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混合动力电动汽车能量管理策略研究综述

赵秀春 郭戈

赵秀春, 郭戈. 混合动力电动汽车能量管理策略研究综述. 自动化学报, 2016, 42(3): 321-334. doi: 10.16383/j.aas.2016.c150477
引用本文: 赵秀春, 郭戈. 混合动力电动汽车能量管理策略研究综述. 自动化学报, 2016, 42(3): 321-334. doi: 10.16383/j.aas.2016.c150477
ZHAO Xiu-Chun, GUO Ge. Survey on Energy Management Strategies for Hybrid Electric Vehicles. ACTA AUTOMATICA SINICA, 2016, 42(3): 321-334. doi: 10.16383/j.aas.2016.c150477
Citation: ZHAO Xiu-Chun, GUO Ge. Survey on Energy Management Strategies for Hybrid Electric Vehicles. ACTA AUTOMATICA SINICA, 2016, 42(3): 321-334. doi: 10.16383/j.aas.2016.c150477

混合动力电动汽车能量管理策略研究综述

doi: 10.16383/j.aas.2016.c150477
基金项目: 

国家自然科学基金 61273107

国家自然科学基金 61174060

国家自然科学基金 51305065

中央高校自主基金 DC201502010407

中央高校自主基金 3132013334

详细信息
    作者简介:

    赵秀春 大连理工大学博士研究生.2006年获得东北大学机械工程与自动化学院机械电子专业硕士学位.主要研究方向为车辆控制技术.E-mail:zxc_xiu@163.com

    通讯作者:

    郭戈 大连海事大学教授.1998年获得东北大学控制理论与控制工程专业博士学位.主要研究方向为网络控制理论, 程控制, 车辆协同控制, 移动机器人控制.本文通信作者.E-mail:geguo@yeah.net

Survey on Energy Management Strategies for Hybrid Electric Vehicles

Funds: 

National Natural Science Foundation of China 61273107

National Natural Science Foundation of China 61174060

National Natural Science Foundation of China 51305065

Fundamental Research Funds for the Central Universities DC201502010407

Fundamental Research Funds for the Central Universities 3132013334

More Information
    Author Bio:

    Ph.D. candidate at the School of Control Science and Engineering, Dalian University of Technology. She received her master degree from Northeastern University in 2006. Her main research interest is vehicle control technology. E-mail:

    Corresponding author: GUO Ge Professor at Dalian Maritime University. He received his Ph.D. degree from Northeastern University in 1998. His research interest covers networked control system theory, process control, vehicular cooperative control, and mobile robot control. Corresponding author of this paper. E-mail:geguo@yeah.net
  • 摘要: 能量管理对于提高混合动力电动汽车(Hybrid electric vehicles, HEVs)的燃油经济性、驾驶性能及减少排放具有至关重要的作用.本文对混合动力电动汽车能量管理问题的研究进展及现状进行了全面总结, 从不同角度对混合动力电动汽车的能量管理问题进行描述, 并对主要能量管理策略进行了分析和对比研究, 指出各种控制方法的优点及其存在的问题与不足, 最后对混合动力电动汽车能量管理策略研究的未来发展方向进行了展望.
  • 图  1  混合动力电动汽车能量管理策略划分

    Fig.  1  Energy management strategies overview for HEV

    表  1  能量管理策略性能对比

    Table  1  Performance comparison of various energy management strategies

    性能 确定规则 模糊逻辑规则 全局优化 瞬时优化
    优点 算法简单、易于实现 不依赖于模型的精确度, 具有较强的鲁棒性与适应性 具有理想的优化性能, 能够实现全局优化, 常用于其他算法的性能评估 通常不受循环工况的制约, 计算量少, 可用于实时控制, 能够实现瞬时能量最优
    缺点 依赖于经验和静态数据, 不能适应工况变化和负载的动态变化, 无法保证最优控制 模糊规则的制定依赖于经验, 无法保证全局最优 通常都依赖于工况循环, 算法的计算量较大, 不利于实时控制, 因此具有一定的局限性 无法保证全局最优
    下载: 导出CSV
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  • 收稿日期:  2015-08-05
  • 录用日期:  2016-01-15
  • 刊出日期:  2016-03-01

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