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                    混合動力電動汽車的跟車控制與能量管理

                    趙秀春 郭戈

                    趙秀春, 郭戈. 混合動力電動汽車的跟車控制與能量管理. 自動化學報, 2021, x(x): 1?9 doi: 10.16383/j.aas.200136
                    引用本文: 趙秀春, 郭戈. 混合動力電動汽車的跟車控制與能量管理. 自動化學報, 2021, x(x): 1?9 doi: 10.16383/j.aas.200136
                    Zhao Xiu-Chun, Guo Ge. Tracking control and energy management of hybrid electric vehicle. Acta Automatica Sinica, 2021, x(x): 1?9 doi: 10.16383/j.aas.200136
                    Citation: Zhao Xiu-Chun, Guo Ge. Tracking control and energy management of hybrid electric vehicle. Acta Automatica Sinica, 2021, x(x): 1?9 doi: 10.16383/j.aas.200136

                    混合動力電動汽車的跟車控制與能量管理

                    doi: 10.16383/j.aas.200136
                    基金項目: 國家自然科學基金(U1808205, 61573077, 61973053, 51975089, 157507), 遼寧省教育廳科學研究經費(LJYT201915)資助
                    詳細信息
                      作者簡介:

                      趙秀春:大連理工大學控制科學與工程專業博士研究生. 2006年獲東北大學機械電子專業碩士學位. 主要研究方向為車輛控制技術與混合動力電動汽車能量管理. E-mail: zxcxiu@163.com

                      郭戈:東北大學教授. 1998年獲得東北大學控制理論與控制工程專業博士學位. 主要研究方向為智能交通系統, 運動目標檢測跟蹤網絡. 本文通信作者. E-mail: geguo@yeah.net

                    Tracking Control and Energy Management of Hybrid Electric Vehicle

                    Funds: Supported by National Natural Science Foundation of P. R. China (U1808205, 61573077, 61973053, 51975089, 157507), Scientific Research Fund of Liaoning Provincial Education Department(LJYT201915)
                    More Information
                      Author Bio:

                      ZHAO Xiu-Chun Ph. D. candidate in Control Science and Engineering, Dalian University of Technology. She received her master degree from North-eastern unversity in 2006. Her main research interest is 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, moving target detection and tracking with network. Corresponding author of this paper

                    • 摘要: 混合動力電動汽車(Hybrid electric vehicles, HEVs)的能量管理問題至關重要, 而混合動力電動汽車的跟車控制不僅涉及跟車效果及安全性, 也影響著能量的高效利用. 本文將HEVs的跟車控制與能量管理相結合, 提出一種基于安全距離的HEVs車輛跟蹤與能量管理控制方法. 首先考慮了由坡度、載荷變動建立了HEVs車輛跟車系統的非線性模型, 并基于安全距離, 提出一種基于道路觀測器的動態面控制(Dynamic surface control, DSC)進行車輛跟蹤控制. 然后, 結合跟蹤控制下工況循環, 采用滾動動態規劃算法(Dynamic programming, DP)進行混合動力電動汽車能量實時優化控制. 最后, 通過仿真研究進行驗證.
                    • 圖  1  HEV控制系統

                      Fig.  1  HEV control system

                      圖  2  PSHEV功率關系

                      Fig.  2  PSHEV power flow relationship

                      圖  3  發動機燃油消耗率

                      Fig.  3  Engine fuel consumption rate map in Advisor

                      圖  4  發動機燃油消耗率-功率曲線

                      Fig.  4  Engine fuel consumption rate and power

                      圖  5  道路坡度

                      Fig.  5  Road slope

                      圖  6  HEV車輛位置

                      Fig.  6  Position profile of HEV

                      圖  7  HEV車輛速度曲線

                      Fig.  7  Velocity profile of HEV

                      圖  8  速度工況曲線

                      Fig.  8  Velocity cycle of HEV

                      圖  9  SOC變化曲線

                      Fig.  9  SOC of HEV

                      圖  10  功率分配曲線

                      Fig.  10  Power distribution of HEV

                      表  1  HEV車輛主要參數

                      Table  1  Parameters of HEV

                      參數數值單位參數數值單位
                      整車質量1332kg車輪半徑0.287m
                      重力加速度9.81N/kg迎風面積1.746m2
                      車身長度3m空氣密度1.29kg/m3
                      風阻系數0.3滾動阻力系數0.3m/s
                      下載: 導出CSV

                      表  2  燃油消耗對比

                      Table  2  Comparison of fuel consumption

                      優化方法(ECE工況)燃油消耗(l/100 km)提高(%)
                      Advisor6.3
                      本文算法4.6812
                      下載: 導出CSV
                      360彩票
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                    • 網絡出版日期:  2021-08-05

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