城市电气化BRT车队的最佳充电调度和车载控制,考虑合成代表性驾驶周期
Ahmed Ali1, Ahmed F Ayad2, Mostafa Asfoor3,4
1Automotive Engineering Department, Military Technical College, I. Fangari, Cairo, Cairo, 11766, Egypt. ahmed.m.ali@mtc.edu.eg.
Scientific reports
|March 6, 2024
概括
这项研究优化了使用合成驾驶周期的电动车队运营,以减少能源使用和成本. 它在车队规模,充电基础设施和运营费用方面实现了显著的节省,同时保持了驾驶能力.
科学领域:
- 电气工程 电气工程
- 运输系统 运输系统
- 运营研究 运营研究
背景情况:
- 电气化车队需要有效的充电调度和车辆控制策略.
- 现实世界的驾驶模式是复杂的,并且有很大的差异,影响车队的性能.
- 优化车队运营需要平衡能源消耗,运营成本和驾驶能力.
研究的目的:
- 开发一种全面的方法,以实现最佳的充电调度和电气化车队的车载控制.
- 为一个特定的案例研究 (开罗,埃及) 合成代表性的驾驶周期.
- 尽量减少能源消耗和运营成本,同时保持车队性能.
主要方法:
- 通过K-means集群合成了一个基于距离的代表性驾驶周期.
- 制定了两个用于充电调度和车辆控制的多目标优化问题.
- 使用非主导遗传算法II (NSGA-II) 来解决优化问题.
- 考虑了波动的电力成本和车队运营数据.
主要成果:
- 在能源消耗方面取得了19%的改善,在机载能量保留方面取得了28%的改善.
- 保持驾驶能力,减轻了不到2%的风险.
- 车队规模减少了40.8%,充电站减少了20%,年度充电成本减少了21.9%.
结论:
- 提出的综合性方法有效优化了电气化车队运营.
- 合成驾驶周期和实时电价对于定制解决方案至关重要.
- 该方法为电气化车队提供了显著的经济和环境效益.
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