Remaining useful life estimation of Lithium-ion battery based on interacting multiple model particle filter and support vector regression

A New Lithium-Ion Battery SOH Estimation Method Based on an Indirect Enhanced Health Indicator and Support Vector Regression in PHMs

(2020) Zhengyu Liu et al.   Energies

A comprehensive review of battery modeling and state estimation approaches for advanced battery management systems

(2020) Yujie Wang et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

A hybrid prognostic method for system degradation based on particle filter and relevance vector machine

(2019) Yang Chang et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Overview of model-based online state-of-charge estimation using Kalman filter family for lithium-ion batteries

(2019) Prashant Shrivastava et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review

(2019) Yi Li et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Remaining useful life prediction of lithium-ion batteries with adaptive unscented kalman filter and optimized support vector regression

(2019) Zhiwei Xue et al.   NEUROCOMPUTING

Parameter optimization of support vector regression based on sine cosine algorithm

(2018) Sai Li et al.   EXPERT SYSTEMS WITH APPLICATIONS

A Practical Lithium-Ion Battery Model for State of Energy and Voltage Responses Prediction Incorporating Temperature and Ageing Effects

(2018) Kaiyuan Li et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

State of health prediction of lithium-ion batteries: Multiscale logic regression and Gaussian process regression ensemble

(2018) Jianbo Yu   RELIABILITY ENGINEERING & SYSTEM SAFETY

An integrated imputation-prediction scheme for prognostics of battery data with missing observations

(2018) Roozbeh Razavi-Far et al.   EXPERT SYSTEMS WITH APPLICATIONS

Prognostics of Li(NiMnCo)O2-based lithium-ion batteries using a novel battery degradation model

(2017) Fangfang Yang et al.   MICROELECTRONICS RELIABILITY

Interacting multiple model particle filter for prognostics of lithium-ion batteries

(2017) Xiaohong Su et al.   MICROELECTRONICS RELIABILITY

Remaining Useful Life Prediction of Lithium-Ion Batteries Based on Spherical Cubature Particle Filter

(2016) Dong Wang et al.   IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

An integrated unscented kalman filter and relevance vector regression approach for lithium-ion battery remaining useful life and short-term capacity prediction

(2015) Xiujuan Zheng et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Review of Hybrid Prognostics Approaches for Remaining Useful Life Prediction of Engineered Systems, and an Application to Battery Life Prediction

(2014) Linxia Liao et al.   IEEE TRANSACTIONS ON RELIABILITY

Lithium-ion battery state of health monitoring and remaining useful life prediction based on support vector regression-particle filter

(2014) Hancheng Dong et al.   JOURNAL OF POWER SOURCES

Prognostics of Lithium-Ion Batteries Based on the Verhulst Model, Particle Swarm Optimization and Particle Filter

(2013) Weiming Xian et al.   IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

Improved adaptive state-of-charge estimation for batteries using a multi-model approach

(2013) Huazhen Fang et al.   JOURNAL OF POWER SOURCES

An ensemble model for predicting the remaining useful performance of lithium-ion batteries

(2013) Yinjiao Xing et al.   MICROELECTRONICS RELIABILITY

Prognostics for state of health estimation of lithium-ion batteries based on combination Gaussian process functional regression

(2013) Datong Liu et al.   MICROELECTRONICS RELIABILITY

Online State-of-Health Assessment for Battery Management Systems

(2011) M V Micea et al.   IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

Prognostics of lithium-ion batteries based on Dempster–Shafer theory and the Bayesian Monte Carlo method

(2011) Wei He et al.   JOURNAL OF POWER SOURCES

Remaining useful life estimation – A review on the statistical data driven approaches

(2010) Xiao-Sheng Si et al.   EUROPEAN JOURNAL OF OPERATIONAL RESEARCH