Modeling of Li-ion batteries for real-time analysis and control: A data-driven approach
Author:
Affiliation:
1. Temple University,Dynamical Systems Lab (DSLab),Department of Mechanical Engineering,Philadelphia,PA,USA
Funder
Office of Naval Research
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9866948/9867142/09867616.pdf?arnumber=9867616
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1. Robust data-driven discovery of partial differential equations with time-dependent coefficients;chen,2021
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1. Effect of Temperature and SOC on Frequency-Response Modeling of Li-ion Batteries;2023 IEEE Conference on Control Technology and Applications (CCTA);2023-08-16
2. Analysing Performance of 2RC Equivalent Circuit Models of Li-Ion Cell for Embedded Code Generation;2023 IEEE 3rd International Conference on Sustainable Energy and Future Electric Transportation (SEFET);2023-08-09
3. Discovering Governing Equations of Li-ion Batteries Pertaining State of Charge Using Input-Output Data;2023 American Control Conference (ACC);2023-05-31
4. A Physics-Inspired Machine Learning Nonlinear Model of Li-ion Batteries;2023 American Control Conference (ACC);2023-05-31
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