On the public citation graph

A Review on Different State of Battery Charge Estimation Techniques and Management Systems for EV Applications

https://doi.org/10.3390/electronics11111795

0 signed · 206 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.

Claim with ORCID

Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.

See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/9781119710905.ch6openalex-snapshot

Reconfigurable Battery Management System for Microgrid Application

inferredcites →https://doi.org/10.1002/ente.202000984openalex-snapshot

Recent Advancements in Battery Management System for Li‐Ion Batteries of Electric Vehicles: Future Role of Digital Twin, Cyber‐Physical Systems, Battery Swapping Technology, and Nondestructive Testing

inferredcites →https://doi.org/10.1007/s11465-018-0516-8openalex-snapshot

A brief review on key technologies in the battery management system of electric vehicles

inferredcites →https://doi.org/10.1016/b978-1-78242-377-5.00014-5openalex-snapshot

Aging of lithium-ion batteries for electric vehicles

inferredcites →https://doi.org/10.1016/j.apenergy.2012.08.031openalex-snapshot

A new model for State-of-Charge (SOC) estimation for high-power Li-ion batteries

inferredcites →https://doi.org/10.1016/j.apenergy.2013.12.046openalex-snapshot

State-of-charge estimation and uncertainty for lithium-ion battery strings

inferredcites →https://doi.org/10.1016/j.apenergy.2015.05.103openalex-snapshot

A novel modeling methodology of open circuit voltage hysteresis for LiFePO4 batteries based on an adaptive discrete Preisach model

inferredcites →https://doi.org/10.1016/j.apenergy.2015.10.092openalex-snapshot

Online state of charge estimation and open circuit voltage hysteresis modeling of LiFePO4 battery using invariant imbedding method

inferredcites →https://doi.org/10.1016/j.apenergy.2016.02.086openalex-snapshot

Comprehensive study of the influence of aging on the hysteresis behavior of a lithium iron phosphate cathode-based lithium ion battery – An experimental investigation of the hysteresis

inferredcites →https://doi.org/10.1016/j.apenergy.2016.06.042openalex-snapshot

Assessment of electrical vehicles as a successful driver for reducing CO2 emissions in China

inferredcites →https://doi.org/10.1016/j.apenergy.2016.07.003openalex-snapshot

A review of wireless power transfer for electric vehicles: Prospects to enhance sustainable mobility

inferredcites →https://doi.org/10.1016/j.apenergy.2017.05.183openalex-snapshot

A novel method on estimating the degradation and state of charge of lithium-ion batteries used for electrical vehicles

inferredcites →https://doi.org/10.1016/j.apm.2013.01.024openalex-snapshot

Battery state-of-charge estimator using the SVM technique

inferredcites →https://doi.org/10.1016/j.automatica.2010.06.004openalex-snapshot

An adaptive high-gain observer for nonlinear systems

inferredcites →https://doi.org/10.1016/j.compchemeng.2012.02.003openalex-snapshot

State-of-charge estimation for lithium-ion batteries under various operating conditions using an equivalent circuit model

inferredcites →https://doi.org/10.1016/j.egyr.2021.08.113openalex-snapshot

A review on online state of charge and state of health estimation for lithium-ion batteries in electric vehicles

inferredcites →https://doi.org/10.1016/j.electacta.2018.11.134openalex-snapshot

A comparative study of global optimization methods for parameter identification of different equivalent circuit models for Li-ion batteries

inferredcites →https://doi.org/10.1016/j.enconman.2011.06.003openalex-snapshot

Kalman filtering state of charge estimation for battery management system based on a stochastic fuzzy neural network battery model

inferredcites →https://doi.org/10.1016/j.enconman.2011.07.009openalex-snapshot

Simulation and experiment of thermal energy management with phase change material for ageing LiFePO4 power battery

inferredcites →https://doi.org/10.1016/j.enconman.2013.04.013openalex-snapshot

An improved control method of battery energy storage system for hourly dispatch of photovoltaic power sources

inferredcites →https://doi.org/10.1016/j.energy.2012.01.009openalex-snapshot

Online model-based estimation of state-of-charge and open-circuit voltage of lithium-ion batteries in electric vehicles

inferredcites →https://doi.org/10.1016/j.energy.2019.03.059openalex-snapshot

State-of-charge estimation of lithium-ion batteries based on gated recurrent neural network

inferredcites →https://doi.org/10.1016/j.engappai.2005.12.005openalex-snapshot

Fuzzy logic-based learning system and estimation of state-of-charge of lead-acid battery

inferredcites →https://doi.org/10.1016/j.enpol.2015.08.029openalex-snapshot

Uncertainty and differences in GHG emissions between electric and conventional gasoline vehicles with implications for transport policy making

inferredcites →https://doi.org/10.1016/j.est.2016.09.008openalex-snapshot

Online state of charge estimation for the aerial lithium-ion battery packs based on the improved extended Kalman filter method

inferredcites →https://doi.org/10.1016/j.est.2018.07.006openalex-snapshot

Revisiting the dual extended Kalman filter for battery state-of-charge and state-of-health estimation: A use-case life cycle analysis

inferredcites →https://doi.org/10.1016/j.est.2020.101458openalex-snapshot

Physics-based models in PV-battery hybrid power systems: Thermal management and degradation analysis

inferredcites →https://doi.org/10.1016/j.est.2020.101577openalex-snapshot

Coupled effects of charge–discharge cycles and rates on the mechanical behavior of electrodes in lithium–ion batteries

inferredcites →https://doi.org/10.1016/j.est.2020.101785openalex-snapshot

Effect of integrating the hysteresis component to the equivalent circuit model of Lithium-ion battery for dynamic and non-dynamic applications

inferredcites →https://doi.org/10.1016/j.est.2020.101978openalex-snapshot

State of charge estimation by multi-innovation unscented Kalman filter for vehicular applications

inferredcites →https://doi.org/10.1016/j.est.2020.102199openalex-snapshot

The self-discharging of supercapacitors interpreted in terms of a distribution of rate constants

inferredcites →https://doi.org/10.1016/j.est.2021.102521openalex-snapshot

Active cell voltage balancing of Electric vehicle batteries by using an optimized switched capacitor strategy

inferredcites →https://doi.org/10.1016/j.est.2021.102559openalex-snapshot

Co-estimation for capacity and state of charge for lithium-ion batteries using improved adaptive extended Kalman filter

inferredcites →https://doi.org/10.1016/j.est.2021.102572openalex-snapshot

Classification, summarization and perspectives on state-of-charge estimation of lithium-ion batteries used in electric vehicles: A critical comprehensive survey

inferredcites →https://doi.org/10.1016/j.est.2021.102655openalex-snapshot

An extended Kalman filter based data-driven method for state of charge estimation of Li-ion batteries

inferredcites →https://doi.org/10.1016/j.est.2021.102940openalex-snapshot

Review of electric vehicle energy storage and management system: Standards, issues, and challenges

inferredcites →https://doi.org/10.1016/j.est.2021.103023openalex-snapshot

Battery energy-storage system: A review of technologies, optimization objectives, constraints, approaches, and outstanding issues

inferredcites →https://doi.org/10.1016/j.est.2021.103099openalex-snapshot

A comprehensive review on system architecture and international standards for electric vehicle charging stations

inferredcites →https://doi.org/10.1016/j.est.2021.103225openalex-snapshot

A technological overview & design considerations for developing electric vehicle charging stations

inferredcites →https://doi.org/10.1016/j.est.2021.103235openalex-snapshot

Adaptive estimation-based hierarchical model predictive control methodology for battery active equalization topologies: Part I–Balancing strategy

inferredcites →https://doi.org/10.1016/j.est.2021.103292openalex-snapshot

A data-driven accurate battery model to use in probabilistic analyses of power systems

inferredcites →https://doi.org/10.1016/j.est.2021.103314openalex-snapshot

Optimization of an air-based thermal management system for lithium-ion battery packs

inferredcites →https://doi.org/10.1016/j.ijepes.2014.04.059openalex-snapshot

State of charge estimation for Li-ion batteries using neural network modeling and unscented Kalman filter-based error cancellation

inferredcites →https://doi.org/10.1016/j.ijepes.2014.06.017openalex-snapshot

An online state of charge estimation method with reduced prior battery testing information

inferredcites →https://doi.org/10.1016/j.jclepro.2016.03.120openalex-snapshot

Sustainability analysis of the electric vehicle use in Europe for CO2 emissions reduction

inferredcites →https://doi.org/10.1016/j.jpowsour.2004.02.033openalex-snapshot

Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs

inferredcites →https://doi.org/10.1016/j.jpowsour.2004.05.064openalex-snapshot

Thermal analysis of lithium-ion batteries

inferredcites →https://doi.org/10.1016/j.jpowsour.2005.04.039openalex-snapshot

Design and implementation of a fuzzy logic-based state-of-charge meter for Li-ion batteries used in portable defibrillators

inferredcites →https://doi.org/10.1016/j.jpowsour.2006.06.003openalex-snapshot

Sigma-point Kalman filtering for battery management systems of LiPB-based HEV battery packs

inferredcites →https://doi.org/10.1016/j.jpowsour.2006.06.004openalex-snapshot

Sigma-point Kalman filtering for battery management systems of LiPB-based HEV battery packs

inferredcites →https://doi.org/10.1016/j.jpowsour.2006.09.006openalex-snapshot

The novel state of charge estimation method for lithium battery using sliding mode observer

inferredcites →https://doi.org/10.1016/j.jpowsour.2009.11.048openalex-snapshot

Lithium batteries: Status, prospects and future

inferredcites →https://doi.org/10.1016/j.jpowsour.2010.06.098openalex-snapshot

Dynamic electric behavior and open-circuit-voltage modeling of LiFePO4-based lithium ion secondary batteries

inferredcites →https://doi.org/10.1016/j.jpowsour.2011.03.101openalex-snapshot

A review on prognostics and health monitoring of Li-ion battery

inferredcites →https://doi.org/10.1016/j.jpowsour.2012.10.057openalex-snapshot

LiFePO4 battery pack capacity estimation for electric vehicles based on charging cell voltage curve transformation

inferredcites →https://doi.org/10.1016/j.jpowsour.2012.10.058openalex-snapshot

Particle filter for state of charge and state of health estimation for lithium–iron phosphate batteries

inferredcites →https://doi.org/10.1016/j.jpowsour.2012.10.060openalex-snapshot

A review on the key issues for lithium-ion battery management in electric vehicles

inferredcites →https://doi.org/10.1016/j.jpowsour.2013.08.026openalex-snapshot

Battery equalization active methods

inferredcites →https://doi.org/10.1016/j.jpowsour.2013.09.135openalex-snapshot

A novel model of the initial state of charge estimation for LiFePO4 batteries

inferredcites →https://doi.org/10.1016/j.jpowsour.2014.01.020openalex-snapshot

A practical framework of electrical based online state-of-charge estimation of lithium ion batteries

inferredcites →https://doi.org/10.1016/j.jpowsour.2014.07.103openalex-snapshot

A novel method for state of charge estimation of lithium-ion batteries using a nonlinear observer

inferredcites →https://doi.org/10.1016/j.jpowsour.2014.11.135openalex-snapshot

Electrochemical state and internal variables estimation using a reduced-order physics-based model of a lithium-ion cell and an extended Kalman filter

inferredcites →https://doi.org/10.1016/j.jpowsour.2015.01.038openalex-snapshot

From a novel classification of the battery state of charge estimators toward a conception of an ideal one

inferredcites →https://doi.org/10.1016/j.jpowsour.2015.06.140openalex-snapshot

A study of the open circuit voltage characterization technique and hysteresis assessment of lithium-ion cells

inferredcites →https://doi.org/10.1016/j.jpowsour.2015.12.079openalex-snapshot

Unbalanced discharging and aging due to temperature differences among the cells in a lithium-ion battery pack with parallel combination

inferredcites →https://doi.org/10.1016/j.jpowsour.2015.12.083openalex-snapshot

Electrochemical model parameter identification of a lithium-ion battery using particle swarm optimization method

inferredcites →https://doi.org/10.1016/j.jpowsour.2016.01.001openalex-snapshot

Modelling and experimental evaluation of parallel connected lithium ion cells for an electric vehicle battery system

inferredcites →https://doi.org/10.1016/j.jpowsour.2016.02.087openalex-snapshot

Effects of imbalanced currents on large-format LiFePO 4 /graphite batteries systems connected in parallel

inferredcites →https://doi.org/10.1016/j.jpowsour.2016.05.121openalex-snapshot

Lithium-ion Open Circuit Voltage (OCV) curve modelling and its ageing adjustment

inferredcites →https://doi.org/10.1016/j.jpowsour.2016.07.090openalex-snapshot

Multi-temperature state-dependent equivalent circuit discharge model for lithium-sulfur batteries

inferredcites →https://doi.org/10.1016/j.jpowsour.2016.07.121openalex-snapshot

A Study of Cell-to-Cell Interactions and Degradation in Parallel Strings: Implications for the Battery Management System

inferredcites →https://doi.org/10.1016/j.jpowsour.2017.03.001openalex-snapshot

On state-of-charge determination for lithium-ion batteries

inferredcites →https://doi.org/10.1016/j.microrel.2012.11.010openalex-snapshot

State of charge estimation for electric vehicle batteries using unscented kalman filtering

inferredcites →https://doi.org/10.1016/j.proeng.2011.08.492openalex-snapshot

Measurement and analysis for lithium battery of high-rate discharge performance

inferredcites →https://doi.org/10.1016/j.renene.2016.06.009openalex-snapshot

Li-ion dynamics and state of charge estimation

inferredcites →https://doi.org/10.1016/j.rser.2014.04.018openalex-snapshot

The future of lithium availability for electric vehicle batteries

inferredcites →https://doi.org/10.1016/j.rser.2014.10.047openalex-snapshot

A comprehensive review on estimation strategies used in hybrid and battery electric vehicles

inferredcites →https://doi.org/10.1016/j.rser.2016.06.033openalex-snapshot

A review of the stage-of-the-art charging technologies, placement methodologies, and impacts of electric vehicles

inferredcites →https://doi.org/10.1016/j.rser.2016.11.126openalex-snapshot

Battery charge equalization controller in electric vehicle applications: A review

inferredcites →https://doi.org/10.1016/j.rser.2017.05.001openalex-snapshot

A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: Challenges and recommendations

inferredcites →https://doi.org/10.1016/s0378-7753(02)00200-8openalex-snapshot

Battery thermal models for hybrid vehicle simulations

inferredcites →https://doi.org/10.1016/s0378-7753(02)00713-9openalex-snapshot

Battery Monitoring and Electrical Energy Management

inferredcites →https://doi.org/10.1016/s0378-7753(99)00079-8openalex-snapshot

Determination of state-of-charge and state-of-health of batteries by fuzzy logic methodology

inferredcites →https://doi.org/10.1016/s0378-7753(99)00329-8openalex-snapshot

Reliable battery operation — a challenge for the battery management system

inferredcites →https://doi.org/10.1016/s0378-7753(99)00527-3openalex-snapshot

Comparison between computer simulations and experimental data for high-rate discharges of plastic lithium-ion batteries

inferredcites →https://doi.org/10.1016/s1004-9541(13)60570-4openalex-snapshot

Soft Sensor for Inputs and Parameters Using Nonlinear Singular State Observer in Chemical Processes

inferredcites →https://doi.org/10.1049/iet-cta.2013.0082openalex-snapshot

State‐of‐charge estimation of the lithium‐ion battery system with time‐varying parameter for hybrid electric vehicles

inferredcites →https://doi.org/10.1049/iet-pel.2013.0746openalex-snapshot

Hybrid state of charge estimation for lithium‐ion batteries: design and implementation

inferredcites →https://doi.org/10.1049/iet-pel.2014.0523openalex-snapshot

Design of adaptive H ∞ filter for implementing on state‐of‐charge estimation based on battery state‐of‐charge‐varying modelling

inferredcites →https://doi.org/10.1049/joe.2018.9234openalex-snapshot

State‐of‐Charge estimation of Li‐ion battery at different temperatures using particle filter

inferredcites →https://doi.org/10.1049/pel2.12129openalex-snapshot

State‐of‐charge estimation technique for lithium‐ion batteries by means of second‐order extended Kalman filter and equivalent circuit model: Great temperature robustness state‐of‐charge estimation

inferredcites →https://doi.org/10.1063/1.4798430openalex-snapshot

A critical review on state of charge of batteries

inferredcites →https://doi.org/10.1063/1.4944961openalex-snapshot

Voltage equalization control algorithm for monitoring and balancing of series connected lithium-ion battery

inferredcites →https://doi.org/10.1088/1757-899x/937/1/012046openalex-snapshot

Battery modelling and state of charge estimation methods for Energy Management in Electric Vehicle-A review

inferredcites →https://doi.org/10.1093/ijlct/ctac002openalex-snapshot

Modeling carbon dioxide emission of countries in southeast of Asia by applying artificial neural network

inferredcites →https://doi.org/10.1109/access.2017.2725301openalex-snapshot

State of Charge Estimation of Battery Energy Storage Systems Based on Adaptive Unscented Kalman Filter With a Noise Statistics Estimator

inferredcites →https://doi.org/10.1109/access.2017.2780258openalex-snapshot

Critical Review on the Battery State of Charge Estimation Methods for Electric Vehicles

inferredcites →https://doi.org/10.1109/access.2018.2817655openalex-snapshot

State-of-the-Art and Energy Management System of Lithium-Ion Batteries in Electric Vehicle Applications: Issues and Recommendations

inferredcites →https://doi.org/10.1109/access.2019.2926517openalex-snapshot

Combined CNN-LSTM Network for State-of-Charge Estimation of Lithium-Ion Batteries

inferredcites →https://doi.org/10.1109/access.2020.2967563openalex-snapshot

Comparative Study of the Influence of Open Circuit Voltage Tests on State of Charge Online Estimation for Lithium-Ion Batteries

inferredcites →https://doi.org/10.1109/access.2020.3047971openalex-snapshot

Noise Adaptive Moving Horizon Estimation for State-of-Charge Estimation of Li-Ion Battery

inferredcites →https://doi.org/10.1109/aici.2009.15openalex-snapshot

Battery Model Parameters Estimation with the Sigma Point Kalman Filter

inferredcites →https://doi.org/10.1109/aimsec.2011.6009928openalex-snapshot

Battery state-of-charge estimation based on sigma point Kalman filter

inferredcites →https://doi.org/10.1109/appeec.2011.5748714openalex-snapshot

Research on State of Charge Estimation of Batteries Used in Electric Vehicle

inferredcites →https://doi.org/10.1109/autest.2008.4662684openalex-snapshot

Automotive battery management systems

inferredcites →https://doi.org/10.1109/cca.2008.4629639openalex-snapshot

Lithium-ion battery state of charge estimation with a Kalman Filter based on a electrochemical model

inferredcites →https://doi.org/10.1109/cencon.2015.7409543openalex-snapshot

Sizing of a VRB battery based on max-min method of power dispatch in a wind-PV hybrid system

inferredcites →https://doi.org/10.1109/cisp.2009.5303451openalex-snapshot

State of Charge Estimation Online Based on EKF-Ah Method for Lithium-Ion Power Battery

inferredcites →https://doi.org/10.1109/cisp.2011.6100603openalex-snapshot

Battery state of charge online estimation based on particle filter

inferredcites →https://doi.org/10.1109/fuzz.2003.1206580openalex-snapshot

Battery state-of-charge (SOC) estimation using adaptive neuro-fuzzy inference system (ANFIS)

inferredcites →https://doi.org/10.1109/iccsn.2011.6013952openalex-snapshot

Battery state of charge estimation for electric vehicle based on neural network

inferredcites →https://doi.org/10.1109/iciea.2010.5516984openalex-snapshot

Prediction of state of charge of Lithium-ion rechargeable battery with electrochemical impedance spectroscopy theory

inferredcites →https://doi.org/10.1109/iciea.2012.6360994openalex-snapshot

RBF network-aided adaptive unscented kalman filter for lithium-ion battery SOC estimation in electric vehicles

inferredcites →https://doi.org/10.1109/iciea.2013.6566439openalex-snapshot

Adaptive gain sliding mode observer for state of charge estimation based on combined battery equivalent circuit model in electric vehicles

inferredcites →https://doi.org/10.1109/icosec49089.2020.9215263openalex-snapshot

SOC Estimation of battery in Hybrid Vehicle Using Adaptive Neuro-Fuzzy Technique

inferredcites →https://doi.org/10.1109/iemdc.2003.1210310openalex-snapshot

EV battery state of charge: neural network based estimation

inferredcites →https://doi.org/10.1109/ijcnn.2011.6033495openalex-snapshot

Battery state of charge estimation based on a combined model of Extended Kalman Filter and neural networks

inferredcites →https://doi.org/10.1109/indin.2017.8104844openalex-snapshot

SOC estimation for a lithium-ion battery by designing a nonlinear observer based on an equivalent circuit model

inferredcites →https://doi.org/10.1109/itec.2012.6243437openalex-snapshot

Review of adaptive systems for lithium batteries State-of-Charge and State-of-Health estimation

inferredcites →https://doi.org/10.1109/itec.2012.6243505openalex-snapshot

A joint model and SOC estimation method for lithium battery based on the sigma point KF

inferredcites →https://doi.org/10.1109/itec.2013.6573477openalex-snapshot

Extended Kalman Filter based battery state of charge(SOC) estimation for electric vehicles

inferredcites →https://doi.org/10.1109/itec48692.2020.9161523openalex-snapshot

Battery SoC Estimation from EIS using Neural Nets

inferredcites →https://doi.org/10.1109/jsyst.2021.3123436openalex-snapshot

Combined Approach for Power Loss Minimization in Distribution Networks in the Presence of Gridable Electric Vehicles and Dispersed Generation

inferredcites →https://doi.org/10.1109/mpe.2017.2708812openalex-snapshot

Technological Developments in Batteries: A Survey of Principal Roles, Types, and Management Needs

inferredcites →https://doi.org/10.1109/pesc.2007.4342462openalex-snapshot

The State and Parameter Estimation of an Li-Ion Battery Using a New OCV-SOC Concept

inferredcites →https://doi.org/10.1109/pesc.2007.4342463openalex-snapshot

State Estimation of a Lithium-Ion Battery Through Kalman Filter

inferredcites →https://doi.org/10.1109/spit.2018.8350462openalex-snapshot

State-of-charge estimation of lithium-ion batteries using extended Kalman filter and unscented Kalman filter

inferredcites →https://doi.org/10.1109/tase.2015.2434052openalex-snapshot

Performance Evaluation of Modularized Global Equalization System for Lithium-Ion Battery Packs

inferredcites →https://doi.org/10.1109/tcst.2018.2842038openalex-snapshot

State-of-Charge Estimation Using an EKF-Based Adaptive Observer

inferredcites →https://doi.org/10.1109/tec.2006.874229openalex-snapshot

Accurate electrical battery model capable of predicting runtime and I-V performance

inferredcites →https://doi.org/10.1109/tec.2007.895457openalex-snapshot

A Merged Fuzzy Neural Network and Its Applications in Battery State-of-Charge Estimation

inferredcites →https://doi.org/10.1109/tia.2020.3004294openalex-snapshot

State-of-Charge Estimation of Li-Ion Battery in Electric Vehicles: A Deep Neural Network Approach

inferredcites →https://doi.org/10.1109/tie.2002.1005395openalex-snapshot

Adaptive neuro-fuzzy modeling of battery residual capacity for electric vehicles

inferredcites →https://doi.org/10.1109/tie.2007.899926openalex-snapshot

State-of-Charge Determination From EMF Voltage Estimation: Using Impedance, Terminal Voltage, and Current for Lead-Acid and Lithium-Ion Batteries

inferredcites →https://doi.org/10.1109/tie.2013.2288195openalex-snapshot

A Chain Structure of Switched Capacitor for Improved Cell Balancing Speed of Lithium-Ion Batteries

inferredcites →https://doi.org/10.1109/tie.2015.2463770openalex-snapshot

Advanced Power-Source Integration in Hybrid Electric Vehicles: Multicriteria Optimization Approach

inferredcites →https://doi.org/10.1109/tie.2017.2787586openalex-snapshot

Long Short-Term Memory Networks for Accurate State-of-Charge Estimation of Li-ion Batteries

inferredcites →https://doi.org/10.1109/tie.2018.2880668openalex-snapshot

A Simplified Model-Based State-of-Charge Estimation Approach for Lithium-Ion Battery With Dynamic Linear Model

inferredcites →https://doi.org/10.1109/tii.2013.2284713openalex-snapshot

Model-Based Dynamic Power Assessment of Lithium-Ion Batteries Considering Different Operating Conditions

inferredcites →https://doi.org/10.1109/tpel.2008.924629openalex-snapshot

Nonlinear State of Charge Estimator for Hybrid Electric Vehicle Battery

inferredcites →https://doi.org/10.1109/tpel.2013.2243918openalex-snapshot

Support Vector Machines Used to Estimate the Battery State of Charge

inferredcites →https://doi.org/10.1109/tte.2016.2569069openalex-snapshot

Multi-timescale Parametric Electrical Battery Model for Use in Dynamic Electric Vehicle Simulations

inferredcites →https://doi.org/10.1109/tvt.2012.2222684openalex-snapshot

Evaluation on State of Charge Estimation of Batteries With Adaptive Extended Kalman Filter by Experiment Approach

inferredcites →https://doi.org/10.1109/tvt.2012.2235474openalex-snapshot

State of Charge Estimation of Lithium-Ion Batteries in Electric Drive Vehicles Using Extended Kalman Filtering

inferredcites →https://doi.org/10.1109/tvt.2013.2287375openalex-snapshot

The State of Charge Estimation of Lithium-Ion Batteries Based on a Proportional-Integral Observer

inferredcites →https://doi.org/10.1109/vppc.2011.6042988openalex-snapshot

Kalman filter based state-of-charge estimation for lithium-ion batteries in hybrid electric vehicles using pulse charging

inferredcites →https://doi.org/10.1109/vppc.2011.6043108openalex-snapshot

Comparison of passive cell balancing and active cell balancing for automotive batteries

inferredcites →https://doi.org/10.1109/vppc.2013.6671667openalex-snapshot

Battery State Estimation Using Mixed Kalman/Hinfinity, Adaptive Luenberger and Sliding Mode Observer

inferredcites →https://doi.org/10.1109/vppc.2013.6671711openalex-snapshot

State-of-Charge Estimation of Lithium-Ion Battery Using Multi-State Estimate Technic for Electric Vehicle Applications

inferredcites →https://doi.org/10.1155/2013/953792openalex-snapshot

The State of Charge Estimating Methods for Battery: A Review

inferredcites →https://doi.org/10.1155/2014/176052openalex-snapshot

Tuning of Kalman Filter Parameters via Genetic Algorithm for State-of-Charge Estimation in Battery Management System

inferredcites →https://doi.org/10.1155/2015/631263openalex-snapshot

A Review on Fault Mechanism and Diagnosis Approach for Li‐Ion Batteries

inferredcites →https://doi.org/10.1201/b11292openalex-snapshot

Lithium-Ion Batteries

inferredcites →https://doi.org/10.23919/acc50511.2021.9482734openalex-snapshot

Online State of Charge Estimation of Lithium-ion Battery Cells: A Multiple Model Adaptive Estimation Approach

inferredcites →https://doi.org/10.32920/ryerson.14652222.v1openalex-snapshot

Accuracy improvement of SOC estimation in lithium-ion batteries by ANFIS vs ANN modeling of nonlinear cell characteristics

inferredcites →https://doi.org/10.3390/en11071820openalex-snapshot

State of the Art of Lithium-Ion Battery SOC Estimation for Electrical Vehicles

inferredcites →https://doi.org/10.3390/en13236257openalex-snapshot

Hybrid Battery Thermal Management System in Electrical Vehicles: A Review

inferredcites →https://doi.org/10.3390/en14030758openalex-snapshot

Adaptive Online State of Charge Estimation of EVs Lithium-Ion Batteries with Deep Recurrent Neural Networks

inferredcites →https://doi.org/10.3390/en14113284openalex-snapshot

Current Trends for State-of-Charge (SoC) Estimation in Lithium-Ion Battery Electric Vehicles

inferredcites →https://doi.org/10.3390/en14154617openalex-snapshot

Comprehensive Review on Smart Techniques for Estimation of State of Health for Battery Management System Application

inferredcites →https://doi.org/10.3390/en4111840openalex-snapshot

Battery Management Systems in Electric and Hybrid Vehicles

inferredcites →https://doi.org/10.3390/su122410451openalex-snapshot

A Study on State of Charge and State of Health Estimation in Consideration of Lithium-Ion Battery Aging

inferredcites →https://doi.org/10.4028/www.scientific.net/amr.211-212.1204openalex-snapshot

State of Charge (SOC) Estimation of Ni-MH Battery Based on Least Square Support Vector Machines

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4753914openalex-extracted

Lithium Battery SOC Estimation Based on Improved Vffrls-Aekf

inferred← citeshttps://doi.org/10.1002/ente.202500360openalex-snapshot

An Improved Equivalent Circuit Model and a Variable Scale Unscented Kalman Filter for State‐of‐Charge Estimation of Lithium‐Ion Batteries at Variable Ambient Temperatures

inferred← citeshttps://doi.org/10.1007/978-3-031-89420-6_25openalex-snapshot

Machine Learning and Deep Learning-Based Comparison Methods for the Estimate of Mobile Device Charging Duration

inferred← citeshttps://doi.org/10.1007/s11581-026-07117-7openalex-snapshot

Machine learning based neural network framework for state of charge and state of power mapping estimation of lithium-ion cells for electric vehicles

inferred← citeshttps://doi.org/10.1007/s41939-025-01014-8openalex-snapshot

A novel optimized machine learning algorithm approach for solar-powered xEV charging stations

inferred← citeshttps://doi.org/10.1016/j.est.2023.108876openalex-snapshot

VLSI design and FPGA implementation of state-of-charge and state-of-health estimation for electric vehicle battery management systems

inferred← citeshttps://doi.org/10.1016/j.est.2024.111179openalex-snapshot

A review of battery energy storage systems and advanced battery management system for different applications: Challenges and recommendations

inferred← citeshttps://doi.org/10.1016/j.est.2024.113392openalex-snapshot

Lithium battery state of charge estimation based on improved variable forgetting factor recursive least squares method and adaptive Kalman filter joint algorithm

inferred← citeshttps://doi.org/10.1016/j.est.2025.116202openalex-snapshot

Improving electric vehicle state of charge estimation with wavelet transform-integrated 1D-CNN pooling layers

inferred← citeshttps://doi.org/10.1016/j.est.2025.118140openalex-snapshot

Optimized deep convolutional neural networks for SOC and SOH estimation in electric vehicles using orangutan algorithm

inferred← citeshttps://doi.org/10.1016/j.est.2026.121364openalex-snapshot

A comprehensive review of energy and battery management system integration: Architectures, approaches, and research directions

inferred← citeshttps://doi.org/10.1016/j.fub.2025.100087openalex-snapshot

Next-generation battery energy management systems in electric vehicles: An overview of artificial intelligence

inferred← citeshttps://doi.org/10.1016/j.inffus.2026.104642openalex-snapshot

Uncertainty management in data-driven state estimation: Taxonomy, methods, and battery applications

inferred← citeshttps://doi.org/10.1016/j.nxener.2025.100337openalex-snapshot

Analysis and advancements of the state of charge estimation methods in smart battery management system supported by lithium-ion battery operated electric vehicles

inferred← citeshttps://doi.org/10.1016/j.prime.2023.100362openalex-snapshot

An extended Kalman-Bucy filter for state of charge estimation of 2-RC network modelled Li-ion battery

inferred← citeshttps://doi.org/10.1016/j.psep.2024.09.105openalex-snapshot

Applications of artificial intelligence and cell balancing techniques for battery management system (BMS) in electric vehicles: A comprehensive review

inferred← citeshttps://doi.org/10.1016/j.rineng.2026.112115openalex-snapshot

A critical review of state of charge estimation and lifetime prediction models for batteries used in electric vehicles

inferred← citeshttps://doi.org/10.1093/ce/zkae084openalex-snapshot

Estimating state of charge of battery in renewable energy systems: a data-driven approach with artificial neural networks

inferred← citeshttps://doi.org/10.1109/access.2023.3250221openalex-snapshot

A Comprehensive Review on Electric Vehicle: Battery Management System, Charging Station, Traction Motors

inferred← citeshttps://doi.org/10.1109/access.2024.3490655openalex-snapshot

Digital Twin Model for Lithium-Ion Battery SOC Estimation in Battery Swapping Station

inferred← citeshttps://doi.org/10.1109/access.2025.3528314openalex-snapshot

Lithium Battery Life Prediction for Electric Vehicles Using Enhanced TCN and SVN Quantile Regression

inferred← citeshttps://doi.org/10.1109/cpere65146.2025.11240013openalex-snapshot

Design and Optimization of Extended-Range Electric Vehicles: A Simulation-Based Approach

inferred← citeshttps://doi.org/10.1109/iraset68627.2026.11538576openalex-snapshot

Battery Management Systems for Lithium-Ion Batteries in Electric Vehicles: Architectures, Modeling, and SOC Estimation Methods - A State of the Art

inferred← citeshttps://doi.org/10.1109/peeec63877.2024.00044openalex-snapshot

Optimization and Management Strategies of Electric Two Wheeled Vehicle Battery Exchange Network Based on Artificial Intelligence

inferred← citeshttps://doi.org/10.1149/1945-7111/ae6bf6openalex-snapshot

Sensor Driven Long Short-Term Memory Gate Recurrent Estimation with Deep Reinforcement Learning Based Charge Control for Battery Swapping Station Application

inferred← citeshttps://doi.org/10.1155/2023/3648488openalex-snapshot

A Comprehensive Review of Various Topologies and Control Techniques for DC-DC Converter-Based Lithium-Ion Battery Charge Equalization

inferred← citeshttps://doi.org/10.1155/ijae/7914048openalex-snapshot

Unresolved Challenges of Fuel Cell Propulsion Systems in Urban Air Mobility: An MBSE‐Based Systematic Literature Review

inferred← citeshttps://doi.org/10.11591/ijece.v14i3.pp2449-2456openalex-snapshot

Enhancing battery system identification: nonlinear autoregressive modeling for Li-ion batteries

inferred← citeshttps://doi.org/10.21203/rs.3.rs-4392938/v1openalex-snapshot

Season Aware Solar Photovoltaic-Based Efficient EV Charging System Using A Novel JFL-BiLSTM And RF-SHO

inferred← citeshttps://doi.org/10.23919/aeit63317.2024.10736742openalex-snapshot

On-Line State Estimation for Li-Ion Batteries in Traction Applications

inferred← citeshttps://doi.org/10.30521/jes.1339832openalex-snapshot

Online estimation of state-of-charge using auxiliary load

inferred← citeshttps://doi.org/10.3389/fbael.2026.1883201openalex-snapshot

AI/ML enabled smart battery management systems in electric vehicles

inferred← citeshttps://doi.org/10.3390/batteries11020058openalex-snapshot

Online Cell-by-Cell Calibration Method to Enhance the Kalman-Filter-Based State-of-Charge Estimation

inferred← citeshttps://doi.org/10.3390/batteries9100521openalex-snapshot

A Data-Driven Digital Twin of Electric Vehicle Li-Ion Battery State-of-Charge Estimation Enabled by Driving Behavior Application Programming Interfaces

inferred← citeshttps://doi.org/10.3390/engproc2024070053openalex-snapshot

The Temperature Effect on Electric Vehicle’s Lithium-Ion Battery Aging Using Machine Learning Algorithm

inferred← citeshttps://doi.org/10.3390/recycling7060081openalex-snapshot

The Application of Artificial Intelligence in the Effective Battery Life Cycle in the Closed Circular Economy Model—A Perspective

inferred← citeshttps://doi.org/10.3390/su151813376openalex-snapshot

A Review of Multilevel Inverter Topologies for Grid-Connected Sustainable Solar Photovoltaic Systems

inferred← citeshttps://doi.org/10.3390/su162210026openalex-snapshot

Systematic Review of Battery Life Cycle Management: A Framework for European Regulation Compliance

inferred← citeshttps://doi.org/10.3390/sym17030321openalex-snapshot

Advanced Algorithms in Battery Management Systems for Electric Vehicles: A Comprehensive Review

inferred← citeshttps://doi.org/10.3390/wevj15090381openalex-snapshot

A Review on State-of-Charge Estimation Methods, Energy Storage Technologies and State-of-the-Art Simulators: Recent Developments and Challenges

inferred← citeshttps://doi.org/10.3390/wevj17090452openalex-snapshot

A Hierarchical Multi-Timescale Method with Aging-Aware Capacity Correction for Low-Temperature State-of-Charge Estimation of Lithium-Ion Batteries

inferred← citeshttps://doi.org/10.36296/1819-8058.2025.3(82).8-18openalex-snapshot

ІМПУЛЬСНИЙ МЕТОД КОНТРОЛЮ ПОТОЧНОГО СТАНУ ЗАРЯДЖЕНОСТІ ЕЛЕКТРОХІМІЧНОГО НАКОПИЧУВАЧА ЕНЕРГІЇ

inferred← citeshttps://doi.org/10.37285/ajmt.6.2.9openalex-snapshot

State of Charge Estimation Methods for Electric Vehicles & Hybrid Electric Vehicles: Present Standing and Upcoming Outlook – A Review

Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.