Unmanaged hybrid battery/supercapacitor energy storage systems possess higher performance with lower cost and complexity compared to not only individual cells, but also electronically managed hybrid systems. Achieving full performance requires the understanding of the power distribution and predicting their best combinations. In this work, a semi-empirical modeling methodology is presented that can predict the current distribution and the voltage response of battery/supercapacitor hybrid systems under arbitrary charge/discharge profiles. Results are presented for the assessment of hybrid systems under real life scenarios. The key strength of the presented method is that it is free of any parametrization, fits or subjective inputs. The modeling methodology is validated with experimental measurements for two different Li-ion battery chemistries, namely Lithium Iron Phosphate and Lithium Vanadium Pentoxide, connected in parallel to wide range of supercapacitors. Finally, we outline several design rules for hybrid storage systems for different use cases.

与单个电池以及电子管理的混合系统相比，非管理混合电池/超级电容器储能系统具有更高的性能和更低的成本和复杂性。实现全部性能需要了解功率分布并预测它们的最佳组合。在这项工作中，提出了一种半经验建模方法，可以预测任意充电/放电曲线下电池/超级电容器混合系统的电流分布和电压响应。给出了在现实生活场景下评估混合系统的结果。所提出方法的关键优势在于它没有任何参数化、拟合或主观输入。该建模方法通过两种不同锂离子电池化学成分的实验测量得到验证，即磷酸铁锂和五氧化二钒锂，并联连接到各种超级电容器。最后，我们概述了针对不同用例的混合存储系统的几个设计规则。