Mai, L., Liu, M., Hao, H. et al. (13 more authors) (2025) A high-resolution dataset on electric passenger vehicle characteristics in China and the European Union. Scientific Data, 12. 1449. ISSN: 2052-4463
Abstract
China and the EU are the world’s largest Electric Vehicle (EV) markets, making it crucial to understand their electrification progress for global insights. However, previous assessments of regional EV markets often provide broad EV market characteristic estimations, but neglect critical spatial and segmental heterogeneity, thereby limiting research and policy precision. To fill such a knowledge gap, this study proposes a multi-dataset fusion approach that enables the characterization of passenger vehicle electrification progress in both China and the EU at highly resolved spatial, segmental, and powertrain levels for the year 2023. The dataset includes EV sales, market penetration, battery chemistry mix, and sales-weighted average battery capacity for all wheelbase-defined segments across 31 provinces and municipalities in China, as well as the EU27, Iceland, and Norway. It characterizes the current state of passenger vehicle electrification in China and the EU and supports further research on critical material demand estimation, decarbonization performance assessment, and related topics.
Metadata
| Item Type: | Article |
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| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | © The Author(s) 2025. This is an open access article under the terms of the Creative Commons Attribution License (CC-BY-NC-ND 4.0). |
| Dates: |
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| Institution: | The University of Leeds |
| Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) |
| Date Deposited: | 28 Jan 2026 14:50 |
| Last Modified: | 28 Jan 2026 14:50 |
| Status: | Published |
| Publisher: | Nature Research |
| Identification Number: | 10.1038/s41597-025-05770-7 |
| Related URLs: | |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:237073 |
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Licence: CC-BY-NC-ND 4.0

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