftikhar, 2024. "Unit prediction horizon H∞ based model predictive control for the fuel cell based plug-in hybrid electric vehicle with rule-based energy management system," Energy, Elsevier, vol. 312(C).
    • Handle: RePEc:eee:energy:v:312:y:2024:i:c:s0360544224032213
    DOI: 10.1016/j.energy.2024.133445
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544224032213
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2024.133445?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. Yang, Bo & Zhu, Tianjiao & Zhang, Xiaoshun & Wang, Jingbo & Shu, Hongchun & Li, Shengnan & He, Tingyi & Yang, Lei & Yu, Tao, 2020. "Design and implementation of Battery/SMES hybrid energy storage systems used in electric vehicles: A nonlinear robust fractional-order control approach," Energy, Elsevier, vol. 191(C).
    3. Li, Jianwei & Yang, Qingqing & Robinson, Francis. & Liang, Fei & Zhang, Min & Yuan, Weijia, 2017. "Design and test of a new droop control algorithm for a SMES/battery hybrid energy storage system," Energy, Elsevier, vol. 118(C), pages 1110-1122.
    Full references (including those not matched with items on IDEAS)

    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. Pinthurat, Watcharakorn & Hredzak, Branislav, 2021. "Fully decentralized control strategy for heterogeneous energy storage systems distributed in islanded DC datacentre microgrid," Energy, Elsevier, vol. 231(C).
    2. Zhang, Ziyu & Ding, Tao & Zhou, Quan & Sun, Yuge & Qu, Ming & Zeng, Ziyu & Ju, Yuntao & Li, Li & Wang, Kang & Chi, Fangde, 2021. "A review of technologies and applications on versatile energy storage systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
    3. İnci, Mustafa & Büyük, Mehmet & Demir, Mehmet Hakan & İlbey, Göktürk, 2021. "A review and research on fuel cell electric vehicles: Topologies, power electronic converters, energy management methods, technical challenges, marketing and future aspects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    4. Das, Himadry Shekhar & Tan, Chee Wei & Yatim, A.H.M., 2017. "Fuel cell hybrid electric vehicles: A review on power conditioning units and topologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 268-291.
    5. Sanghyun Yun & Jinwon Yun & Jaeyoung Han, 2023. "Development of a 470-Horsepower Fuel Cell–Battery Hybrid Xcient Dynamic Model Using Simscape TM," Energies, MDPI, vol. 16(24), pages 1-22, December.
    6. Kurnia, Jundika C. & Sasmito, Agus P. & Shamim, Tariq, 2017. "Performance evaluation of a PEM fuel cell stack with variable inlet flows under simulated driving cycle conditions," Applied Energy, Elsevier, vol. 206(C), pages 751-764.
    7. Wang, Yujie & Sun, Zhendong & Chen, Zonghai, 2019. "Energy management strategy for battery/supercapacitor/fuel cell hybrid source vehicles based on finite state machine," Applied Energy, Elsevier, vol. 254(C).
    8. Liu, Xinzhi & Qi, Nanjian & Dai, Keren & Yin, Yajiang & Zhao, Jiahao & Wang, Xiaofeng & You, Zheng, 2022. "Sponge Supercapacitor rule-based energy management strategy for wireless sensor nodes optimized by using dynamic programing algorithm," Energy, Elsevier, vol. 239(PE).
    9. Hannan, M.A. & Lipu, M.S.H. & Hussain, A. & Mohamed, A., 2017. "A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: Challenges and recommendations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 834-854.
    10. Kwan, T.H. & Shen, Y. & Pei, G., 2021. "Recycling fuel cell waste heat to the thermoelectric cooler for enhanced combined heat, power and water production," Energy, Elsevier, vol. 223(C).
    11. Mohammadi, Mohammad & Noorollahi, Younes & Mohammadi-ivatloo, Behnam & Yousefi, Hossein, 2017. "Energy hub: From a model to a concept – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1512-1527.
    12. Benmouna, Amel & Becherif, Mohamed & Depernet, Daniel & Ebrahim, Mohamed A., 2018. "Novel Energy Management Technique for Hybrid Electric Vehicle via Interconnection and Damping Assignment Passivity Based Control," Renewable Energy, Elsevier, vol. 119(C), pages 116-128.
    13. Guanglin Zhang & Yu Cao & Yongsheng Cao & Demin Li & Lin Wang, 2017. "Optimal Energy Management for Microgrids with Combined Heat and Power (CHP) Generation, Energy Storages, and Renewable Energy Sources," Energies, MDPI, vol. 10(9), pages 1-18, August.
    14. Zhu, Lingfeng & Wang, Yinshun & Guo, Yuetong & Liu, Wei & Hu, Chengyang, 2023. "Current decay and compensation of a closed-loop HTS magnet in non-uniform magnetic fields based on electro-magneto-thermal semi-analytical analysis," Energy, Elsevier, vol. 277(C).
    15. Jamila Snoussi & Seifeddine Ben Elghali & Mohamed Benbouzid & Mohamed Faouzi Mimouni, 2018. "Auto-Adaptive Filtering-Based Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles," Energies, MDPI, vol. 11(8), pages 1-20, August.
    16. Zhou, Hongxu & Yu, Zhongwei & Wu, Xiaohua & Fan, Zhanfeng & Yin, Xiaofeng & Zhou, Lingxue, 2023. "Dynamic programming improved online fuzzy power distribution in a demonstration fuel cell hybrid bus," Energy, Elsevier, vol. 284(C).
    17. Xian Zhao & Siqi Wang & Xiaoyue Wang, 2018. "Characteristics and Trends of Research on New Energy Vehicle Reliability Based on the Web of Science," Sustainability, MDPI, vol. 10(10), pages 1-25, October.
    18. Wang, Yujie & Sun, Zhendong & Chen, Zonghai, 2019. "Development of energy management system based on a rule-based power distribution strategy for hybrid power sources," Energy, Elsevier, vol. 175(C), pages 1055-1066.
    19. 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.
    20. Hoque, M.M. & Hannan, M.A. & Mohamed, A. & Ayob, A., 2017. "Battery charge equalization controller in electric vehicle applications: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 1363-1385.

    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:312:y:2024:i:c:s0360544224032213. 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.