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An improved algorithm for estimating key battery state parameters

When the State of Charge, State of Health, and parameters of a Lithium-ion battery are estimated simultaneously, estimation accuracy is hard to be ensured due to uncertainties in the estimation process. A sequential algorithm, which uses frequency-scale separation and estimates parameters/states sequentially by injecting currents with different frequencies, is proposed in this paper to improve estimation performance. Specifically, by incorporating a high-pass filter, the parameters can be independently characterized by injecting high-frequency and medium-frequency currents, respectively. Using the estimated parameters, battery capacity and State of Charge can then be estimated concurrently. Experimental results show that the estimation accuracy of the proposed sequential algorithm is much better than the concurrent algorithm where all parameters/states are estimated simultaneously, and the computational cost can also be reduced. Finally, experiments are conducted at different temperatures to verify the effectiveness of the proposed algorithm for varying battery capacities.

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Song, Ziyou, Jun Hou, Xuefeng Li, Xiaogang Wu, Xiaosong Hu, Heath Hofmann, Jing Sun. The sequential algorithm for combined state of charge and state of health estimation of lithium-ion battery based on active current injection. Energy 193: 116732, 2020.  https://doi.org/10.1016/j.energy.2019.116732