SOC estimation based on the gas‐liquid dynamics model using particle filter algorithm
Published 2022 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
SOC
estimation based on the gas‐liquid dynamics model using particle filter algorithm
Authors
Keywords
-
Journal
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
Volume -, Issue -, Pages -
Publisher
Wiley
Online
2022-09-19
DOI
10.1002/er.8594
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- An extended Kalman filter based SOC estimation method for Li-ion battery
- (2022) Zhenjie Cui et al. Energy Reports
- A cubature Kalman filter for online state-of-charge estimation of lithium-ion battery using a gas-liquid dynamic model
- (2022) Huanhuan Li et al. Journal of Energy Storage
- Online State-of-Charge Estimation Based on the Gas–Liquid Dynamics Model for Li(NiMnCo)O2 Battery
- (2021) Haobin Jiang et al. Energies
- State-of-charge estimation of lithium-ion batteries from a gas-liquid dynamics model including the direct temperature input
- (2021) Haobin Jiang et al. Journal of Energy Storage
- Model based state-of-energy estimation for LiFePO4 batteries using unscented particle filter
- (2020) Jiaqing Chang et al. Journal of Power Electronics
- A new gas–liquid dynamics model towards robust state of charge estimation of lithium-ion batteries
- (2020) Biao Chen et al. Journal of Energy Storage
- Particle filter-based state-of-charge estimation and remaining-dischargeable-time prediction method for lithium-ion batteries
- (2019) Zonghai Chen et al. JOURNAL OF POWER SOURCES
- Battery charge equalization controller in electric vehicle applications: A review
- (2017) M.M. Hoque et al. RENEWABLE & SUSTAINABLE ENERGY REVIEWS
- Influence of different open circuit voltage tests on state of charge online estimation for lithium-ion batteries
- (2016) Fangdan Zheng et al. APPLIED ENERGY
- Kalman filter for onboard state of charge estimation and peak power capability analysis of lithium-ion batteries
- (2016) Guangzhong Dong et al. JOURNAL OF POWER SOURCES
- Lyapunov-Based Adaptive State of Charge and State of Health Estimation for Lithium-Ion Batteries
- (2015) Hicham Chaoui et al. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
- A Bayesian approach for Li-Ion battery capacity fade modeling and cycles to failure prognostics
- (2015) Jian Guo et al. JOURNAL OF POWER SOURCES
- A method for state-of-charge estimation of LiFePO 4 batteries at dynamic currents and temperatures using particle filter
- (2015) Yujie Wang et al. JOURNAL OF POWER SOURCES
- State of charge estimation of lithium-ion batteries using the open-circuit voltage at various ambient temperatures
- (2013) Yinjiao Xing et al. APPLIED ENERGY
- A novel approach for state of charge estimation based on adaptive switching gain sliding mode observer in electric vehicles
- (2013) Xiaopeng Chen et al. JOURNAL OF POWER SOURCES
- Online estimation of internal resistance and open-circuit voltage of lithium-ion batteries in electric vehicles
- (2011) Yi-Hsien Chiang et al. JOURNAL OF POWER SOURCES
Find the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
SearchAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started