Estimation strategies for state of charge and state of power of lithium-ion batteries
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Publisher
Elsevier
Reference31 articles.
1. A strong tracking adaptive fading-extended Kalman filter for the state of charge estimation of lithium-ion batteries;Takyi-Aninakwa;Int. J. Energy Res.,2022
2. Improved covariance matching–electrical equivalent modeling for accurate internal state characterization of packing lithium-ion batteries;Wang;Int. J. Energy Res.,2022
3. A novel collaborative multiscale weighting factor-adaptive Kalman filtering method for the time-varying whole-life-cycle state of charge estimation of lithium-ion batteries;Wang;Int. J. Energy Res.,2022
4. Modelling lithium-ion battery ageing in electric vehicle applications-calendar and cycling ageing combination effects;Redondo-Iglesias;Batteries-Basel,2020
5. A novel safety anticipation estimation method for the aerial lithium-ion battery pack based on the real-time detection and filtering;Wang;J. Clean. Prod.,2018
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