Optimal adaptation of equivalent factor of equivalent consumption minimization strategy for fuel cell hybrid electric vehicles under active state inequality constraints
Optimal adaptation of equivalent factor of equivalent consumption minimization strategy for fuel cell hybrid electric vehicles under active state inequality constraints
复制标题
DOI：
10.1016/j.jpowsour.2014.05.067
复制
发表时间：
2014-12
影响因子：
9.2
通讯作者：
Jihun Han;Youngjin Park;Dongsuk Kum
中科院分区：
文献类型：
--
作者：
Jihun Han;Youngjin Park;Dongsuk Kum
在现有的燃料电池混合动力汽车（FCHEV）的能量管理策略（EMS）中，等效消耗最小化策略（ECMS）通常被认为是一种实用的方法，因为它可以实时执行，同时实现接近最优的性能。然而，在具有不确定性的现实驾驶条件下，例如丘陵道路，除非实时最优地调整等效因子（EF），否则不能保证ECMS的接近最优性和电荷维持。本文提出了一种从动态规划（DP）解中提取全局最优EF轨迹的方法，用于EF自适应策略的设计。为了说明提取方法的性能和过程中，FCHEV的能量管理问题在丘陵道路条件下的案例研究。主要目的是了解如何EF应调整和EF适应燃料经济性的影响，在几个丘陵公路的情况下。使用提取方法，DP为基础的EF计算，其性能进行了比较与庞特里亚金的最小值原则（PMP）和传统的ECMS。结果表明，最佳EF适应显着提高燃油经济性时，电池SoC约束成为活跃的，因此EF必须在严重的丘陵道路条件下进行适当的调整。
Among existing energy management strategies (EMSs) for fuel cell hybrid electric vehicles (FCHEV), the equivalent consumption minimization strategy (ECMS) is often considered as a practical approach because it can be implemented in real-time, while achieving near-optimal performance. However, under real-world driving conditions with uncertainties such as hilly roads, both near-optimality and charge-sustenance of ECMS are not guaranteed unless the equivalent factor (EF) is optimally adjusted in real-time. In this paper, a methodology of extracting the globally optimal EF trajectory from dynamic programming (DP) solution is proposed for the design of EF adaptation strategies. In order to illustrate the performance and process of the extraction method, a FCHEV energy management problem under hilly road conditions is investigated as a case study. The main goal is to learn how EF should be adjusted and the impact of EF adaptation on fuel economy under several hilly road cases. Using the extraction method, the DP-based EF is computed, and its performance is compared with those of Pontryagin's minimum principle (PMP) and conventional ECMS. The results show that the optimal EF adaptation significantly improves fuel economy when the battery SoC constraint becomes active, and thus EF must be properly adjusted under severely hilly road conditions.