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混合动力电动汽车的跟车控制与能量管理

赵秀春 郭戈

赵秀春, 郭戈. 混合动力电动汽车的跟车控制与能量管理. 自动化学报, 2022, 48(1): 162−170 doi: 10.16383/j.aas.c200136
引用本文: 赵秀春, 郭戈. 混合动力电动汽车的跟车控制与能量管理. 自动化学报, 2022, 48(1): 162−170 doi: 10.16383/j.aas.c200136
Zhao Xiu-Chun, Guo Ge. Tracking control and energy management of hybrid electric vehicles. Acta Automatica Sinica, 2022, 48(1): 162−170 doi: 10.16383/j.aas.c200136
Citation: Zhao Xiu-Chun, Guo Ge. Tracking control and energy management of hybrid electric vehicles. Acta Automatica Sinica, 2022, 48(1): 162−170 doi: 10.16383/j.aas.c200136

混合动力电动汽车的跟车控制与能量管理

doi: 10.16383/j.aas.c200136
基金项目: 国家自然科学基金(U1808205, 61573077, 61973053, 51975089, 51575079), 辽宁省教育厅科学研究经费(LJYT201915)资助
详细信息
    作者简介:

    赵秀春:大连民族大学讲师, 大连理工大学控制科学与工程专业博士研究生. 2006年获得东北大学硕士学位. 主要研究方向为车辆控制技术, 混合动力电动汽车能量管理. E-mail: zxc_xiu@163.com

    郭戈:东北大学教授. 1998年获得东北大学博士学位. 主要研究方向为智能交通系统, 运动目标检测跟踪网络. 本文通信作者. E-mail: geguo@yeah.net

Tracking Control and Energy Management of Hybrid Electric Vehicles

Funds: Supported by National Natural Science Foundation of China (U1808205, 61573077, 61973053, 51975089, 51575079), and Scientific Research Fund of Liaoning Provincial Education Department (LJYT201915)
More Information
    Author Bio:

    ZHAO Xiu-Chun Lecturer at Dalian Minzu University, Ph. D. candidate at Control Science and Engineering, Dalian University of Technology. She received her master degree from Northeastern Unversity in 2006. Her research interest covers vehicle control technology, and hybrid electric vehicle energy management

    GUO Ge Professor at Northeastern University. He received his Ph. D. degree from Northeastern University in 1998. His research interest covers intelligent transportation system, and moving target detection and tracking with network. Corresponding author of this paper

  • 摘要: 混合动力电动汽车(Hybrid electric vehicles, HEVs)的能量管理问题至关重要, 而混合动力电动汽车的跟车控制不仅涉及跟车效果与安全性, 也影响着能量的高效利用. 将HEVs的跟车控制与能量管理相结合, 提出一种基于安全距离的HEVs车辆跟踪与能量管理控制方法. 首先, 考虑坡度、载荷变动建立了HEVs车辆跟车系统的非线性模型, 并基于安全距离, 提出一种基于道路观测器的动态面控制(Dynamic surface control, DSC)进行车辆跟踪控制. 然后, 结合跟踪控制下工况循环, 采用滚动动态规划(Dynamic programming, DP)算法进行混合动力电动汽车能量实时优化控制. 最后, 通过仿真研究进行验证.
  • 图  1  HEV控制系统

    Fig.  1  HEV control system

    图  2  Power-split HEV功率关系

    Fig.  2  Power-split HEV power relationship

    图  3  发动机燃油消耗率

    Fig.  3  Engine fuel consumption rate map in Advisor

    图  4  发动机燃油消耗率−功率曲线

    Fig.  4  Engine fuel consumption rate and power

    图  5  道路坡度

    Fig.  5  Road slope

    图  6  HEV车辆位置

    Fig.  6  Position profile of HEV

    图  7  HEV车辆速度曲线

    Fig.  7  Velocity profile of HEV

    图  8  速度工况曲线

    Fig.  8  Velocity cycle of HEV

    图  9  SOC变化曲线

    Fig.  9  SOC of HEV

    图  10  功率分配曲线

    Fig.  10  Power distribution of HEV

    表  1  HEV车辆主要参数

    Table  1  Parameters of HEV

    参数数值单位参数数值单位
    整车质量1332kg车轮半径0.287m
    重力加速度9.81N/kg迎风面积1.746m2
    车身长度3m空气密度1.29kg/m3
    风阻系数0.3滚动阻力系数0.3m/s
    下载: 导出CSV

    表  2  燃油消耗对比

    Table  2  Comparison of fuel consumption

    优化方法 (ECE 工况)燃油消耗 (l/100 km)提高 (%)
    Advisor6.3
    本文算法4.6812
    下载: 导出CSV
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出版历程
  • 收稿日期:  2020-03-16
  • 网络出版日期:  2021-08-05
  • 刊出日期:  2022-01-25

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