Review of the Remaining Useful Life Prognostics of Vehicle Lithium-Ion Batteries Using Data-Driven Methodologies
Abstract
:1. Introduction
2. Remaining Useful Life (RUL) Prognostics Methodologies
2.1. RUL Prognostics Methodologies Based on Artificial Intelligence
2.2. RUL Prognostics Methodologies Based on Filtering Techniques
2.3. RUL Prognostics Methodologies Based on the Stochastic Degradation Process
3. Problem Analysis
- (1)
- Degradation modeling and RUL prediction methods for vehicle lithium-ion batteries with time-varying ambient temperature
- (2)
- Degradation modeling and RUL prediction methods for vehicle lithium-ion batteries with a random variable current
- (3)
- Degradation modeling and RUL prediction methods for vehicle lithium-ion batteries considering self-recharge characteristics
- (4)
- Denoising of random signals for vehicle lithium-ion batteries considering the system configuration of the cars
4. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Methodology | Advantages | Disadvantages | Main Relevant References |
---|---|---|---|
Artificial intelligence | (a) Does not need a data model (b) The algorithms are simple and feasible (c) The algorithms are the best solution for non-linear systems | (a) The point estimated value of RUL (b) Does not describe the uncertainty of measurement results | [12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33] |
Filtering techniques | (a) Can be used in any form of state-space model (b) best solution for non-linear, Gaussian, and non-Gaussian systems | (a) Needs data mode (state-space model) (b) The point estimated value of RUL | [34,35,36,37,38,39,40,41,42,43,44,45] |
Stochastic process | (a) Considers the time-dependence of the degradation process (b) Describes the uncertainty of predictable results | (a) Higher calculation complexity (b) Considers uncertain factors | [46,47,48,49] |
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Wu, L.; Fu, X.; Guan, Y. Review of the Remaining Useful Life Prognostics of Vehicle Lithium-Ion Batteries Using Data-Driven Methodologies. Appl. Sci. 2016, 6, 166. https://doi.org/10.3390/app6060166
Wu L, Fu X, Guan Y. Review of the Remaining Useful Life Prognostics of Vehicle Lithium-Ion Batteries Using Data-Driven Methodologies. Applied Sciences. 2016; 6(6):166. https://doi.org/10.3390/app6060166
Chicago/Turabian StyleWu, Lifeng, Xiaohui Fu, and Yong Guan. 2016. "Review of the Remaining Useful Life Prognostics of Vehicle Lithium-Ion Batteries Using Data-Driven Methodologies" Applied Sciences 6, no. 6: 166. https://doi.org/10.3390/app6060166