• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

一个用于全球电动汽车充电需求分析的城市规模且协调一致的数据集。

A City-scale and Harmonized Dataset for Global Electric Vehicle Charging Demand Analysis.

作者信息

Guo Zihan, You Linlin, Zhu Rui, Zhang Yan, Yuen Chau

机构信息

School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen, China.

Guangdong Provincial Key Laboratory of Intelligent Transportation System, School of Intelligent Systems Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China.

出版信息

Sci Data. 2025 Jul 17;12(1):1254. doi: 10.1038/s41597-025-05584-7.

DOI:10.1038/s41597-025-05584-7
PMID:40675987
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12271547/
Abstract

With increasing policy and market support for electric vehicles (EVs) worldwide, analyzing EV charging demand is crucial for jointly optimizing transportation and energy systems. However, existing public datasets typically suffer from limited global coverage, coarse temporal resolution, and narrow feature availability. Here, we present CHARGED, a city-scale and harmonized dataset for global electric vehicle charging demand analysis. CHARGED contains hourly records from April 1 to September 30, 2023, covering about 12,000 charging chargers across six representative cities on six continents, including Amsterdam, Johannesburg, Los Angeles, Melbourne, São Paulo, and Shenzhen. Each entry encompasses core charging metrics (duration, volume, electricity price, and service price) alongside rich auxiliary information (weather variables, geospatial attributes, and multi-level static descriptors). CHARGED fills existing gaps and provides standardized data with spatiotemporal features aligned and multi-source information harmonized. Technical validation shows the potential of CHARGED to support in-depth characterization of user charging demand, and to impel the study of more advanced machine learning models, especially those enabling transfer learning across diverse urban contexts.

摘要

随着全球对电动汽车(EV)的政策和市场支持不断增加,分析电动汽车充电需求对于联合优化交通和能源系统至关重要。然而,现有的公共数据集通常存在全球覆盖范围有限、时间分辨率粗糙和特征可用性狭窄的问题。在此,我们展示了CHARGED,这是一个用于全球电动汽车充电需求分析的城市规模且统一的数据集。CHARGED包含2023年4月1日至9月30日的每小时记录,涵盖六大洲六个代表性城市的约12000个充电桩,包括阿姆斯特丹、约翰内斯堡、洛杉矶、墨尔本、圣保罗和深圳。每个条目包含核心充电指标(持续时间、电量、电价和服务价格)以及丰富的辅助信息(天气变量、地理空间属性和多级静态描述符)。CHARGED填补了现有空白,并提供了时空特征对齐且多源信息统一的标准化数据。技术验证表明,CHARGED有潜力支持对用户充电需求的深入表征,并推动对更先进机器学习模型的研究,特别是那些能够在不同城市环境中实现迁移学习的模型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bc9/12271547/9d92fd4424f5/41597_2025_5584_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bc9/12271547/d22d794ab4a2/41597_2025_5584_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bc9/12271547/9d92fd4424f5/41597_2025_5584_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bc9/12271547/d22d794ab4a2/41597_2025_5584_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bc9/12271547/9d92fd4424f5/41597_2025_5584_Fig2_HTML.jpg

相似文献

1
A City-scale and Harmonized Dataset for Global Electric Vehicle Charging Demand Analysis.一个用于全球电动汽车充电需求分析的城市规模且协调一致的数据集。
Sci Data. 2025 Jul 17;12(1):1254. doi: 10.1038/s41597-025-05584-7.
2
Fast charging coordination for electric vehicles in a charging station based on heuristics and metaheuristics.基于启发式算法和元启发式算法的充电站中电动汽车快速充电协调
Sci Rep. 2025 Jul 1;15(1):21031. doi: 10.1038/s41598-025-06788-y.
3
Effects of city design on transport mode choice and exposure to health risks during and after a crisis: a retrospective observational analysis.危机期间及之后城市设计对交通方式选择和健康风险暴露的影响:一项回顾性观察分析
Lancet Planet Health. 2025 Jun;9(6):e467-e479. doi: 10.1016/S2542-5196(25)00088-9.
4
Electric vehicle attributed future air pollution alleviation: A case study in Guangdong province, China.电动汽车对未来空气污染缓解的影响:以中国广东省为例
J Environ Manage. 2025 Sep;391:126442. doi: 10.1016/j.jenvman.2025.126442. Epub 2025 Jul 4.
5
UrbanEV: An Open Benchmark Dataset for Urban Electric Vehicle Charging Demand Prediction.UrbanEV:用于城市电动汽车充电需求预测的开放基准数据集。
Sci Data. 2025 Mar 28;12(1):523. doi: 10.1038/s41597-025-04874-4.
6
High-temporal-resolution dataset of uni-, bidirectional, and dynamic electric vehicle charging profiles.单方向、双向和动态电动汽车充电曲线的高时间分辨率数据集。
Sci Data. 2025 Jul 10;12(1):1192. doi: 10.1038/s41597-025-05524-5.
7
Nairobi motorcycle transit comparison dataset: Fuel vs. electric vehicle performance tracking (2023).内罗毕摩托车运输比较数据集:燃油与电动汽车性能追踪(2023年)
Data Brief. 2025 Jun 19;61:111805. doi: 10.1016/j.dib.2025.111805. eCollection 2025 Aug.
8
A deep neural network approach for optimizing charging behavior for electric vehicle ride-hailing fleet.一种用于优化电动汽车网约车车队充电行为的深度神经网络方法。
Sci Rep. 2025 Jul 1;15(1):21451. doi: 10.1038/s41598-025-05953-7.
9
Flexibility in load demand and PHEV parameters for clean and economic microgrid operation.用于清洁且经济的微电网运行的负荷需求和插电式混合动力汽车(PHEV)参数的灵活性。
Sci Rep. 2025 Jul 2;15(1):22615. doi: 10.1038/s41598-025-07338-2.
10
Effects of consumers and health providers working in partnership on health services planning, delivery and evaluation.消费者和医疗服务提供者合作对卫生服务规划、提供和评估的影响。
Cochrane Database Syst Rev. 2021 Sep 15;9(9):CD013373. doi: 10.1002/14651858.CD013373.pub2.

本文引用的文献

1
A framework reforming personalized Internet of Things by federated meta-learning.一种通过联邦元学习对个性化物联网进行改革的框架。
Nat Commun. 2025 Apr 20;16(1):3739. doi: 10.1038/s41467-025-59217-z.
2
UrbanEV: An Open Benchmark Dataset for Urban Electric Vehicle Charging Demand Prediction.UrbanEV:用于城市电动汽车充电需求预测的开放基准数据集。
Sci Data. 2025 Mar 28;12(1):523. doi: 10.1038/s41597-025-04874-4.
3
A multiscale model for multivariate time series forecasting.一种用于多变量时间序列预测的多尺度模型。
Sci Rep. 2025 Jan 10;15(1):1565. doi: 10.1038/s41598-024-82417-4.
4
A dataset for multi-faceted analysis of electric vehicle charging transactions.电动汽车充电交易的多方面分析数据集。
Sci Data. 2024 Mar 1;11(1):262. doi: 10.1038/s41597-024-02942-9.
5
An Integrated Assessment of Emissions, Air Quality, and Public Health Impacts of China's Transition to Electric Vehicles.中国向电动汽车转型的排放、空气质量及公共健康影响的综合评估
Environ Sci Technol. 2022 Feb 16. doi: 10.1021/acs.est.1c06148.