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Cited by 663

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Fuel cell application in the automotive industry and future perspective

Olabi, A.G., Wilberforce, Tabbi, Abdelkareem, Mohammad Ali·2021·Energy

Abstract

Abstract The automotive industry remains one of the most significant contributors to total global emissions worldwide. This growing challenge is primarily attributed to the high dependency on fossil fuel as its primary source of energy. This review highlights the current state of the application of fuel cells in the automotive industry, as well as the technological advances made in comparison to the early years of the automotive sector. Future prospects of these technologies are also thoroughly reviewed. Factors impeding the advancement of these technologies while also impeding their commercialization are presented, with possible solutions to this problem also suggested. In summary, this investigation seeks to explore pragamatic approach that can be adopted to reduce the overall cost of fuel cells and their possible integration in the automotive industry.

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Crossref · 10.1016/j.energy.2020.118955

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Metadata

Authors
Olabi, A. G., Wilberforce, T., & Abdelkareem, M. A.
Venue
Energy
Publisher
Elsevier BV
Published
2021-01
Volume
214
Pages
118955
ISSN
0360-5442 (ISSN-L)
OpenAlex
W3090384029
Cited by
663
References
2
FWCI
32.58
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Fuel cell application in the automotive industry and future perspective. https://app.cochat.ai/papers/10.1016/j.energy.2020.118955
The paper
Olabi, A. G., Wilberforce, T., & Abdelkareem, M. A. (2021). Fuel cell application in the automotive industry and future perspective. Energy. https://doi.org/10.1016/j.energy.2020.118955

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.