燃料效率
汽车工程
卡车
汽车工业
动态规划
最优控制
行驶循环
混合动力汽车
能源管理
混合动力
工程类
电源管理
计算机科学
发动机功率
功率(物理)
电动汽车
控制工程
数学优化
航空航天工程
能量(信号处理)
物理
统计
量子力学
数学
算法
作者
Chan-Chiao Lin,Huei Peng,Jessy W. Grizzle,Jun-Mo Kang
标识
DOI:10.1109/tcst.2003.815606
摘要
Hybrid vehicle techniques have been widely studied recently because of their potential to significantly improve the fuel economy and drivability of future ground vehicles. Due to the dual-power-source nature of these vehicles, control strategies based on engineering intuition frequently fail to fully explore the potential of these advanced vehicles. In this paper, we present a procedure for the design of a near-optimal power management strategy. The design procedure starts by defining a cost function, such as minimizing a combination of fuel consumption and selected emission species over a driving cycle. Dynamic programming (DP) is then utilized to find the optimal control actions including the gear-shifting sequence and the power split between the engine and motor while subject to a battery SOC-sustaining constraint. Through analysis of the behavior of DP control actions, near-optimal rules are extracted, which, unlike DP control signals, are implementable. The performance of this power management control strategy is studied by using the hybrid vehicle model HE-VESIM developed at the Automotive Research Center of the University of Michigan. A tradeoff study between fuel economy and emissions was performed. It was found that significant emission reduction could be achieved at the expense of a small increase in fuel consumption.
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