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References from Lithium-ion battery data and where to find it. Local targets link to admitted publications; unresolved targets remain external evidence.
Bringing forward the development of battery cells for automotive applications: perspective of R&D activities in China, Japan, the EU and the USA
10.1016/j.jpowsour.2020.228073 · 2020 · External reference
Automotive Li-ion batteries: current status and future perspectives
10.1007/s41918-018-0022-z · 2019 · External reference
Free radicals: making a case for battery modeling
10.1149/2.f03204if · 2020 · External reference
Mass load prediction for lithium-ion battery electrode clean production: a machine learning approach
10.1016/j.jclepro.2020.125159 · 2021 · External reference
Feature analyses and modelling of lithium-ion batteries manufacturing based on random forest classification
2021 · External reference
Data-driven prediction of battery cycle life before capacity degradation
10.1038/s41560-019-0356-8 · 2019 · External reference
10.1016/j.egyai.2020.100006 · 2020 · Admitted local publication
FOBSS: monitoring data from a modular battery system
2019 · External reference
Randomized battery usage data set
2009 · External reference
Battery data set
2007 · External reference
Degradation of commercial lithium-ion cells as a function of chemistry and cycling conditions
10.1149/1945-7111/abae37 · 2020 · External reference
Accelerated cycle life testing and capacity degradation modeling of LiCoO2-graphite cells
10.1016/j.jpowsour.2019.226830 · 2019 · External reference
Cycle life testing and modeling of graphite/LiCoO2 cells under different state of charge ranges
10.1016/j.jpowsour.2016.07.057 · 2016 · External reference
A novel method for the modeling of the state of health of lithium-ion cells using machine learning for practical applications
10.1016/j.knosys.2021.106900 · 2021 · External reference
Calendar aging of lithium-ion batteries
10.1149/2.0411609jes · 2016 · External reference
Investigation of path-dependent degradation in lithium-ion batteries
10.1002/batt.202000160 · 2020 · External reference
Remaining useful life assessment of lithium-ion batteries in implantable medical devices
10.1016/j.jpowsour.2017.11.056 · 2018 · External reference
10.1016/j.egyai.2020.100016 · 2020 · Admitted local publication
Predicting the state of charge and health of batteries using data-driven machine learning
2020 · External reference
Perspective–combining physics and machine learning to predict battery lifetime
10.1149/1945-7111/abec55 · 2021 · External reference
Robust prognostics for state of health estimation of lithium-ion batteries based on an improved PSO–SVR model
10.1016/j.microrel.2015.06.133 · 2015 · External reference
Estimation of Li-ion battery state of health based on multilayer perceptron: as an EV application
10.1016/j.ifacol.2018.11.734 · 2018 · External reference
Gaussian process regression for forecasting battery state of health
10.1016/j.jpowsour.2017.05.004 · 2017 · External reference
Machine learning pipeline for battery state of health estimation
10.1038/s42256-021-00312-3 · 2021 · External reference
The state of charge estimating methods for battery: areview
2013 · External reference
State-of-charge estimation of Li-ion batteries using deep neural networks: a machine learning approach
10.1016/j.jpowsour.2018.06.104 · 2018 · External reference
State-of-health monitoring of lithium-ion batteries in electric vehicles by on-board internal resistance estimation
10.1016/j.jpowsour.2010.08.035 · 2011 · External reference
Data-driven Ohmic resistance estimation of battery packs for electric vehicles
10.3390/en12244772 · 2019 · External reference
Model migration neural network for predicting battery aging trajectories
10.1109/tte.2020.2979547 · 2020 · External reference
Modified Gaussian process regression models for cyclic capacity prediction of lithium-ion batteries
10.1109/tte.2019.2944802 · 2019 · External reference
Identifying degradation patterns of lithium ion batteries from impedance spectroscopy using machine learning
2020 · External reference
Elbows of internal resistance rise curves in Li-ion cells
10.3390/en14041206 · 2021 · External reference
Novel battery state-of-health online estimation method using multiple health indicators and an extreme learning machine
10.1016/j.energy.2018.06.220 · 2018 · External reference
Internal short circuit detection for lithium-ion battery pack with parallel-series hybrid connections
10.1016/j.jclepro.2020.120277 · 2020 · External reference
A fractional-order model-based battery external short circuit fault diagnosis approach for all-climate electric vehicles application
10.1016/j.jclepro.2018.03.259 · 2018 · External reference
A machine learning framework for early detection of lithium plating combining multiple physics-based electrochemical signatures
10.1016/j.xcrp.2021.100352 · 2021 · External reference
Expanding the lifetime of Li-ion batteries through optimization of charging profiles
10.1016/j.jclepro.2019.04.031 · 2019 · External reference
Charging pattern optimization for lithium-ion batteries with an electrothermal-aging model
10.1109/tii.2018.2866493 · 2018 · External reference
A compact resonant switched-capacitor heater for lithium-ion battery self-heating at low temperatures
10.1109/tpel.2019.2954703 · 2019 · External reference
Modelling and understanding battery materials with machine-learning-driven atomistic simulations
2020 · External reference
Improving optimal control of grid-connected lithium-ion batteries through more accurate battery and degradation modelling
10.1016/j.jpowsour.2018.01.004 · 2018 · External reference
Unresolved reference
2019 · External reference
Unlocking extra value from grid batteries using advanced models
10.1016/j.jpowsour.2020.229355 · 2021 · External reference
Probabilistic prediction of energy demand and driving range for electric vehicles with federated learning
10.1109/ojvt.2021.3065529 · 2021 · External reference
An efficient screening method for retired lithium-ion batteries based on support vector machine
10.1016/j.jclepro.2020.121882 · 2020 · External reference
Digital twin for battery systems: cloud battery management system with online state-of-charge and state-of-health estimation
10.1016/j.est.2020.101557 · 2020 · External reference
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Verification of a remaining flying time prediction system for small electric aircraft
2015 · External reference
Adaptation of an Electrochemistry-based Li-ion Battery Model to Account for Deterioration Observed Under Randomized Use
2014 · External reference
Particle-filtering-based prognosis framework for energy storage devices with a statistical characterization of state-of-health regeneration phenomena
10.1109/tim.2012.2215142 · 2012 · External reference
Health monitoring and remaining useful life estimation of lithium-ion aeronautical batteries
2012 · External reference
Dynamic battery remaining useful life estimation: an on-line data-driven approach
2012 · External reference
Model adaptation for prognostics in a particle filtering framework
2011 · External reference
Modeling Li-ion battery capacity depletion in a particle filtering framework
2009 · External reference
Major challenges in prognostics: study on benchmarking prognostic datasets
2012 · External reference
Data-driven prognostics for lithium-ion battery based on Gaussian process regression
2012 · External reference
An integrated health and contingency management case study on an autonomous ground robot
2011 · External reference
Study on impedance model of Li-ion battery
2011 · External reference
Transient behavior modeling and physical meaning analysis for battery
2010 · External reference
Designing data-driven battery prognostic approaches for variable loading profiles: Some lessons learned
2012 · External reference
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Prognostics of lithium-ion batteries based on Dempster–Shafer theory and the Bayesian Monte Carlo method
10.1016/j.jpowsour.2011.08.040 · 2011 · External reference
Comparative analysis of features for determining state of health in lithium-ion batteries
2013 · External reference
An ensemble model for predicting the remaining useful performance of lithium-ion batteries
10.1016/j.microrel.2012.12.003 · 2013 · External reference
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Closed-loop optimization of fast-charging protocols for batteries with machine learning
10.1038/s41586-020-1994-5 · 2020 · External reference
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Intrinsic variability in the degradation of a batch of commercial 18650 lithium-ion cells
10.3390/en11051031 · 2018 · External reference
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D2.3 - Report Containing Aging Test Profiles and Test Results
2020 · External reference
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An advanced microstructural and electrochemical datasheet on 18650 Li-ion batteries with nickel-rich NMC811 cathodes and graphite-silicon anodes
10.1149/1945-7111/abc4c1 · 2020 · External reference
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A rapid online calculation method for state of health of lithium-ion battery based on coulomb counting method and differential voltage analysis
10.1016/j.jpowsour.2020.228740 · 2020 · External reference
A data-driven Coulomb counting method for state of charge calibration and estimation of lithium-ion battery
2020 · External reference
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Learning human-understandable models for the health assessment of Li-ion batteries via multi-objective genetic programming
10.1016/j.engappai.2019.08.013 · 2019 · External reference
Driving cycle testing of electric vehicle batteries and systems
10.1016/0378-7753(92)80039-e · 1992 · External reference
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A Simplified Battery Discharge Profile Based Upon the Federal Urban Driving Schedule
1988 · External reference
The ARTEMIS european driving cycles for measuring car pollutant emissions
10.1016/j.scitotenv.2004.04.070 · 2004 · External reference
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Lg 18650HG2 Li-ion battery data and example deep neural network xEV SOC estimator script
2020 · External reference
Long short-term memory networks for accurate state-of-charge estimation of Li-ion batteries
10.1109/tie.2017.2787586 · 2018 · External reference
Stacked bidirectional long short-term memory networks for state-of-charge estimation of lithium-ion batteries
10.1016/j.energy.2019.116538 · 2020 · External reference
A compact methodology via a recurrent neural network for accurate equivalent circuit type modeling of lithium-ion batteries
10.1109/tia.2018.2874588 · 2019 · External reference
Li-ion battery model performance for automotive drive cycles with current pulse and EIS parameterization
2017 · External reference
Robust xEV battery state-of-charge estimator design using a feedforward deep neural network
10.4271/2020-01-1181 · 2020 · External reference
Li-ion battery state of charge estimation using long short-term memory recurrent neural network with transfer learning
2019 · External reference
Modeling and state-of-charge prediction of lithium-ion battery and ultracapacitor hybrids with a co-estimator
10.1016/j.energy.2017.01.044 · 2017 · External reference
Experimental data of lithium-ion battery and ultracapacitor under DST and UDDS profiles at room temperature
10.1016/j.dib.2017.01.019 · 2017 · External reference
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State of charge estimation for Li-ion batteries using neural network modeling and unscented Kalman filter-based error cancellation
10.1016/j.ijepes.2014.04.059 · 2014 · External reference
State of charge estimation of lithium-ion batteries using the open-circuit voltage at various ambient temperatures
10.1016/j.apenergy.2013.07.008 · 2014 · External reference
Influence of different open circuit voltage tests on state of charge online estimation for lithium-ion batteries
10.1016/j.apenergy.2016.09.010 · 2016 · External reference
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10.1016/j.electacta.2021.138524
10.1016/j.electacta.2021.138524 · External reference
10.1016/j.est.2020.101552
10.1016/j.est.2020.101552 · External reference
Prediction of constant power delivery of lithium-ion cells at high loads
10.1016/j.est.2020.101552 · 2020 · External reference
Electrochemical impedance spectroscopy for all-solid-state batteries: theory, methods and future outlook
10.1002/celc.202100108 · 2021 · External reference
Lithium-ion capacitor–characterization and development of new electrical model
10.1016/j.energy.2015.02.069 · 2015 · External reference
10.1038/s41467-020-15235-7
10.1038/s41467-020-15235-7 · External reference
A comparison between electrochemical impedance spectroscopy and incremental capacity-differential voltage as Li-ion diagnostic techniques to identify and quantify the effects of degradation modes within battery management systems
10.1016/j.jpowsour.2017.03.042 · 2017 · External reference
Long-term low-rate cycling of LiCoO2/graphite Li-ion cells at 55 °C
10.1149/2.056206jes · 2012 · External reference
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HIRF battery data set
2015 · External reference
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Small satellite power simulation data set
2015 · External reference
A battery certification testbed for small satellite missions
2015 · External reference
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Generation of synthetic battery data with capacity variation
2019 · External reference
Capacity fade estimation using supervised learning
2017 · External reference
Big data training data for artificial intelligence-based Li-ion diagnosis and prognosis
10.1016/j.jpowsour.2020.228806 · 2020 · External reference
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Analysis of synthetic voltage vs. capacity datasets for big data Li-ion diagnosis and prognosis
10.3390/en14092371 · 2021 · External reference
A study of cell-to-cell interactions and degradation in parallel strings: implications for the battery management system
10.1016/j.jpowsour.2016.07.121 · 2016 · External reference
10.1016/j.jpowsour.2017.03.042
10.1016/j.jpowsour.2017.03.042 · External reference
Intelligent state of health estimation for lithium-ion battery pack based on big data analysis
10.1016/j.est.2020.101836 · 2020 · External reference
A hybrid statistical data-driven method for on-line joint state estimation of lithium-ion batteries
10.1016/j.apenergy.2019.114408 · 2020 · External reference
Dremus: a data-restricted multi-physics simulation model for lithium-ion battery storage
10.1016/j.est.2020.102051 · 2020 · External reference
An evaluation study of different modelling techniques for calendar ageing prediction of lithium-ion batteries
10.1016/j.rser.2020.110017 · 2020 · External reference
Early detection of anomalous degradation behavior in lithium-ion batteries
10.1016/j.est.2020.101710 · 2020 · External reference
Capacity estimation for lithium-ion battery using experimental feature interval approach
10.1016/j.energy.2020.117778 · 2020 · External reference
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Beep: a python library for battery evaluation and early prediction
10.1016/j.softx.2020.100506 · 2020 · External reference
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A Bayesian view on the Hilbert transform and the Kramers–Kronig transform of electrochemical impedance data: Probabilistic estimates and quality scores
10.1016/j.electacta.2020.136864 · 2020 · External reference
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