With the widespread popularity of electric vehicles (EV), effective assessment for retired EVs has become increasingly critical. Unlike traditional internal combustion vehicles, for EV, batteries account for a large proportion of the entire vehicle cost. Therefore, a fast battery capacity estimation method based on open-circuit voltage (OCV) estimation is forthwith proposed. The method calculates capacity using the ratio of the change in electric quantity to the corresponding change in state-of-charge (SOC), and the SOC is estimated via a fast OCV estimation method proposed in this paper. The fast test procedure includes a charging/discharging test and a short rest, which take less than 30 minutes in total and provide the data for the battery capacity estimation. For estimation, a weighted voltage relaxation model, containing two parallel resistor–capacitor (RC) components, is established. Its parameters are then optimized using the beetle antenna search algorithm with the approximate OCV range obtained in the test and an early voltage relaxation curve. The results of the experiments show that the proposed model and algorithm can accurately estimate the OCV, and the capacity estimation can be quickly realized in half an hour while limiting inaccuracy to less than 3%.

随着电动汽车（EV）的广泛普及，对退休电动汽车进行有效评估变得越来越重要。与传统的内燃机汽车不同，对于电动汽车而言，电池在整个汽车成本中所占比例很大。因此，提出了一种基于开路电压（OCV）估计的快速电池容量估计方法。该方法使用电量变化与相应充电状态变化（SOC）的比率来计算容量，并通过本文提出的快速OCV估算方法估算SOC。快速测试过程包括充电/放电测试和短暂的休息，总共耗时不到30分钟，并为估算电池容量提供了数据。为了进行估算，使用了加权电压松弛模型，建立了包含两个并联的电阻-电容器（RC）组件。然后使用甲虫天线搜索算法优化其参数，并在测试中获得近似的OCV范围和早期的电压松弛曲线。实验结果表明，所提出的模型和算法能够准确估计OCV，并且可以在半小时内快速实现容量估计，同时将不准确度限制在3％以内。