Battery remaining useful life prediction at different discharge rates
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Dong Wang | Yang Zhao | Kwok-Leung Tsui | Fangfang Yang | K. Tsui | Yang Zhao | Fangfang Yang | Dong Wang | F. Yang
[1] Dong Wang,et al. An Intelligent Prognostic System for Gear Performance Degradation Assessment and Remaining Useful Life Estimation , 2015 .
[2] Bhaskar Saha,et al. Prognostics Methods for Battery Health Monitoring Using a Bayesian Framework , 2009, IEEE Transactions on Instrumentation and Measurement.
[3] M.G. Pecht,et al. Prognostics and health management of electronics , 2008, IEEE Transactions on Components and Packaging Technologies.
[4] Jorge F. Silva,et al. Particle-Filtering-Based Prognosis Framework for Energy Storage Devices With a Statistical Characterization of State-of-Health Regeneration Phenomena , 2013, IEEE Transactions on Instrumentation and Measurement.
[5] Kwok-Leung Tsui,et al. An ensemble model for predicting the remaining useful performance of lithium-ion batteries , 2013, Microelectron. Reliab..
[6] David He,et al. Lithium-ion battery life prognostic health management system using particle filtering framework , 2011 .
[7] Donghua Zhou,et al. Remaining useful life estimation - A review on the statistical data driven approaches , 2011, Eur. J. Oper. Res..
[8] Jay Lee,et al. Review and recent advances in battery health monitoring and prognostics technologies for electric vehicle (EV) safety and mobility , 2014 .
[9] Bin Zhang,et al. Machine Condition Prediction Based on Adaptive Neuro–Fuzzy and High-Order Particle Filtering , 2011, IEEE Transactions on Industrial Electronics.
[10] Dong Wang,et al. Prognostics of Li(NiMnCo)O2-based lithium-ion batteries using a novel battery degradation model , 2017, Microelectron. Reliab..
[11] K. Goebel,et al. Prognostics in Battery Health Management , 2008, IEEE Instrumentation & Measurement Magazine.
[12] Fei Feng,et al. A Combined State of Charge Estimation Method for Lithium-Ion Batteries Used in a Wide Ambient Temperature Range , 2014 .
[13] Dong Wang,et al. Remaining Useful Life Prediction of Lithium-Ion Batteries Based on Spherical Cubature Particle Filter , 2016, IEEE Transactions on Instrumentation and Measurement.
[14] M. Verbrugge,et al. Cycle-life model for graphite-LiFePO 4 cells , 2011 .
[15] Xiaoning Jin,et al. Lithium-ion battery state of health monitoring and remaining useful life prediction based on support vector regression-particle filter , 2014 .
[16] Michael Osterman,et al. Prognostics of lithium-ion batteries based on DempsterShafer theory and the Bayesian Monte Carlo me , 2011 .
[17] Bhaskar Saha,et al. Model Adaptation for Prognostics in a Particle Filtering Framework , 2011 .
[18] Enrico Zio,et al. Particle Filter-Based Prognostics for an Electrolytic Capacitor Working in Variable Operating Conditions , 2016, IEEE Transactions on Power Electronics.
[19] Tom Gorka,et al. Method for estimating capacity and predicting remaining useful life of lithium-ion battery , 2014, 2014 International Conference on Prognostics and Health Management.
[20] G. Kitagawa. Monte Carlo Filter and Smoother for Non-Gaussian Nonlinear State Space Models , 1996 .
[21] Noureddine Zerhouni,et al. Particle filter-based prognostics: Review, discussion and perspectives , 2016 .
[22] Wei Liang,et al. Remaining useful life prediction of lithium-ion battery with unscented particle filter technique , 2013, Microelectron. Reliab..
[23] Enrico Zio,et al. A particle filtering and kernel smoothing-based approach for new design component prognostics , 2015, Reliab. Eng. Syst. Saf..
[24] Kai Goebel,et al. Comparison of prognostic algorithms for estimating remaining useful life of batteries , 2009 .
[25] Jianbo Yu,et al. State-of-Health Monitoring and Prediction of Lithium-Ion Battery Using Probabilistic Indication and State-Space Model , 2015, IEEE Transactions on Instrumentation and Measurement.
[26] Ruqiang Yan,et al. Remaining Useful Life Prediction of Rolling Bearings Using an Enhanced Particle Filter , 2015, IEEE Transactions on Instrumentation and Measurement.
[27] Enrico Zio,et al. Monte Carlo-based filtering for fatigue crack growth estimation , 2009 .
[28] Michael Pecht,et al. Application of a state space modeling technique to system prognostics based on a health index for condition-based maintenance , 2012 .
[29] Enrico Zio,et al. Particle filtering prognostic estimation of the remaining useful life of nonlinear components , 2011, Reliab. Eng. Syst. Saf..
[30] Neil J. Gordon,et al. A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking , 2002, IEEE Trans. Signal Process..