...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Applied Energy >Adaptive real-time optimal energy management strategy based on equivalent factors optimization for plug-in hybrid electric vehicle
【24h】

Adaptive real-time optimal energy management strategy based on equivalent factors optimization for plug-in hybrid electric vehicle

机译：基于等效因子优化的插电式混合动力汽车自适应实时最优能量管理策略

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Plug-in hybrid electric vehicle (PHEV) is one of the most promising products to solve the problem about air pollution and energy crisis. Considering the characteristics of urban bus route, maybe a fixed control-parameter control strategy for PHEV cannot perfectly match the complicated variation of driving conditions, and as a result the ideal vehicle fuel economy would not be obtained. Therefore, it is of great significance to develop an adaptive real-time optimal energy management strategy for PHEV by taking the segment characteristics of driving cycles into consideration. In this study, a novel energy management strategy for Plug-in hybrid electric bus (PHEB) is proposed, which optimizes the equivalent factor (EF) of each segment in the driving cycle. The proposed strategy includes an offline part and an online part. In the offline part, the driving cycles are divided into segments according to the actual positions of bus stops, the EF of each segment is optimized by linear weight particle swarm optimization algorithm with different initial states of charge (SOC). The optimization results of EF are then converted into a 2-dimensional look up table, which can be used to make real-time adjustments to online control strategy. In the online part, the optimal instantaneous energy distribution is obtained in this hybrid powertrain. Finally, the proposed strategy is verified with simulation and hardware in the loop tests, and three kinds of commonly used control strategies are adopted for comparison. Results show when the initial SOC is 90%, the fuel economy with the proposed strategy can be improved by 15.93% compared with that of baseline strategy, and when the initial SOC is 60%, this value is 16.02%. The proposed strategy may provide theoretical support for control optimization of PHEV. (C) 2017 Elsevier Ltd. All rights reserved.
机译：插电式混合动力汽车（PHEV）是解决空气污染和能源危机问题的最有前途的产品之一。考虑到城市公交路线的特点，PHEV的固定控制参数控制策略可能无法完全匹配复杂的行驶条件变化，结果将无法获得理想的车辆燃油经济性。因此，考虑驾驶循环的分段特性，为PHEV制定自适应的实时最优能量管理策略具有重要意义。在这项研究中，提出了一种新型的插电式混合动力客车（PHEB）能源管理策略，该策略优化了驾驶循环中每个路段的等效因子（EF）。提出的策略包括离线部分和在线部分。在离线部分，根据公交车站的实际位置将行驶周期划分为多个部分，并通过具有不同初始荷电状态（SOC）的线性权重粒子群优化算法对每个部分的EF进行优化。然后将EF的优化结果转换为二维查找表，该表可用于对在线控制策略进行实时调整。在在线部分中，在此混合动力总成中获得了最佳的瞬时能量分布。最后，在环路测试中通过仿真和硬件对所提出的策略进行了验证，并采用了三种常用的控制策略进行比较。结果表明，当初始SOC为90％时，与基线策略相比，所提策略的燃油经济性可提高15.93％，而当初始SOC为60％时，该值为16.02％。所提出的策略可以为PHEV的控制优化提供理论支持。 （C）2017 Elsevier Ltd.保留所有权利。

著录项

  • 来源
    《Applied Energy》 |2017年第1期|883-896|共14页
  • 作者

    Yang Chao; Du Siyu; Li Liang; You Sixong; Yang Yiyong; Zhao Yue;

  • 作者单位

    Tsinghua Univ, State Key Lab Automot Safety & Energy, Beijing 100084, Peoples R China;

    China Univ Geosci Beijing, Sch Engn & Technol, Beijing 100083, Peoples R China;

    Tsinghua Univ, State Key Lab Automot Safety & Energy, Beijing 100084, Peoples R China|Collaborat Innovat Ctr Elect Vehicles Beijing, Beijing 100084, Peoples R China;

    Tsinghua Univ, State Key Lab Automot Safety & Energy, Beijing 100084, Peoples R China;

    China Univ Geosci Beijing, Sch Engn & Technol, Beijing 100083, Peoples R China;

    Tsinghua Univ, State Key Lab Automot Safety & Energy, Beijing 100084, Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Plug-in hybrid electric vehicle; Energy management strategy; Real-time optimization; Linear weight particle swarm optimization; Driving cycle segmentation;

    机译：插电式混合动力汽车;能源管理策略;实时优化;线性权重粒子群优化;行驶周期分段;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号