A hybrid data-driven method optimized by physical rules for online state collaborative estimation of lithium-ion batteries

Closed-loop optimization of fast-charging protocols for batteries with machine learning

Peter M. Attia, Aditya Grover, Norman Jin et al. · Nature · 2020 · 1.1K citations · Full text

Engineering, Computer Science, Electrochemical Engineering +15

Predicting the state of charge and health of batteries using data-driven machine learning

Man‐Fai Ng, Jin Zhao, Qingyu Yan et al. · Nature Machine Intelligence · 2020 · 743 citations · Full text

Engineering, Computer Science, Materials Science +12

Electric Vehicles Batteries: Requirements and Challenges

Jie Deng, Chulheung Bae, Adam Denlinger et al. · Joule · 2020 · 721 citations · Full text

Engineering, Automotive Engineering, Electrical Engineering +12

Overview of model-based online state-of-charge estimation using Kalman filter family for lithium-ion batteries

Prashant Shrivastava, Mohd Yamani Idna Idris, Saad Mekhilef · Renewable and Sustainable Energy Reviews · 2019 · 681 citations

Engineering, Chemical Engineering, Systems Engineering +16

The Co-estimation of State of Charge, State of Health, and State of Function for Lithium-Ion Batteries in Electric Vehicles

Ping Shen, Minggao Ouyang, Languang Lu et al. · IEEE Transactions on Vehicular Technology · 2017 · 528 citations

Engineering, Automotive Engineering, Systems Engineering +17