Weakest cells cut EV battery pack lifetime by up to 22.8 percent

A small number of faster-ageing cells can quietly dictate the fate of an entire electric vehicle battery pack, according to a study published in Nature Energy that quantified at fleet scale how cell-to-cell inconsistency limits pack performance, lifetime, and resource utilization under real-world operating conditions. The work revealed that a few cells ageing faster than their neighbors can severely constrain an entire pack’s usable capacity, power output, and service life. The study was led by Prof. Chen Zhongwei of the Dalian Institute of Chemical Physics (DICP) of the Chinese Academy of Sciences, together with Prof. Zou Changfu of Chalmers University of Technology and researchers from Beijing Institute of Technology and Zeekr Technology Europe AB.

Electric vehicle battery packs are built from many individual cells, and no two cells are identical. Differences in raw materials, manufacturing processes, cell grouping, local temperature distribution, and everyday usage cause cells within the same pack to age at different rates. The consequence is a classic “weakest-cell” effect in series-connected packs: during charging, the lower-capacity cell hits the upper voltage limit first; during discharge and high-power operation, the higher-resistance cell reaches safety constraints earlier; and once the fastest-ageing cell crosses the retirement threshold, the whole pack may have to be taken out of service prematurely. While earlier studies relied mostly on laboratory test data, the long-term, system-level consequences of this inconsistency under actual driving conditions had not been systematically quantified until now.

To close that gap, the researchers developed a fleet-scale framework for cell-level ageing diagnosis and system-level performance evaluation. The dataset covered electric passenger cars equipped with nickel-manganese-cobalt (NMC) batteries and electric buses equipped with lithium-iron-phosphate (LFP) batteries, with vehicle operation spanning more than three years and individual vehicle mileage reaching up to 300,000 kilometers. Using the voltage, current, temperature, and state-of-charge signals routinely recorded during vehicle operation, the team combined battery model identification with neural networks to estimate the ageing trajectories of individual cell capacity and internal resistance under unified reference conditions. According to the researchers, this approach reduced the influence of seasonal variation and differences in state of charge and operating conditions, enabling more consistent comparisons of cell ageing. From these estimates, the team established six metrics covering cell state-of-health dispersion, pack health utilization, lifetime utilization, state-of-charge utilization, power capability utilization, and energy-resource utilization. In the passenger-car fleet, cell-to-cell variation in state of health remained generally small at lower mileage. However, after accumulated mileage exceeded roughly 170,000 km, individual cells in many vehicles began to enter accelerated ageing regimes, and differences among cells increased markedly, although the onset and severity varied across vehicles.

The quantified losses were substantial. Under a unified retirement threshold, cell-to-cell inconsistency reduced the usable pack-level state of health by 6.2 percent for electric passenger cars and 7.5 percent for buses. Relative to the average lifetime of the constituent cells, pack lifetime was shortened by 17.7 percent and 22.8 percent, respectively. Power capability losses caused by internal-resistance heterogeneity reached 12.9 percent and 15.1 percent. By contrast, under the charging and balancing strategies used in the studied vehicles, the impact of state-of-charge imbalance on usable charged capacity was typically below 2 percent. Taking premature retirement and state-of-charge imbalance into account, the lifetime energy-resource utilization of the passenger-car and bus battery packs was only 80.7 percent and 72.9 percent, respectively. In other words, when the weakest cell triggers the pack’s retirement criterion, approximately 19.3 percent and 27.1 percent of potential energy resources remain under-utilized. These results demonstrate that battery pack degradation cannot be evaluated solely by the average ageing level of its cells, because a few faster-ageing cells can significantly limit pack lifetime, power capability, and resource utilization.

The comparison between the two fleets also suggests that battery balancing strategies can affect how cell-to-cell inconsistency develops over the long term. According to the researchers, improving EV battery utilization therefore requires a coordinated approach covering battery manufacturing, cell grouping, and operational management. Reducing initial differences between cells and optimizing cell grouping could help prevent cell-to-cell inconsistency from becoming amplified during service, while advanced balancing control and thermal management could help reduce differences in cell ageing. Reconfigurable battery systems may provide another route to mitigating the limitations imposed by the weakest cells. “Our findings show that the performance and lifetime of an EV battery pack are not determined solely by the average ageing level of their cells, but can be strongly constrained by a small number of faster-ageing cells,” said Prof. Chen. “By quantifying this weakest-cell effect under real-world EV operation, our study provides a basis for improving battery utilization, lifetime management, and system-level optimization.”

Subject of Research: Study quantifies how cell-to-cell inconsistency constrains EV battery pack performance

Article Title: Study quantifies how cell-to-cell inconsistency constrains EV battery pack performance

Article References: Study quantifies how cell-to-cell inconsistency constrains EV battery pack performance. Original publication (Bibliographic details unavailable.)

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Keywords: quantifies, cell-to-cell, inconsistency, constrains, battery, pack, performance, scientific research