Related references
Note: Only part of the references are listed.On-line battery state-of-charge estimation based on an integrated estimator
Yujie Wang et al.
APPLIED ENERGY (2017)
A systematic state-of-charge estimation framework for multi-cell battery pack in electric vehicles using bias correction technique
Fengchun Sun et al.
APPLIED ENERGY (2016)
Open-Circuit Voltage-Based State of Charge Estimation of Lithium-ion Battery Using Dual Neural Network Fusion Battery Model
Xuanju Dang et al.
ELECTROCHIMICA ACTA (2016)
Comparisons of Modeling and State of Charge Estimation for Lithium-Ion Battery Based on Fractional Order and Integral Order Methods
Renxin Xiao et al.
ENERGIES (2016)
Critical review of state of health estimation methods of Li-ion batteries for real applications
M. Berecibar et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2016)
A novel multistage Support Vector Machine based approach for Li ion battery remaining useful life estimation
Meru A. Patil et al.
APPLIED ENERGY (2015)
A method for state of energy estimation of lithium-ion batteries based on neural network model
Guangzhong Dong et al.
ENERGY (2015)
ANFIS (adaptive neuro-fuzzy inference system) based online SOC (State of Charge) correction considering cell divergence for the EV (electric vehicle) traction batteries
Haifeng Dai et al.
ENERGY (2015)
Study on the correlation between state of charge and coulombic efficiency for commercial lithium ion batteries
Yuejiu Zheng et al.
JOURNAL OF POWER SOURCES (2015)
A novel dual-scale cell state-of-charge estimation approach for series-connected battery pack used in electric vehicles
Fengchun Sun et al.
JOURNAL OF POWER SOURCES (2015)
On-line optimization of battery open circuit voltage for improved state-of-charge and state-of-health estimation
Shijie Tong et al.
JOURNAL OF POWER SOURCES (2015)
Electric vehicle state of charge estimation: Nonlinear correlation and fuzzy support vector machine
Hanmin Sheng et al.
JOURNAL OF POWER SOURCES (2015)
Combined H∞ and passivity state estimation of memristive neural networks with random gain fluctuations
Rathinasamy Sakthivel et al.
NEUROCOMPUTING (2015)
A method for the estimation of the battery pack state of charge based on in-pack cells uniformity analysis
Liang Zhong et al.
APPLIED ENERGY (2014)
A new neural network model for the state-of-charge estimation in the battery degradation process
LiuWang Kang et al.
APPLIED ENERGY (2014)
A data-driven multi-scale extended Kalman filtering based parameter and state estimation approach of lithium-ion polymer battery in electric vehicles
Rui Xiong et al.
APPLIED ENERGY (2014)
State of charge estimation for Li-ion batteries using neural network modeling and unscented Kalman filter-based error cancellation
Wei He et al.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS (2014)
On-line equalization for lithium-ion battery packs based on charging cell voltages: Part 2. Fuzzy logic equalization
Yuejiu Zheng et al.
JOURNAL OF POWER SOURCES (2014)
Energy management of a power-split plug-in hybrid electric vehicle based on genetic algorithm and quadratic programming
Zheng Chen et al.
JOURNAL OF POWER SOURCES (2014)
State-of-charge estimation for battery management system using optimized support vector machine for regression
J. N. Hu et al.
JOURNAL OF POWER SOURCES (2014)
Battery Energy Storage System (BESS) and Battery Management System (BMS) for Grid-Scale Applications
Matthew T. Lawder et al.
PROCEEDINGS OF THE IEEE (2014)
A new model for State-of-Charge (SOC) estimation for high-power Li-ion batteries
Yao He et al.
APPLIED ENERGY (2013)
Battery Management System An Overview of Its Application in the Smart Grid and Electric Vehicles
Habiballah Rahimi-Eichi et al.
IEEE INDUSTRIAL ELECTRONICS MAGAZINE (2013)
Evaluation on State of Charge Estimation of Batteries With Adaptive Extended Kalman Filter by Experiment Approach
Rui Xiong et al.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2013)
State of Charge Estimation of Lithium-Ion Batteries in Electric Drive Vehicles Using Extended Kalman Filtering
Zheng Chen et al.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2013)
A review on the key issues for lithium-ion battery management in electric vehicles
Languang Lu et al.
JOURNAL OF POWER SOURCES (2013)
Online battery state of health estimation based on Genetic Algorithm for electric and hybrid vehicle applications
Zheng Chen et al.
JOURNAL OF POWER SOURCES (2013)
Advanced mathematical methods of SOC and SOH estimation for lithium-ion batteries
Dave Andre et al.
JOURNAL OF POWER SOURCES (2013)
State of charge estimation for electric vehicle batteries using unscented kalman filtering
Wei He et al.
MICROELECTRONICS RELIABILITY (2013)
Kalman filtering state of charge estimation for battery management system based on a stochastic fuzzy neural network battery model
Xu Long et al.
ENERGY CONVERSION AND MANAGEMENT (2012)
State-of-charge prediction of batteries and battery-supercapacitor hybrids using artificial neural networks
T. Weigert et al.
JOURNAL OF POWER SOURCES (2011)
Adaptive online state-of-charge determination based on neuro-controller and neural network
Shen Yanqing
ENERGY CONVERSION AND MANAGEMENT (2010)
State-of-charge estimation of lead-acid batteries using an adaptive extended Kalman filter
Jaehyun Han et al.
JOURNAL OF POWER SOURCES (2009)
State-of-charge and capacity estimation of lithium-ion battery using a new open-circuit voltage versus state-of-charge
Seongjun Lee et al.
JOURNAL OF POWER SOURCES (2008)
Sigma-point Kalman filtering for battery management systems of LiPB-based HEV battery packs - Part 1: Introduction and state estimation
Gregory L. Plett
JOURNAL OF POWER SOURCES (2006)
Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs - Part 3. State and parameter estimation
GL Plett
JOURNAL OF POWER SOURCES (2004)