Cooperative optimization of velocity planning and energy management for connected plug-in hybrid electric vehicles

被引:25
|
作者
Liu, Yonggang [1 ,2 ]
Huang, Zhenzhen [1 ,2 ]
Li, Jie [1 ,2 ]
Ye, Ming [3 ]
Zhang, Yuanjian [4 ]
Chen, Zheng [5 ,6 ]
机构
[1] Chongqing Univ, State Key Lab Mech Transmiss, Chongqing 400044, Peoples R China
[2] Chongqing Univ, Sch Automot Engn, Chongqing 400044, Peoples R China
[3] Chongqing Univ Technol, Key Lab Adv Mfg Technol Automobile Parts, Minist Educ, Chongqing 400054, Peoples R China
[4] Queens Univ Belfast, Sir William Wright Technol Ctr, Belfast BT9 5BS, Antrim, North Ireland
[5] Kunming Univ Sci & Technol, Fac Transportat Engn, Kunming 650500, Yunnan, Peoples R China
[6] Queen Mary Univ London, Sch Engn & Mat Sci, London E1 4NS, England
基金
欧盟地平线“2020”; 国家重点研发计划; 中国国家自然科学基金;
关键词
Collaborative optimization; Energy management strategy; Iterative dynamic programming; Plug-in hybrid electric vehicles; Termination constraints; MODEL-PREDICTIVE CONTROL; CONTROL STRATEGY; FUEL-CELL; ALGORITHM; SPLIT; INFORMATION; BATTERY;
D O I
10.1016/j.apm.2021.02.033
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In this paper, a cooperative optimization strategy is proposed for velocity planning and energy management of intelligent connected plug-in hybrid electric vehicles. Based on the established vehicle model, a mathematical analytical method is investigated to convert the driving cycles from the original time based profiles to the driving distance based speed values. Then, the iterative dynamic programming is exploited to achieve the synergistic optimization in terms of speed planning and power allocation of the vehicle with the con-sideration of gear shifting limits and speed fluctuation. To meet the requirement of trip duration limitation which may be violated due to autonomous speed planning, the termi-nal driving time is constrained by adding a time adjustment factor to the cost function. The simulation results suggest that the proposed strategy attains the collaborative opti-mization with high efficiency in terms of speed planning and driving power distribution. In addition, the proposed strategy leads to significant reduction of the energy consumption cost under the constraints of allowed speed variation ranges. (c) 2021 Elsevier Inc. All rights reserved.
引用
收藏
页码:715 / 733
页数:19
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