State-of-Charge and State-of-Health online estimation of Li-ion battery for the More Electrical Aircraft based on semi-empirical ageing model and Sigma-Point Kalman Filtering-Reference-Cited by-同舟云学术

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State-of-Charge and State-of-Health online estimation of Li-ion battery for the More Electrical Aircraft based on semi-empirical ageing model and Sigma-Point Kalman Filtering

Published:2021-04-27 Issue: Volume: Page:
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Container-title:2021 Smart Systems Integration (SSI)
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Author:

Laurin Antoine,Heiries Vincent,Montaru Maxime

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9466933/9466951/09466997.pdf?arnumber=9466997

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Recurrent Neural Networks for Estimating the State of Health of Lithium-Ion Batteries;Batteries;2024-03-20

2. Development and Comparison of Rule- and Machine Learning-Based EMS for HESS Providing Grid Services;IEEE Access;2024

3. Field programmable gate arrays implementation of a Kalman filter based state of charge observer of a lithium ion battery pack;Journal of Energy Storage;2023-10

4. A Review of DC Fast Chargers with BESS for Electric Vehicles: Topology, Battery, Reliability Oriented Control and Cooling Perspectives;Batteries;2023-02-08

5. Optimal lifetime management strategy for Self-Reconfigurable Batteries;2022 IEEE 95th Vehicular Technology Conference: (VTC2022-Spring);2022-06

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