在线和离线控制相结合的燃料电池有轨电车能量管理策略

doi:10.13229/j.cnki.jdxbgxb.20221593

摘要/Abstract

摘要：

燃料电池/锂电池/超级电容混合动力有轨电车全局能量管理策略中的动态规划控制效果良好，能够较好地提高燃油经济性，但是其需要先验工况、计算量大、耗时长、无法实现在线控制，针对上述问题本文提出了一种改进策略。首先，根据有轨电车历史运行数据建立马尔科夫功率状态转移矩阵，对有轨电车运行工况进行预测；其次，利用滑动窗口大量连续、无限快速观测数据的特点对有轨电车中的燃料电池功率数据进行更新，加快动态规划算法的迭代速度，并以最小氢耗量为目标函数，通过逆向求解正向寻优获得最优控制；最后，将本文策略与状态机策略、传统动态规划策略进行对比分析。结果表明：本文策略运算时间相较于传统动态规划大幅减少，有效地减少了燃料电池大电流放电的次数和幅值，提高了燃料电池的耐久性；在有轨电车实时运行过程中对主辅电源进行合理的功率分配，提高了混合动力系统的燃油经济性和平均效率。

关键词: 混合动力有轨电车, 全局优化, 工况预测, 能量管理策略

Abstract:

The dynamic programming in the global energy management strategy of fuel cell/lithium battery/supercapacitor hybrid trams is effective and can improve the fuel economy， but it requires a priori operating conditions， is computationally intensive， time-consuming， and cannot be controlled online， and an improvement strategy is proposed to address the above problems. Firstly， the Markov power state transfer matrix is established based on the historical tram operation data to predict the tram operation conditions； secondly， the fuel cell power data in the tram is updated by using the sliding window with a large number of continuous and infinitely fast observation data to speed up the iteration of the dynamic planning algorithm， and the minimum hydrogen consumption is used as the objective function to obtain the optimal control by solving the forward search in the inverse direction. Finally， the proposed strategy is compared with the state machine strategy and the traditional dynamic planning strategy. The results show that the proposed strategy significantly reduces the operation time compared with the traditional dynamic planning， effectively reduces the number and amplitude of fuel cell high-current discharges， and improves the durability of the fuel cell； the reasonable power distribution of the main and auxiliary power sources during the real-time operation of the tram improves the fuel economy and average efficiency of the hybrid system.

Key words: hybrid tram, global optimization, working condition prediction, energy management strategy

中图分类号:

TM91

高锋阳,强雅昕,高智山,徐昊,史志龙. 在线和离线控制相结合的燃料电池有轨电车能量管理策略[J]. 吉林大学学报(工学版), 2024, 54(10): 3064-3076.

Feng-yang GAO,Ya-xin QIANG,Zhi-shan GAO,Hao XU,Zhi-long SHI. Energy management strategy for fuel cell trams combining online and offline control[J]. Journal of Jilin University(Engineering and Technology Edition), 2024, 54(10): 3064-3076.

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参数	数值
驱动电机（8个）/kW	8×110
变流器/V	DC750（500~900）
轴重/t	12
列车自重/t	47
列车车体长度/mm	31 075
续驶里程/km	>40
最高运行速度/（km·h^-1）	60

参数	数值
燃料电池单体数量/个	735
燃料电池堆电压/V	540
燃料电池堆最大储氢量/kg	14
锂电池组串并联数目	114串2并
锂电池组额定电压/V	331
锂电池组最大放电电流/A	120
超级电容组串并联数量/个	11串3并
超级电容组额定电压/V	750
超级电容组最大电流/A	98（持续）；1 900（1 s）

对比指标	状态机	传统动态规划	本文策略
系统氢耗量/kg	2.87	2.65	2.29
系统效率/%	78.25	83.61	89.72
锂电池SOC始末状态差值/%	-4.8	3.5	0
超级电容SOC最大偏移率/%	31.6	10.5	9.4
燃料电池峰值电流/A	100.5	80.7	40.3

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