State-of-health estimators coupled to a random forest approach for lithium-ion battery aging factor ranking
Published 2020 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
State-of-health estimators coupled to a random forest approach for lithium-ion battery aging factor ranking
Authors
Keywords
Li-ion battery, SoH estimation, Aging factors ranking, Machine learning, Random forest
Journal
JOURNAL OF POWER SOURCES
Volume 484, Issue -, Pages 229154
Publisher
Elsevier BV
Online
2020-11-26
DOI
10.1016/j.jpowsour.2020.229154
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Remaining useful life prediction of lithium-ion battery based on improved cuckoo search particle filter and a novel state of charge estimation method
- (2020) Xianghui Qiu et al. JOURNAL OF POWER SOURCES
- State-of-health estimation of lithium-ion battery based on fractional impedance model and interval capacity
- (2020) Qingxia Yang et al. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
- The potential of Li-ion batteries in ECOWAS solar home systems
- (2019) Boucar Diouf et al. Journal of Energy Storage
- Remaining useful life prediction of lithium-ion batteries based on false nearest neighbors and a hybrid neural network
- (2019) Guijun Ma et al. APPLIED ENERGY
- Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review
- (2019) Yi Li et al. RENEWABLE & SUSTAINABLE ENERGY REVIEWS
- Developing a real-time data-driven battery health diagnosis method, using time and frequency domain condition indicators
- (2019) S. Khaleghi et al. APPLIED ENERGY
- Deep convolutional neural networks with ensemble learning and transfer learning for capacity estimation of lithium-ion batteries
- (2019) Sheng Shen et al. APPLIED ENERGY
- Synchronous estimation of state of health and remaining useful lifetime for lithium-ion battery using the incremental capacity and artificial neural networks
- (2019) Shuzhi Zhang et al. Journal of Energy Storage
- Satellite lithium-ion battery remaining useful life estimation with an iterative updated RVM fused with the KF algorithm
- (2018) Yuchen SONG et al. Chinese Journal of Aeronautics
- Incremental capacity analysis and differential voltage analysis based state of charge and capacity estimation for lithium-ion batteries
- (2018) Linfeng Zheng et al. ENERGY
- A quick on-line state of health estimation method for Li-ion battery with incremental capacity curves processed by Gaussian filter
- (2018) Yi Li et al. JOURNAL OF POWER SOURCES
- Investigating the error sources of the online state of charge estimation methods for lithium-ion batteries in electric vehicles
- (2018) Yuejiu Zheng et al. JOURNAL OF POWER SOURCES
- Progress in solid electrolytes toward realizing solid-state lithium batteries
- (2018) Kazunori Takada JOURNAL OF POWER SOURCES
- Economic implications of lithium ion battery degradation for Vehicle-to-Grid (V2X) services
- (2018) Andrew W. Thompson JOURNAL OF POWER SOURCES
- Metal organic framework laden poly(ethylene oxide) based composite electrolytes for all-solid-state Li-S and Li-metal polymer batteries
- (2018) Shruti Suriyakumar et al. ELECTROCHIMICA ACTA
- A critical review on self-adaptive Li-ion battery ageing models
- (2018) M. Lucu et al. JOURNAL OF POWER SOURCES
- Health conscious fast charging of Li-ion batteries via a single particle model with aging mechanisms
- (2018) Xianke Lin et al. JOURNAL OF POWER SOURCES
- Lithium-ion battery state of health estimation with short-term current pulse test and support vector machine
- (2018) Jinhao Meng et al. MICROELECTRONICS RELIABILITY
- Random forest regression for online capacity estimation of lithium-ion batteries
- (2018) Yi Li et al. APPLIED ENERGY
- Poly(ethylene oxide) reinforced Li6PS5Cl composite solid electrolyte for all-solid-state lithium battery: Enhanced electrochemical performance, mechanical property and interfacial stability
- (2018) Jun Zhang et al. JOURNAL OF POWER SOURCES
- A data-driven remaining capacity estimation approach for lithium-ion batteries based on charging health feature extraction
- (2018) Peiyao Guo et al. JOURNAL OF POWER SOURCES
- Battery degradation and behaviour for electric vehicles: Review and numerical analyses of several models
- (2017) Samuel Pelletier et al. TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
- State-of-health estimation of lithium-ion battery packs in electric vehicles based on genetic resampling particle filter
- (2016) Jun Bi et al. APPLIED ENERGY
- On-board state of health estimation of LiFePO4 battery pack through differential voltage analysis
- (2016) Limei Wang et al. APPLIED ENERGY
- Development of an empirical aging model for Li-ion batteries and application to assess the impact of Vehicle-to-Grid strategies on battery lifetime
- (2016) Martin Petit et al. APPLIED ENERGY
- Calendar Aging of NCA Lithium-Ion Batteries Investigated by Differential Voltage Analysis and Coulomb Tracking
- (2016) Peter Keil et al. JOURNAL OF THE ELECTROCHEMICAL SOCIETY
- Critical review of state of health estimation methods of Li-ion batteries for real applications
- (2016) M. Berecibar et al. RENEWABLE & SUSTAINABLE ENERGY REVIEWS
- Performance comparison of four lithium–ion battery technologies under calendar aging
- (2015) Akram Eddahech et al. ENERGY
- Determination of lithium-ion battery state-of-health based on constant-voltage charge phase
- (2014) Akram Eddahech et al. JOURNAL OF POWER SOURCES
- Experimental investigation of the lithium-ion battery impedance characteristic at various conditions and aging states and its influence on the application
- (2012) Wladislaw Waag et al. APPLIED ENERGY
- Advanced mathematical methods of SOC and SOH estimation for lithium-ion batteries
- (2012) Dave Andre et al. JOURNAL OF POWER SOURCES
- Ageing monitoring of lithium-ion cell during power cycling tests
- (2011) A. Eddahech et al. MICROELECTRONICS RELIABILITY
- Conditional Variable Importance for Random Forests
- (2008) Carolin Strobl et al. BMC BIOINFORMATICS
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started