AI 中文总结
研究在电池异质性和筛选不确定性下退役锂离子电池组的最优组装问题，提出含拓扑筛选阶段的鲁棒优化框架，通过混合整数线性规划选择电池并分配，经实验验证该方法能满足可行性要求，相比单指标基线大幅降低归一化失配目标。
AI 中文摘要
退役电动汽车电池供应增加为二次利用的固定储能带来机遇，但将异质退役电池组装成可靠电池组具有挑战性。本文提出一种用于二次利用电池组对电池组装的鲁棒优化框架。拓扑筛选阶段先识别满足逆变器和能量需求的最小电池串并联配置，降低后续分配问题维度。对于每个候选拓扑，通过混合整数线性规划选择电池并沿串联串分配，将功率、电压和能量需求作为硬约束，同时最小化直流内阻、容量和自放电不平衡的归一化加权和。此外，将容量和直流内阻的测量不确定性建模为有界区间，以保证在最坏参数偏差下的可行性。该框架在四个异质库存上针对10kW/10kWh固定备用应用进行评估。所提方法在每种情况下都满足所有可行性要求，而单指标排序启发式算法在至少一个库存上失败。相对于按目标值的最佳单指标基线，它将归一化失配目标降低76 - 87%，表明联合优化电池匹配与应用级可行性要求可改善筛选不确定性下的异质二次利用电池组装。
英文摘要
The growing supply of retired electric vehicle batteries presents an opportunity for second-life stationary energy storage, but assembling heterogeneous retired cells into reliable packs is challenging due to substantial variation in capacity, DC internal resistance (DCIR), and self-discharge. This paper proposes a robust optimization framework for cell-to-pack assembly of second-life batteries. A topology-screening stage first identifies minimum-cell series-parallel configurations satisfying inverter and energy requirements, reducing the dimensionality of the subsequent assignment problem. For each candidate topology, a mixed-integer linear program selects cells and assigns them along the series string, enforcing power, voltage, and energy requirements as hard constraints while minimizing a normalized, weighted sum of DCIR spread, capacity spread, and self-discharge imbalance. Additionally, measurement uncertainty in capacity and DCIR is modeled as bounded intervals to guarantee feasibility under worst-case parameter deviations. The framework is evaluated on four heterogeneous inventories for a 10 kW/10 kWh stationary backup application. The proposed method satisfies all feasibility requirements in every case, while single-metric sorting heuristics each fail on at least one inventory. Relative to the best single-metric baseline by objective value, it reduces the normalized mismatch objective by 76-87%, demonstrating that jointly optimizing cell matching with application-level feasibility requirements improves heterogeneous second-life pack assembly under screening uncertainty.
