论文标题
锂离子电池库参数的实时自适应估计
Real Time Adaptive Estimation of Li-ion Battery Bank Parameters
论文作者
论文摘要
本文提出了基于400 V Li-Ion电池组的基于准确有效的通用自适应稳定剂（UAS）的在线参数估计技术。电池开路电压，建模瞬态响应的参数以及串联电阻都在单个实时测试中估计。与早期基于UAS的单个电池组的工作相反，此工作不需要事先离线实验或任何后处理。实时快速收敛参数的估计值最少的实验努力使电池参数在运行时可以自我更新。提出的策略已通过数学验证，其性能在400 V，6.6 AH Li-Ion电池库中为感应电机驱动的原型电动汽车（EV）牵引系统提供动力。
This paper proposes an accurate and efficient Universal Adaptive Stabilizer (UAS) based online parameters estimation technique for a 400 V Li-ion battery bank. The battery open circuit voltage, parameters modeling the transient response, and series resistance are all estimated in a single real-time test. In contrast to earlier UAS based work on individual battery packs, this work does not require prior offline experimentation or any post-processing. Real time fast convergence of parameters' estimates with minimal experimental effort enables self-update of battery parameters in run-time. The proposed strategy is mathematically validated and its performance is demonstrated on a 400 V, 6.6 Ah Li-ion battery bank powering the induction motor driven prototype electric vehicle (EV) traction system.
