发表机构
State Key Laboratory of Heavy Oil Processing, China University of Petroleum (Beijing); Zhonghai Energy Storage Technology (Beijing) Co., Ltd.（中国石油大学（北京）重质油国家重点实验室; 中海储能科技（北京）有限公司）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究针对工业级33kW铁铬液流电池，提出FlowBD-E1框架，通过早期循环数据预测全周期充电轨迹，其递归潜变量预测策略实现低误差，为液流电池健康管理提供长时程诊断信号。
AI 中文摘要
长时程固定式储能需要能在容量出现显著损失前检测到其衰减的电池。铁铬氧化还原液流电池因使用储量丰富且低成本的活性物质而颇具吸引力，但其运行受缓慢的铬动力学、析氢、膜渗透及电解质失衡等过程影响。这些耦合过程会逐渐改变完整充电电压/电流（V/I）轨迹，但多数电池预后研究要么聚焦于锂离子电池，要么将老化压缩为标量容量和健康状态（SOH）标签。本研究针对一款工业级33kW铁铬氧化还原液流电池，提出FlowBD-E1——一种早期循环生成式预测框架，仅通过最初几个循环即可预测完整的未来充电V/I轨迹。该模型结合了多尺度卷积编码器、生命周期Transformer和感知年龄的FiLM解码器，我们对比了三种部署策略：单步潜变量外推（SLE）、递归潜变量预测（RLF）和教师强制更新（TFU）。在289个循环中使用前9个循环时，RLF在剩余生命周期内实现了0.731%的联合V/I平均绝对百分比误差（MAPE），且SOH估计的MAPE低于1%。消融实验和独立序列测试表明，该感知年龄的生成式架构优于LSTM和TCN基线，在工业验证下仍保持亚百分比误差。这些结果表明，早期循环轨迹生成可将短期调试记录转化为液流电池管理的长时程诊断信号。
英文摘要
Long-duration stationary energy storage requires batteries whose degradation can be detected before substantial capacity loss has accumulated. Iron-chromium redox flow batteries are attractive for this role because they use abundant and low-cost active species, yet their operation is shaped by slow chromium kinetics, hydrogen evolution, membrane crossover and electrolyte imbalance. These coupled processes gradually reshape the full charge voltage/current (V/I) trajectory, but most battery prognostic studies either focus on lithium-ion cells or compress ageing into scalar capacity and state-of-health (SOH) labels. Here we study an industrial 33 kW Fe-Cr redox flow battery and introduce FlowBD-E1, an early-cycle generative forecasting framework that predicts complete future charge V/I trajectories from only the first few cycles. The model combines a multi-scale convolutional encoder, a lifecycle Transformer and an age-aware FiLM decoder, and we compare three deployment strategies: single-step latent extrapolation (SLE), recursive latent forecasting (RLF) and teacher-forced updating (TFU). Using the first 9 of 289 cycles, RLF achieved a joint V/I mean absolute percentage error (MAPE) of 0.731% over the remaining lifecycle and produced SOH estimates below 1% MAPE. Ablation and independent-sequence tests showed that the age-aware generative architecture outperformed LSTM and TCN baselines and retained sub-percent errors under industrial validation. These results suggest that early-cycle trajectory generation can turn a short commissioning record into a long-horizon diagnostic signal for flow-battery management.
