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Lithium‐ion battery SOC / SOH adaptive estimation via simplified single particle model

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

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Analysis of Lithium‐Ion Battery Models Based on Electrochemical Impedance Spectroscopy
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Thermal analysis of high-power lithium-ion battery packs using flow network approach
inferredcites →https://doi.org/10.1002/er.3598openalex-snapshot
Battery state of health estimation: a structured review of models, methods and commercial devices
inferredcites →https://doi.org/10.1002/er.3617openalex-snapshot
A hybrid lithium-ion battery model for system-level analyses
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Parameter estimation of an electrochemistry-based lithium-ion battery model using a two-step procedure and a parameter sensitivity analysis
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Reduced‐order modeling of lead‐acid battery using cluster analysis and orthogonal cluster analysis method
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Mathematical Modeling of Lithium Batteries
inferredcites →https://doi.org/10.1016/j.apenergy.2013.07.008openalex-snapshot
State of charge estimation of lithium-ion batteries using the open-circuit voltage at various ambient temperatures
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.2015.10.025openalex-snapshot
State-space model with non-integer order derivatives for lithium-ion battery
inferredcites →https://doi.org/10.1016/j.apenergy.2016.01.125openalex-snapshot
On-board state of health estimation of LiFePO4 battery pack through differential voltage analysis
inferredcites →https://doi.org/10.1016/j.energy.2016.02.163openalex-snapshot
State of health estimation algorithm of LiFePO4 battery packs based on differential voltage curves for battery management system application
inferredcites →https://doi.org/10.1016/j.jpowsour.2004.02.032openalex-snapshot
Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs
inferredcites →https://doi.org/10.1016/j.jpowsour.2006.04.146openalex-snapshot
Online estimation of the state of charge of a lithium ion cell
inferredcites →https://doi.org/10.1016/j.jpowsour.2007.06.185openalex-snapshot
Capacity loss in rechargeable lithium cells during cycle life testing: The importance of determining state-of-charge
inferredcites →https://doi.org/10.1016/j.jpowsour.2011.09.034openalex-snapshot
Simplification and order reduction of lithium-ion battery model based on porous-electrode theory
inferredcites →https://doi.org/10.1016/j.jpowsour.2011.09.058openalex-snapshot
Battery cell state-of-charge estimation using linear parameter varying system techniques
inferredcites →https://doi.org/10.1016/j.jpowsour.2011.10.013openalex-snapshot
A comparative study of equivalent circuit models for Li-ion batteries
inferredcites →https://doi.org/10.1016/j.jpowsour.2012.07.016openalex-snapshot
Synthesize battery degradation modes via a diagnostic and prognostic model
inferredcites →https://doi.org/10.1016/j.jpowsour.2013.04.129openalex-snapshot
A new extension of physics-based single particle model for higher charge–discharge rates
inferredcites →https://doi.org/10.1016/j.jpowsour.2014.08.089openalex-snapshot
Simplification of physics-based electrochemical model for lithium ion battery on electric vehicle. Part II: Pseudo-two-dimensional model simplification and state of charge estimation
inferredcites →https://doi.org/10.1016/j.jpowsour.2014.12.101openalex-snapshot
Simplification of physics-based electrochemical model for lithium ion battery on electric vehicle. Part I: Diffusion simplification and single particle model
inferredcites →https://doi.org/10.1016/j.jpowsour.2016.10.040openalex-snapshot
Multi-time-scale observer design for state-of-charge and state-of-health of a lithium-ion battery
inferredcites →https://doi.org/10.1016/j.jpowsour.2017.10.063openalex-snapshot
Calendar aging of a 250 kW/500 kWh Li-ion battery deployed for the grid storage application
inferredcites →https://doi.org/10.1016/j.solmat.2017.06.053openalex-snapshot
Demonstration study of hybrid solar power generation/storage micro-grid system under Qatar climate conditions
inferredcites →https://doi.org/10.1016/s0378-7753(02)00193-3openalex-snapshot
Electrochemical modeling of lithium polymer batteries
inferredcites →https://doi.org/10.1109/acc.2012.6315019openalex-snapshot
PDE estimation techniques for advanced battery management systems — Part I: SOC estimation
inferredcites →https://doi.org/10.1109/mcs.2010.936293openalex-snapshot
Algorithms for Advanced Battery-Management Systems
inferredcites →https://doi.org/10.1109/mie.2013.2250351openalex-snapshot
Battery Management System: An Overview of Its Application in the Smart Grid and Electric Vehicles
inferredcites →https://doi.org/10.1109/spec.2016.7846195openalex-snapshot
Matlab simulation of lithium ion cell using electrochemical single particle model
inferredcites →https://doi.org/10.1109/tcst.2016.2571663openalex-snapshot
Battery State Estimation for a Single Particle Model With Electrolyte Dynamics
inferredcites →https://doi.org/10.1109/tie.2015.2449776openalex-snapshot
Butler–Volmer-Equation-Based Electrical Model for High-Power Lithium Titanate Batteries Used in Electric Vehicles
inferredcites →https://doi.org/10.1109/tsg.2018.2867017openalex-snapshot
Estimation of Cell SOC Evolution and System Performance in Module-Based Battery Charge Equalization Systems
inferredcites →https://doi.org/10.1109/tvt.2004.842461openalex-snapshot
Nonlinear Observers for Predicting State-of-Charge and State-of-Health of Lead-Acid Batteries for Hybrid-Electric Vehicles
inferredcites →https://doi.org/10.1109/tvt.2009.2028348openalex-snapshot
New Battery Model and State-of-Health Determination Through Subspace Parameter Estimation and State-Observer Techniques
inferredcites →https://doi.org/10.1115/1.4024801openalex-snapshot
Adaptive Partial Differential Equation Observer for Battery State-of-Charge/State-of-Health Estimation Via an Electrochemical Model
inferredcites →https://doi.org/10.1115/1.4028154openalex-snapshot
A Temperature Dependent, Single Particle, Lithium Ion Cell Model Including Electrolyte Diffusion
inferredcites →https://doi.org/10.1149/1.3521314openalex-snapshot
Single-Particle Model for a Lithium-Ion Cell: Thermal Behavior
inferredcites →https://doi.org/10.1149/2.0201506jesopenalex-snapshot
State-of-Charge Determination in Lithium-Ion Battery Packs Based on Two-Point Measurements in Life
inferredcites →https://doi.org/10.1149/2.053304jesopenalex-snapshot
A Simplified Electrochemical and Thermal Aging Model of LiFePO4-Graphite Li-ion Batteries: Power and Capacity Fade Simulations
inferredcites →https://doi.org/10.1149/2.0761605jesopenalex-snapshot
Modeling of Li-Ion Cells for Fast Simulation of High C-Rate and Low Temperature Operations
inferredcites →https://doi.org/10.1149/2.100206jesopenalex-snapshot
Insights into the Role of Interphasial Morphology on the Electrochemical Performance of Lithium Electrodes
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/10.3390/en7085065openalex-snapshot
Evaluation of Model Based State of Charge Estimation Methods for Lithium-Ion Batteries

What points at this work

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

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The optimization of state of charge and state of health estimation for lithium‐ions battery using combined deep learning and Kalman filter methods
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Novel co‐estimation strategy based on forgetting factor dual particle filter algorithm for the state of charge and state of health of the lithium‐ion battery
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State‐of‐health estimation for the lithium‐ion battery based on gradient boosting decision tree with autonomous selection of excellent features
inferred← citeshttps://doi.org/10.1002/er.7949openalex-snapshot
Low‐complexity state of charge and anode potential prediction for lithium‐ion batteries using a simplified electrochemical model‐based observer under variable load condition
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A novel reed‐leaves like aluminum‐doped manganese oxide presetting sodium‐ion constructed by coprecipitation method for high electrochemical performance sodium‐ion battery
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A Digital Twin Model for Battery Management Systems: Concepts, Algorithms, and Platforms
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A Review on Electric Vehicle Battery Fault Diagnosis Methodologies
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State of Energy Prediction of Lithium-ion Battery Using Sparrow Search Optimization-Random Forest and State-of-the-Art Artificial Intelligence Methods
inferred← citeshttps://doi.org/10.1016/b978-0-443-16160-5.00017-2openalex-snapshot
Aging characteristics of lithium-ion batteries
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Rapid and flexible battery capacity estimation using random short-time charging segments based on residual convolutional networks
inferred← citeshttps://doi.org/10.1016/j.apenergy.2024.124624openalex-snapshot
A framework for joint SOC and SOH estimation of lithium-ion battery: Eliminating the dependency on initial states
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Research on life cycle SOC estimation method of lithium-ion battery oriented to decoupling temperature
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An improved thermal single particle model and parameter estimation for high-capacity battery cell
inferred← citeshttps://doi.org/10.1016/j.enconman.2022.115490openalex-snapshot
Multi-scale thermal modeling, experimental validation, and thermal characterization of a high-power lithium-ion cell for automobile application
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Scalable physics-informed joint state-of-charge and state-of-health estimation framework toward real-time operation of multi-cell lithium-ion energy storage systems
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State of charge estimation method by using a simplified electrochemical model in deep learning framework for lithium-ion batteries
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A vehicle-cloud collaborative framework for state of health estimation of lithium-ion batteries via multi-feature fusion and hybrid data-driven–empirical modeling
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State-of-health estimation of lithium-ion batteries for electrified vehicles using a reduced-order electrochemical model
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Ultrasonic guided wave measurement and modeling analysis of the state of charge for lithium-ion battery
inferred← citeshttps://doi.org/10.1016/j.est.2023.108826openalex-snapshot
Research on variable time-scale SOC and SOH asynchronous collaborative estimation strategy for electric vehicle power lithium iron phosphate batteries
inferred← citeshttps://doi.org/10.1016/j.est.2023.109185openalex-snapshot
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Multiscale-multidomain model order reduction of Lithium-ion batteries for automobile application: A review
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Lithium battery state of charge estimation based on improved variable forgetting factor recursive least squares method and adaptive Kalman filter joint algorithm
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A systematic review of electrochemical model-based lithium-ion battery state estimation in battery management systems
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