包含交通流信息的 PEV 的能源消耗预测
Yong Chen1,2, Zeyu Song3,4, Ruoyu Chen5
1Mechanical Electrical Engineering School, Beijing Information Science and Technology University - Qinghe Xiaoying Campus, No.12, Xiaoying East Road, Qinghe, Haidian, Beijing, 100192, China. chenyong_jz@126.com.
Scientific reports
|July 2, 2025
概括
预测纯电动汽车 (PEV) 的能源消耗可以减少距离焦虑. 这项研究引入了一种使用实时交通数据的新方法,大大提高了预测准确度.
科学领域:
- 汽车工程 汽车工程
- 能源系统 能源系统
- 运输科学 运输科学
背景情况:
- 纯电动汽车 (PEV) 的距离焦虑源于预测与实际驾驶距离的差异.
- 准确的能源消耗预测对于减轻距离焦虑和优化能源管理策略至关重要.
- 由于需要可靠的范围估计,开发PEV受到阻碍.
研究的目的:
- 分析速度,环境因素和驾驶风格对PEV能源消耗的影响.
- 为PEVs开发一个改进的能源消耗预测模型.
- 为了减少预测错误,提高驾驶距离估计的准确性.
主要方法:
- 分析PEV的现实驾驶数据,以确定关键影响因素.
- 开发一种包含实时交通信息的驾驶状况预测方法.
- 将预测方法集成到一个全面的能源消耗模型中.
主要成果:
- 提出的方法显示,预测错误的显著减少.
- 与传统方法相比,根平均平方误差 (RMSE) 减少了66.37%.
- 平均绝对百分比误差 (MAPE) 减少了68.10%.
结论:
- 新的能源消耗预测模型有效地解决了PEV中的范围焦虑.
- 实时交通数据的整合大大提高了预测准确度.
- 这些发现支持优化PEV的能源管理和路线规划.
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