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Impact of cell variability on pack statistics for different vehicle segments

机译:不同车辆区段包装统计包统计影响的影响

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Depending on the level of electrification ([PH]EV, [M]HEV) and cell format (pouch, prismatic, cylindrical), the number of individual cells in a vehicle's battery pack can span several orders of magnitude (from tens to thousands). In this paper, we develop a novel analytical framework to investigate the impact of cell-level manufacturing variability on pack performance. Statistical distributions of pack energy and pack power are derived for any NsMp pack configurations and any level of cell-to-cell variability. These distributions are used to develop vehicle-dependent cell-level manufacturing requirements. The degree to which the series direction negatively affects pack statistics, and the degree to which the parallel direction improves pack statistics, is first quantified under a random sampling scenario. PHEV packs (96s1p) are found to have the highest pack-level statistical penalty, while EV packs made of small-format cylindrical cells (96s74p) incur virtually no statistical penalty. Pack-level statistics for Ns1p packs are shown to greatly benefit from the clustering of low-performing cells. Cell binning strategies for NsMp packs present both advantages and disadvantages. The impacts of cell aging and pack-level voltage limits are further discussed. The results of this study apply even in the presence of cell balancing and under partial SOC usage.
机译:取决于电气化水平([pH] EV,[M] HEV)和细胞格式(袋,棱柱形,圆柱形),车辆电池组中的各个单元的数量可以跨越几个数量级(从数万) 。在本文中,我们开发了一种新的分析框架,以研究细胞级制造变异性对包装性能的影响。由于任何NSMP包配置和任何级别的细胞到细胞变异性导出了包装能量和包装电源的统计分布。这些分布用于开发车辆依赖的细胞级制造要求。串联方向对包装统计的程度产生负面影响,并且并行方向改善包统计的程度,首先在随机采样方案下量化。 PHEV包(96S1P)被发现具有最高的包装级别统计损失,而MOVELACKS由小型圆柱形电池(96S74P)制成几乎没有统计罚款。 NS1P包的Pack级别统计信息显示为大量的低性能小区的聚类受益匪浅。 NSMP包的细胞排放策略呈现出色的优点和缺点。进一步讨论了细胞老化和包装级电压限制的影响。即使在细胞平衡和部分SOC使用情况下也适用于本研究的结果。

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