Online extremum seeking-based optimized energy management strategy for hybrid electric tram considering fuel cell degradation
Online extremum seeking-based optimized energy management strategy for hybrid electric tram considering fuel cell degradation
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DOI：
10.1016/j.apenergy.2021.116505
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发表时间：
2021-01-21
期刊：
影响因子：
11.2
通讯作者：
Gao, Fei
中科院分区：
文献类型：
--
作者：
Li, Qi;Wang, Tianhong;Gao, Fei
为了实现混合动力有轨电车中质子交换膜燃料电池与超级电容器之间的最优功率分配，提出了一种基于在线寻极值的能量优化管理策略.考虑到燃料电池是一个复杂的非线性系统，其性能会随着外部参数的变化而发生变化，因此有必要考虑电堆的性能状态。研究了一种在线极值搜索算法，通过搜索燃料电池性能的变化来寻求最大功率和最大效率点。此外，本文还根据在线极值搜索的结果更新了“安全工作区”。这个过程是通过自适应递归最小二乘算法来实现的。此外，为了限制燃料电池的功率动态，在本研究中考虑了电池堆的退化。为了保证电车的稳定持续运行，超级电容器的荷电状态波动范围也受到限制。在混合动力电动有轨电车缩比试验平台上进行的缩比工况下，成功验证了所提方法的有效性。所提出的方法还比较了状态机控制和等效消耗最小化策略，以进一步证明它具有优势，在氢消耗，充电状态波动，效率，和燃料电池输出功率动态。
In order to realize optimal power distribution between proton exchange membrane fuel cell and supercapacitor in hybrid electric tram, an online extremum seeking-based optimized energy management strategy is proposed in this work. Considering that the fuel cell is a complex nonlinear system, its performance will vary as the external parameters change, so it is necessary to consider the performance state of stack. An online extremum seeking algorithm is investigated in this work to seek the maximum power and maximum efficiency points by searching the variation in fuel cell performance. Besides, this work also updates its "safe operating zone" based on the results of the online extremum seeking. This process is achieved by the adaptive recursive least square algorithm. Furthermore, in order to limit the power dynamic of fuel cell, the degradation of the stack is considered in this study. To guarantee the stable and continued operation of the electric tram, the state of charge fluctuation range of supercapacitor is also limited. The effectiveness of the presented method is successfully verified under scaleddown operating condition of hybrid electric tram on the reduced-scale test platform. The proposed method is also compared with state machine control and equivalent consumption minimization strategy to further demonstrate that it has advantages in hydrogen consumption, state of charge fluctuation, efficiency, and fuel cell output power dynamics.