考虑交通条件的PHEV中的能源管理系统的综合能源,环境和经济优化
Morteza Montazeri-Gh1, Ehsan Alimohammadi2
1Department of Mechanical Engineering, System Simulation and Control Laboratory, Iran University of Science and Technology, Tehran, Iran. montazeri@iust.ac.ir.
Scientific reports
|July 17, 2025
概括
优化插电式混合动力电动汽车 (EMS) 能源管理策略平衡了燃料消耗,排放和电池老化成本. 使用模糊逻辑控制器和遗传算法的多目标方法显示了可持续驾驶的最佳结果.
科学领域:
- 汽车工程 汽车工程
- 环境科学 环境科学
- 控制系统 控制系统
背景情况:
- 化石燃料的依赖导致环境污染和资源枯竭.
- 插电式混合动力电动汽车 (PHEV) 可降低燃油消耗和排放.
- 电池退化显著影响PHEV运营成本和性能.
研究的目的:
- 为 PHEV 能源管理策略 (EMS) 制定一个多目标优化方法.
- 尽量减少能源消耗,环境影响和电池老化成本 (E3).
- 评估EMS优化在不同目标功能场景中的表现.
主要方法:
- 使用实验数据,基于萨曼德车辆建模了一个PHEV.
- 使用遗传算法来优化组件大小.
- 为EMS开发了一个模糊逻辑控制器.
- 在五个驾驶周期中,在一个,两个和三个目标函数进行了多目标优化.
主要成果:
- 三个目标的功能优化产生了最佳的整体性能.
- 单一目标优化减少了13.5%的电池退化,但燃料消耗增加了3%.
- 双目标优化减少了10%的电池退化,同时增加了1.9%的燃料消耗和5.7%的排放.
- 三个目标的优化实现了平均减少3.3%的排放量和4.4%的电池退化,燃料消耗最低增加了0.02%.
结论:
- 多目标优化对于平衡PHEV运营目标来说是优越的.
- 开发的EMS有效地管理能源消耗,排放和电池寿命.
- 这种方法有助于更可持续和更具成本效益的PHEV运行.
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