IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i5p1085-d1345200.html
   My bibliography  Save this article

Hydrogen-Powered Vehicles: Comparing the Powertrain Efficiency and Sustainability of Fuel Cell versus Internal Combustion Engine Cars

Author

Listed:
  • Kirill Durkin

    (Department of Electrical Engineering, Chalmers University of Technology, 41296 Göteborg, Sweden)

  • Ali Khanafer

    (Department of Electrical Engineering, Chalmers University of Technology, 41296 Göteborg, Sweden)

  • Philip Liseau

    (Department of Electrical Engineering, Chalmers University of Technology, 41296 Göteborg, Sweden)

  • Adam Stjernström-Eriksson

    (Department of Electrical Engineering, Chalmers University of Technology, 41296 Göteborg, Sweden)

  • Arvid Svahn

    (Department of Electrical Engineering, Chalmers University of Technology, 41296 Göteborg, Sweden)

  • Linnéa Tobiasson

    (Department of Electrical Engineering, Chalmers University of Technology, 41296 Göteborg, Sweden)

  • Tatiana Santos Andrade

    (Department of Electrical Engineering, Chalmers University of Technology, 41296 Göteborg, Sweden)

  • Jimmy Ehnberg

    (Department of Electrical Engineering, Chalmers University of Technology, 41296 Göteborg, Sweden)

Abstract

Due to the large quantities of carbon emissions generated by the transportation sector, cleaner automotive technologies are needed aiming at a green energy transition. In this scenario, hydrogen is pointed out as a promising fuel that can be employed as the fuel of either a fuel cell or an internal combustion engine vehicle. Therefore, in this work, we propose the design and modeling of a fuel cell versus an internal combustion engine passenger car for a driving cycle. The simulation was carried out using the quasistatic simulation toolbox tool in Simulink considering the main powertrain components for each vehicle. Furthermore, a brief analysis of the carbon emissions associated with the hydrogen production method is addressed to assess the clean potential of hydrogen-powered vehicles compared to conventional fossil fuel-fueled cars. The resulting analysis has shown that the hydrogen fuel cell vehicle is almost twice as efficient compared to internal combustion engines, resulting in a lower fuel consumption of 1.05 kg-H 2 /100 km in the WLTP driving cycle for the fuel cell vehicle, while the combustion vehicle consumed about 1.79 kg-H 2 /100 km. Regarding using different hydrogen colors to fuel the vehicle, hydrogen-powered vehicles fueled with blue and grey hydrogen presented higher carbon emissions compared to petrol-powered vehicles reaching up to 2–3 times higher in the case of grey hydrogen. Thus, green hydrogen is needed as fuel to keep carbon emissions lower than conventional petrol-powered vehicles.

Suggested Citation

  • Kirill Durkin & Ali Khanafer & Philip Liseau & Adam Stjernström-Eriksson & Arvid Svahn & Linnéa Tobiasson & Tatiana Santos Andrade & Jimmy Ehnberg, 2024. "Hydrogen-Powered Vehicles: Comparing the Powertrain Efficiency and Sustainability of Fuel Cell versus Internal Combustion Engine Cars," Energies, MDPI, vol. 17(5), pages 1-15, February.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:5:p:1085-:d:1345200
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/5/1085/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/17/5/1085/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fridtjof Unander, 2005. "Energy indicators and sustainable development: The International Energy Agency approach," Natural Resources Forum, Blackwell Publishing, vol. 29(4), pages 377-391, November.
    2. Zheng, Yuejiu & Ouyang, Minggao & Lu, Languang & Li, Jianqiu & Han, Xuebing & Xu, Liangfei & Ma, Hongbin & Dollmeyer, Thomas A. & Freyermuth, Vincent, 2013. "Cell state-of-charge inconsistency estimation for LiFePO4 battery pack in hybrid electric vehicles using mean-difference model," Applied Energy, Elsevier, vol. 111(C), pages 571-580.
    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. Hu, Lin & Hu, Xiaosong & Che, Yunhong & Feng, Fei & Lin, Xianke & Zhang, Zhiyong, 2020. "Reliable state of charge estimation of battery packs using fuzzy adaptive federated filtering," Applied Energy, Elsevier, vol. 262(C).
    2. Thanh-Tung Nguyen & Abdul Basit Khan & Younghwi Ko & Woojin Choi, 2020. "An Accurate State of Charge Estimation Method for Lithium Iron Phosphate Battery Using a Combination of an Unscented Kalman Filter and a Particle Filter," Energies, MDPI, vol. 13(17), pages 1-15, September.
    3. Karolis Andriuškevičius & Dalia Štreimikienė & Irena Alebaitė, 2022. "Convergence between Indicators for Measuring Sustainable Development and M&A Performance in the Energy Sector," Sustainability, MDPI, vol. 14(16), pages 1-23, August.
    4. Qiaohua Fang & Xuezhe Wei & Haifeng Dai, 2019. "A Remaining Discharge Energy Prediction Method for Lithium-Ion Battery Pack Considering SOC and Parameter Inconsistency," Energies, MDPI, vol. 12(6), pages 1-24, March.
    5. Bizhong Xia & Guanyong Zhang & Huiyuan Chen & Yuheng Li & Zhuojun Yu & Yunchao Chen, 2022. "Verification Platform of SOC Estimation Algorithm for Lithium-Ion Batteries of Electric Vehicles," Energies, MDPI, vol. 15(9), pages 1-20, April.
    6. Yang, Ruixin & Xiong, Rui & He, Hongwen & Mu, Hao & Wang, Chun, 2017. "A novel method on estimating the degradation and state of charge of lithium-ion batteries used for electrical vehicles," Applied Energy, Elsevier, vol. 207(C), pages 336-345.
    7. David Jacobs, 2011. "The Global Market for Liquefied Natural Gas," RBA Bulletin (Print copy discontinued), Reserve Bank of Australia, pages 17-28, September.
    8. Wang, Yujie & Zhang, Chenbin & Chen, Zonghai & Xie, Jing & Zhang, Xu, 2015. "A novel active equalization method for lithium-ion batteries in electric vehicles," Applied Energy, Elsevier, vol. 145(C), pages 36-42.
    9. Wang, Yujie & Zhang, Chenbin & Chen, Zonghai, 2015. "A method for state-of-charge estimation of Li-ion batteries based on multi-model switching strategy," Applied Energy, Elsevier, vol. 137(C), pages 427-434.
    10. Weng, Caihao & Feng, Xuning & Sun, Jing & Peng, Huei, 2016. "State-of-health monitoring of lithium-ion battery modules and packs via incremental capacity peak tracking," Applied Energy, Elsevier, vol. 180(C), pages 360-368.
    11. Oh, Ki-Yong & Epureanu, Bogdan I., 2016. "Characterization and modeling of the thermal mechanics of lithium-ion battery cells," Applied Energy, Elsevier, vol. 178(C), pages 633-646.
    12. Andong Yin & Shenchun Wu & Weihan Li & Jinfang Hu, 2019. "Analysis of Battery Reduction for an Improved Opportunistic Wireless-Charged Electric Bus," Energies, MDPI, vol. 12(15), pages 1-24, July.
    13. Bai, Guangxing & Wang, Pingfeng & Hu, Chao & Pecht, Michael, 2014. "A generic model-free approach for lithium-ion battery health management," Applied Energy, Elsevier, vol. 135(C), pages 247-260.
    14. Guoqing Luo & Yongzhi Zhang & Aihua Tang, 2023. "Capacity Degradation and Aging Mechanisms Evolution of Lithium-Ion Batteries under Different Operation Conditions," Energies, MDPI, vol. 16(10), pages 1-18, May.
    15. Chen, Haosen & Fan, Jinbao & Zhang, Mingliang & Feng, Xiaolong & Zhong, Ximing & He, Jianchao & Ai, Shigang, 2023. "Mechanism of inhomogeneous deformation and equal-stiffness design of large-format prismatic lithium-ion batteries," Applied Energy, Elsevier, vol. 332(C).
    16. Yang, WeiWei & Liu, JianGuo & Zhang, Xiang & Chen, Liang & Zhou, Yong & Zou, ZhiGang, 2017. "Ultrathin LiFePO4 nanosheets self-assembled with reduced graphene oxide applied in high rate lithium ion batteries for energy storage," Applied Energy, Elsevier, vol. 195(C), pages 1079-1085.
    17. Ye, Jiana & Chen, Haodong & Wang, Qingsong & Huang, Peifeng & Sun, Jinhua & Lo, Siuming, 2016. "Thermal behavior and failure mechanism of lithium ion cells during overcharge under adiabatic conditions," Applied Energy, Elsevier, vol. 182(C), pages 464-474.
    18. Kong, Xiangdong & Zheng, Yuejiu & Ouyang, Minggao & Li, Xiangjun & Lu, Languang & Li, Jianqiu & Zhang, Zhendong, 2017. "Signal synchronization for massive data storage in modular battery management system with controller area network," Applied Energy, Elsevier, vol. 197(C), pages 52-62.
    19. Escalante Pérez, Daynier, 2023. "Energy security in Central America: a proposal for a comprehensive estimate," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), April.
    20. Deng, Zhongwei & Hu, Xiaosong & Lin, Xianke & Che, Yunhong & Xu, Le & Guo, Wenchao, 2020. "Data-driven state of charge estimation for lithium-ion battery packs based on Gaussian process regression," Energy, Elsevier, vol. 205(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:gam:jeners:v:17:y:2024:i:5:p:1085-:d:1345200. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.