一个具有多维特征的高分辨率电动汽车充电交易数据集在中国
Yuanshi Zhang1,2, Tongxin Xu1,2, Tao Chen1,2
1School of Electrical Engineering, Southeast University, Nanjing, 210096, China.
Scientific data
|April 16, 2025
概括
本研究介绍了来自中国的全面实时电动汽车 (EV) 充电数据集. 这些数据解决了现有数据集的局限性,使得可以更好地分析电动汽车用户行为和充电基础设施规划.
科学领域:
- 电动汽车技术 电动汽车技术
- 运输系统分析 运输系统分析
- 数据科学数据科学数据科学
背景情况:
- 现有的电动汽车 (EV) 充电交易数据集存在不完整性,偏见和缺乏实时信息的问题.
- 隐私问题和复杂的经销商关系阻碍了创建全面的收费数据.
- 准确的充电数据对于理解市场动态和制定有效的电动汽车政策至关重要.
研究的目的:
- 创建实时电动汽车 (EV) 充电交易数据集,解决现有数据的局限性.
- 为分析电动汽车用户行为和充电模式提供丰富的数据集.
- 支持电动汽车充电设施规划,管理和经济评估方面的研究.
主要方法:
- 在两年内,从中国的13个充电站收集了441,077个充电交易.
- 包括有关充电时间,价格,状态,终止原因和天气条件的详细数据.
- 确保实时数据收集以克服现有的数据集缺陷.
主要成果:
- 开发了一个新的,实时的电动汽车充电交易数据集.
- 数据集捕获了细微的用户行为和充电故障因素.
- 提供了EV充电中高级分析的基础.
结论:
- 新的数据集增强了对电动汽车充电市场动态和用户行为的研究.
- 有助于改进电动汽车充电设施的规划和管理策略.
- 支持对电动汽车充电服务进行更准确的经济评估.
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