Greener plug-in hybrid electric vehicles incorporating renewable energy and rapid system optimization

被引:139
作者
Hu, Xiaosong [1 ,2 ]
Zou, Yuan [3 ]
Yang, Yalian [1 ,2 ]
机构
[1] Chongqing Univ, State Key Lab Mech Transmiss, Chongqing 400044, Peoples R China
[2] Chongqing Univ, Coll Automot Engn, Chongqing 400044, Peoples R China
[3] Beijing Inst Technol, Dept Mech Engn, Beijing 100081, Peoples R China
基金
中国国家自然科学基金;
关键词
Plug-in hybrid electric vehicle; Component sizing; Energy management; Charging control; Optimization; Renewable energy; OPTIMAL POWER MANAGEMENT; IMPACT; BUS;
D O I
10.1016/j.energy.2016.06.037
中图分类号
O414.1 [热力学];
学科分类号
070201 [理论物理];
摘要
It is imperative to explore the full carbon dioxide-saving potential for plug-in hybrid electric vehicles. This paper seeks to examine the role of renewable energy and powertrain optimization in minimizing daily carbon emissions of plug-in hybrid electric vehicles. A spectrum of influencing factors are investigated, including charging protocol, timing, on-road power management strategy, battery size, and carbon-emission intensity of the grid. A high-efficiency convex programming framework is harnessed to optimize a plug-in hybrid powertrain. Two originally important contributions evidently distinguish this work from existing efforts. First, diverse heuristic scenarios and concomitant weaknesses are elucidated, and the carbon reductions arising from renewable energy integration and the convex programming framework are quantified. The great importance of their synergy is accentuated, i.e., swiftly adapting charging/power management controls to wind intermittency. Second, battery health implication is explored for the optimal and heuristic scenarios, via a dynamic battery State-of-Health model. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:971 / 980
页数:10
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