Heuristic Kalman optimized particle filter for remaining useful life prediction of lithium-ion battery
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[1] Jie Liu,et al. A regularized auxiliary particle filtering approach for system state estimation and battery life prediction , 2011 .
[2] Thomas B. Schön,et al. System identification of nonlinear state-space models , 2011, Autom..
[3] Chenbin Zhang,et al. A novel active equalization method for lithium-ion batteries in electric vehicles , 2015 .
[4] Patrick Lyonnet,et al. A new heuristic approach for non-convex optimization problems , 2010, Inf. Sci..
[5] N. Gordon,et al. Novel approach to nonlinear/non-Gaussian Bayesian state estimation , 1993 .
[6] J. Junkins,et al. Optimal Estimation of Dynamic Systems , 2004 .
[7] Juan M. Corchado,et al. Fight sample degeneracy and impoverishment in particle filters: A review of intelligent approaches , 2013, Expert Syst. Appl..
[8] K. Goebel,et al. Prognostics in Battery Health Management , 2008, IEEE Instrumentation & Measurement Magazine.
[9] Patrick Lyonnet,et al. Robust PID controller tuning based on the heuristic Kalman algorithm , 2009, Autom..
[10] Bidyut Baran Chaudhuri,et al. A Kalman filtering induced heuristic optimization based partitional data clustering , 2016, Inf. Sci..
[11] Dorin Comaniciu,et al. Kernel-Based Object Tracking , 2003, IEEE Trans. Pattern Anal. Mach. Intell..
[12] Patrick Lyonnet,et al. A Kalman Optimization Approach for Solving Some Industrial Electronics Problems , 2012, IEEE Transactions on Industrial Electronics.
[13] Bhaskar Saha,et al. Prognostics Methods for Battery Health Monitoring Using a Bayesian Framework , 2009, IEEE Transactions on Instrumentation and Measurement.
[14] Jing Zhao,et al. Particle filter based on Particle Swarm Optimization resampling for vision tracking , 2010, Expert Syst. Appl..
[15] Fredrik Gustafsson,et al. On Resampling Algorithms for Particle Filters , 2006, 2006 IEEE Nonlinear Statistical Signal Processing Workshop.
[16] Kai Goebel,et al. Modeling Li-ion Battery Capacity Depletion in a Particle Filtering Framework , 2009 .
[17] Wei Liang,et al. Remaining useful life prediction of lithium-ion battery with unscented particle filter technique , 2013, Microelectron. Reliab..
[18] Simo Srkk,et al. Bayesian Filtering and Smoothing , 2013 .
[19] Lehrstuhl für Elektrische,et al. Gaussian swarm: a novel particle swarm optimization algorithm , 2004, IEEE Conference on Cybernetics and Intelligent Systems, 2004..
[20] Kazufumi Ito,et al. Gaussian filters for nonlinear filtering problems , 2000, IEEE Trans. Autom. Control..
[21] Nagarajan Raghavan,et al. A metaheuristic approach to remaining useful life estimation of systems subject to multiple degradation mechanisms , 2017, 2017 IEEE International Conference on Prognostics and Health Management (ICPHM).
[22] Patrick Lyonnet,et al. Heuristic Kalman Algorithm for Solving Optimization Problems , 2009, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[23] Kai Goebel,et al. Comparison of prognostic algorithms for estimating remaining useful life of batteries , 2009 .
[24] Jun Bi,et al. State-of-health estimation of lithium-ion battery packs in electric vehicles based on genetic resampling particle filter , 2016 .
[25] David He,et al. Lithium-ion battery life prognostic health management system using particle filtering framework , 2011 .
[26] Michael Osterman,et al. Prognostics of lithium-ion batteries based on DempsterShafer theory and the Bayesian Monte Carlo me , 2011 .