@inproceedings{a36066a79e8049c6922661e2447cb254,
title = "State-of-Health Estimation of Satellite Lithium-Ion Batteries Using Improved Particle Filtering",
abstract = "A strategy is investigated for the state-of-health estimation of satellite lithium-ion batteries. It can be executed in-orbit by the improved particle filtering in this paper. The monitoring model is first obtained by incorporating the related electrochemical models and regression models of lithium-ion battery. Then the model is converted into the dynamic system form in order to apply the particle filtering estimation. Furthermore, an improved particle filtering algorithm is developed by using the grid-search-cross-validation and the support-vector-regression particle filtering techniques. Thus the online estimation can be executed from the monitoring data (charge and discharge cycles) in space. The simulative results demonstrate the validity of the proposed method by using the data from NASA Ames Prognostics Center of Excellence.",
keywords = "battery capacity, charge and discharge cycle, particle filtering, satellite lithium-ion batteries, state-of-health",
author = "Dengfeng Zhang and Weichen Li and Xiaodong Han and Cuimei Bo and Quanling Zhang and Lei Qiao",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 CAA Symposium on Fault Detection, Supervision, and Safety for Technical Processes, SAFEPROCESS 2021 ; Conference date: 17-12-2021 Through 18-12-2021",
year = "2021",
doi = "10.1109/SAFEPROCESS52771.2021.9693636",
language = "英语",
series = "2021 CAA Symposium on Fault Detection, Supervision, and Safety for Technical Processes, SAFEPROCESS 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2021 CAA Symposium on Fault Detection, Supervision, and Safety for Technical Processes, SAFEPROCESS 2021",
address = "美国",
}
