轻型电动汽车的可持续电力管理与混合动力储能和机器学习控制
R Punyavathi1, A Pandian1, Arvind R Singh2
1Department of EEE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, 522302, India.
Scientific reports
|March 7, 2024
概括
本研究介绍了一种用于轻型电动汽车 (LEV) 的可持续电力管理系统,该系统使用混合能源存储解决方案和机器学习. 它优化了可再生能源的使用,并提高了车辆的性能,以实现高效的电动移动.
科学领域:
- 电气工程 电气工程
- 可再生能源系统可再生能源系统
- 交通运输中的人工智能
背景情况:
- 传统的电动汽车电力管理系统面临着仅用电池存储的局限性.
- 整合可再生能源对于提高电动移动的可持续性至关重要.
- 需要先进的控制策略来优化能源利用和车辆性能.
研究的目的:
- 开发和评估轻型电动汽车 (LEV) 的可持续电力管理系统.
- 将混合储能解决方案 (HESS) 与光伏 (PV) 面板和超级电容器集成.
- 实现机器学习 (ML) 增强的控制,以优化动力共享和车辆动态.
主要方法:
- 设计了一个混合储能解决方案 (HESS),结合了电池,超级电容器和光伏电池板.
- 一个基于机器学习 (ML) 的控制算法被开发来管理功率流和电压调节.
- 系统的性能通过模拟评估,重点关注直流总线电压稳定性,扭矩波动和短暂响应.
主要成果:
- ML增强的HESS实现了严格的直流总线电压调节,只有2.7%的偏差.
- 超级电容器有效地管理了快速负载功率变化,而电池则处理了较慢的需求.
- 该系统显著减少了扭矩波动和快速过渡响应时间,包括有效的转速逆转处理.
结论:
- 拟议的可持续电力管理系统为轻型电动汽车提供了强大而高效的解决方案.
- 集成HESS和ML控制优化了可再生能源的利用,并提高了车辆的性能.
- 这种方法为更加可持续,可扩展和先进的电动移动解决方案铺平了道路.
关键词:
混合能源储能解决方案 混合能源储能解决方案轻型电动汽车 轻型电动汽车机器学习是机器学习.太阳能电池和电池的接口在 SRM EV 驱动器上.太阳能电动汽车 太阳能电动汽车超级电容器的超级电容器是什么可持续的电力管理更多相关视频
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