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The modeling of Lithium-ion batteries usually utilizes discrete-time system identification methods to estimate parameters of discrete models. This paper adopts direct continuous-time system identification methods to estimate the parameters of equivalent circuit models for Lithium-ion batteries. Compared with discrete-time system identification methods, the continuous-time system identification methods...
Monitoring the state-of-charge (SoC) for batteries is challenging, especially when a battery has time-varying parameters. We propose to improve SoC estimation using an adaptive strategy and multiple models in this study, developing a unique algorithm called MM-AdaSoC. Specifically, two submodels in state-space form are generated from a modified Nernst battery model. Both are shown to be locally observable...
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