Related references
Note: Only part of the references are listed.Optimal pool composition of commercial electric vehicles in V2G fleet operation of various electricity markets
Benedikt Tepe et al.
APPLIED ENERGY (2022)
Framework for measurement of battery state-of-health (resistance) integrating overpotential effects and entropy changes using energy equilibrium
Karanjot Singh et al.
ENERGY (2022)
Reliability assessment and lifetime prediction of Li-ion batteries for electric vehicles
S. Micari et al.
ELECTRICAL ENGINEERING (2022)
Forecasting: theory and practice
Fotios Petropoulos et al.
INTERNATIONAL JOURNAL OF FORECASTING (2022)
Artificial Intelligence Applied to Battery Research: Hype or Reality?
Teo Lombardo et al.
CHEMICAL REVIEWS (2022)
A hybrid method with cascaded structure for early-stage remaining useful life prediction of lithium-ion battery
Lisen Yan et al.
ENERGY (2022)
Lithium-Ion Batteries Long Horizon Health Prognostic Using Machine Learning
Safieh Bamati et al.
IEEE TRANSACTIONS ON ENERGY CONVERSION (2022)
Automated Feature Extraction and Selection for Data-Driven Models of Rapid Battery Capacity Fade and End of Life
Samuel Greenbank et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2022)
Decay mechanism and capacity prediction of lithium-ion batteries under low-temperature near-adiabatic condition
Hongxun Liu et al.
INORGANIC CHEMISTRY COMMUNICATIONS (2022)
A machine learning-based framework for online prediction of battery ageing trajectory and lifetime using histogram data
Yizhou Zhang et al.
JOURNAL OF POWER SOURCES (2022)
Review-Knees in Lithium-Ion Battery Aging Trajectories
Peter M. Attia et al.
JOURNAL OF THE ELECTROCHEMICAL SOCIETY (2022)
Fast Modeling of the Capacity Degradation of Lithium-Ion Batteries via a Conditional Temporal Convolutional Encoder-Decoder
Jianxiang Wang et al.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION (2022)
A fractional-order model for calendar aging with dynamic storage conditions
Juan Antonio Lopez-Villanueva et al.
JOURNAL OF ENERGY STORAGE (2022)
Prediction of Battery SOH by CNN-BiLSTM Network Fused with Attention Mechanism
Shuo Sun et al.
ENERGIES (2022)
Probabilistic Modeling of Li-Ion Battery Remaining Useful Life
Elio Chiodo et al.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS (2022)
Forecasting battery capacity and power degradation with multi-task learning
Weihan Li et al.
ENERGY STORAGE MATERIALS (2022)
Impedance-based forecasting of lithium-ion battery performance amid uneven usage
Penelope K. Jones et al.
NATURE COMMUNICATIONS (2022)
Multivariable Fractional Polynomials for lithium-ion batteries degradation models under dynamic conditions
Clara Bertinelli Salucci et al.
JOURNAL OF ENERGY STORAGE (2022)
Statistical distribution of Lithium-ion batteries useful life and its application for battery pack reliability
Shuen-Lin Jeng et al.
JOURNAL OF ENERGY STORAGE (2022)
Modeling capacity fade of lithium-ion batteries during dynamic cycling considering path dependence
Alexander Karger et al.
JOURNAL OF ENERGY STORAGE (2022)
Towards Long Lifetime Battery: AI-Based Manufacturing and Management
Kailong Liu et al.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA (2022)
Accelerated Stress Factors Based Nonlinear Wiener Process Model for Lithium-Ion Battery Prognostics
Jin-Zhen Kong et al.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2022)
Aging aware operation of lithium-ion battery energy storage systems: A review
Nils Collath et al.
JOURNAL OF ENERGY STORAGE (2022)
Battery degradation prediction against uncertain future conditions with recurrent neural network enabled deep learning
Jiahuan Lu et al.
ENERGY STORAGE MATERIALS (2022)
A rest-time-based prognostic model for remaining useful life prediction of lithium-ion battery
Liming Deng et al.
NEURAL COMPUTING & APPLICATIONS (2021)
State of Health Prediction of Lithium-Ion Batteries Using Accelerated Degradation Test Data
Pasquale De Falco et al.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS (2021)
Battery lifetime prediction and performance assessment of different modeling approaches
Md Sazzad Hosen et al.
ISCIENCE (2021)
Hybrid physics-informed neural networks for lithium-ion battery modeling and prognosis
Renato G. Nascimento et al.
JOURNAL OF POWER SOURCES (2021)
Physics-based prognostics of implantable-grade lithium-ion battery for remaining useful life prediction
Yu Hui Lui et al.
JOURNAL OF POWER SOURCES (2021)
Challenging Practices of Algebraic Battery Life Models through Statistical Validation and Model Identification via Machine-Learning
Paul Gasper et al.
JOURNAL OF THE ELECTROCHEMICAL SOCIETY (2021)
Perspective-Combining Physics and Machine Learning to Predict Battery Lifetime
Muratahan Aykol et al.
JOURNAL OF THE ELECTROCHEMICAL SOCIETY (2021)
Remaining Useful Life Prediction of Lithium-ion Batteries Based on Wiener Process Under Time-Varying Temperature Condition
Xiaodong Xu et al.
RELIABILITY ENGINEERING & SYSTEM SAFETY (2021)
A critical review of improved deep learning methods for the remaining useful life prediction of lithium-ion batteries
Shunli Wang et al.
ENERGY REPORTS (2021)
State of health forecasting of Lithium-ion batteries applicable in real-world operational conditions
Friedrich von Buelow et al.
JOURNAL OF ENERGY STORAGE (2021)
Predicting battery end of life from solar off-grid system field data using machine learning
Antti Aitio et al.
JOULE (2021)
Kernel recursive least square tracker and long-short term memory ensemble based battery health prognostic model
Muhammad Umair Ali et al.
ISCIENCE (2021)
Novel Data-Efficient Mechanism-Agnostic Capacity Fade Model for Li-Ion Batteries
Minho Kim et al.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2021)
Cycle-life prediction model of lithium iron phosphate-based lithium-ion battery module
Dae Hyun Jung et al.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH (2021)
A generative adversarial network-based synthetic data augmentation technique for battery condition evaluation
Falak Naaz et al.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH (2021)
Statistical Learning for Accurate and Interpretable Battery Lifetime Prediction
Peter M. Attia et al.
JOURNAL OF THE ELECTROCHEMICAL SOCIETY (2021)
Solid-State Lithium Battery Cycle Life Prediction Using Machine Learning
Danpeng Cheng et al.
APPLIED SCIENCES-BASEL (2021)
Battery Durability and Reliability under Electric Utility Grid Operations: Analysis of On-Site Reference Tests
Matthieu Dubarry et al.
ELECTRONICS (2021)
Battery cycle life study through relaxation and forecasting the lifetime via machine learning
Md Sazzad Hosen et al.
JOURNAL OF ENERGY STORAGE (2021)
Modelling the cycling degradation of Li-ion batteries: Chemistry influenced stress factors
Josu Olmos et al.
JOURNAL OF ENERGY STORAGE (2021)
Forecasting state-of-health of lithium-ion batteries using variational long short-term memory with transfer learning
Seongyoon Kim et al.
JOURNAL OF ENERGY STORAGE (2021)
The challenge and opportunity of battery lifetime prediction from field data
Valentin Sulzer et al.
JOULE (2021)
Feature Extraction, Ageing Modelling and Information Analysis of a Large-Scale Battery Ageing Experiment
Jose Genario Jr Jr de Oliveira et al.
ENERGIES (2021)
A Review of Lithium-Ion Battery State of Health Estimation and Prediction Methods
Lei Yao et al.
WORLD ELECTRIC VEHICLE JOURNAL (2021)
Application Dependent End-of-Life Threshold Definition Methodology for Batteries in Electric Vehicles
Mikel Arrinda et al.
BATTERIES-BASEL (2021)
Deep convolutional neural networks with ensemble learning and transfer learning for capacity estimation of lithium-ion batteries
Sheng Shen et al.
APPLIED ENERGY (2020)
Analysis and modeling of cycle aging of a commercial LiFePO4/graphite cell
Maik Naumann et al.
JOURNAL OF POWER SOURCES (2020)
Battery prognostics at different operating conditions
Dong Wang et al.
MEASUREMENT (2020)
Closed-loop optimization of fast-charging protocols for batteries with machine learning
Peter M. Attia et al.
NATURE (2020)
Ensemble Model Based on Stacked Long Short-Term Memory Model for Cycle Life Prediction of Lithium-Ion Batteries
Fu-Kwun Wang et al.
APPLIED SCIENCES-BASEL (2020)
Gaussian Process Regression With Automatic Relevance Determination Kernel for Calendar Aging Prediction of Lithium-Ion Batteries
Kailong Liu et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2020)
Model Migration Neural Network for Predicting Battery Aging Trajectories
Xiaopeng Tang et al.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION (2020)
An evaluation study of different modelling techniques for calendar ageing prediction of lithium-ion batteries
Kailong Liu et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2020)
A fast screening framework for second-life batteries based on an improved bisecting K-means algorithm combined with fast pulse test
Zihao Zhou et al.
JOURNAL OF ENERGY STORAGE (2020)
Stochastic capacity loss and remaining useful life models for lithium-ion batteries in plug-in hybrid electric vehicles
Andrew Chu et al.
JOURNAL OF POWER SOURCES (2020)
Intelligent state of health estimation for lithium-ion battery pack based on big data analysis
Lingjun Song et al.
JOURNAL OF ENERGY STORAGE (2020)
Experimental assessment of cycling ageing of lithium-ion second-life batteries from electric vehicles
Elisa Braco et al.
JOURNAL OF ENERGY STORAGE (2020)
A novel deep learning framework for state of health estimation of lithium-ion battery
Yaxiang Fan et al.
JOURNAL OF ENERGY STORAGE (2020)
Towards the swift prediction of the remaining useful life of lithium-ion batteries with end-to-end deep learning
Joonki Hong et al.
APPLIED ENERGY (2020)
From Cell to Battery System in BEVs: Analysis of System Packing Efficiency and Cell Types
Hendrik Loebberding et al.
WORLD ELECTRIC VEHICLE JOURNAL (2020)
A Review of Battery State of Health Estimation Methods: Hybrid Electric Vehicle Challenges
Nassim Noura et al.
WORLD ELECTRIC VEHICLE JOURNAL (2020)
Battery Electric Vehicle Fast Charging-Evidence from the Norwegian Market
Erik Figenbaum
WORLD ELECTRIC VEHICLE JOURNAL (2020)
Predicting the state of charge and health of batteries using data-driven machine learning
Man-Fai Ng et al.
NATURE MACHINE INTELLIGENCE (2020)
State-of-life prognosis and diagnosis of lithium-ion batteries by data-driven particle filters
F. Cadini et al.
APPLIED ENERGY (2019)
Modeling memoryless degradation under variable stress
Edward Thomas et al.
JOURNAL OF QUALITY TECHNOLOGY (2019)
Data-driven prediction of battery cycle life before capacity degradation
Kristen A. Severson et al.
NATURE ENERGY (2019)
A comparison of methodologies for the non-invasive characterisation of commercial Li-ion cells
Anup Barai et al.
PROGRESS IN ENERGY AND COMBUSTION SCIENCE (2019)
A hybrid prognostic method for system degradation based on particle filter and relevance vector machine
Yang Chang et al.
RELIABILITY ENGINEERING & SYSTEM SAFETY (2019)
Battery health prediction under generalized conditions using a Gaussian process transition model
Robert R. Richardson et al.
JOURNAL OF ENERGY STORAGE (2019)
State estimation for advanced battery management: Key challenges and future trends
Xiaosong Hu et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2019)
Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review
Yi Li et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2019)
A coulombic efficiency-based model for prognostics and health estimation of lithium-ion batteries
Fangfang Yang et al.
ENERGY (2019)
Long-term degradation based analysis for lithium-ion batteries in off-grid wind-battery renewable energy systems
Milad Ghorbanzadeh et al.
ENERGY (2019)
Piecewise model based intelligent prognostics for state of health prediction of rechargeable batteries with capacity regeneration phenomena
Dong Wang et al.
MEASUREMENT (2019)
A review on prognostics and health management (PHM) methods of lithium-ion batteries
Huixing Meng et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2019)
Modified Gaussian Process Regression Models for Cyclic Capacity Prediction of Lithium-Ion Batteries
Kailong Liu et al.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION (2019)
A survey on Image Data Augmentation for Deep Learning
Connor Shorten et al.
JOURNAL OF BIG DATA (2019)
Review and Performance Comparison of Mechanical-Chemical Degradation Models for Lithium-Ion Batteries
Jorn M. Reniers et al.
JOURNAL OF THE ELECTROCHEMICAL SOCIETY (2019)
Technical Viability of Battery Second Life: A Study From the Ageing Perspective
Egoitz Martinez-Laserna et al.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS (2018)
A novel Gaussian process regression model for state-of-health estimation of lithium-ion battery using charging curve
Duo Yang et al.
JOURNAL OF POWER SOURCES (2018)
A new state-of-health estimation method for lithium-ion batteries through the intrinsic relationship between ohmic internal resistance and capacity
Lin Chen et al.
MEASUREMENT (2018)
Modeling of Lithium-Ion Battery Degradation for Cell Life Assessment
Bolun Xu et al.
IEEE TRANSACTIONS ON SMART GRID (2018)
Current status and challenges for automotive battery production technologies
Arno Kwade et al.
NATURE ENERGY (2018)
Co-Estimation of State of Charge and State of Health for Lithium-Ion Batteries Based on Fractional-Order Calculus
Xiaosong Hu et al.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2018)
A review of state of health and remaining useful life estimation methods for lithium-ion battery in electric vehicles: Challenges and recommendations
M. S. Hossain Lipu et al.
JOURNAL OF CLEANER PRODUCTION (2018)
A critical review on self-adaptive Li-ion battery ageing models
M. Lucu et al.
JOURNAL OF POWER SOURCES (2018)
Cycle Life Prediction of Aged Lithium-Ion Batteries from the Fading Trajectory of a Four-Parameter Model
Je-Feng Li et al.
JOURNAL OF THE ELECTROCHEMICAL SOCIETY (2018)
Indirect State-of-Health Estimation for Lithium-Ion Batteries under Randomized Use
Jinsong Yu et al.
ENERGIES (2017)
A probabilistic approach for prognosis of battery pack aging
Chin-Yao Chang et al.
JOURNAL OF POWER SOURCES (2017)
Gaussian process regression for forecasting battery state of health
Robert R. Richardson et al.
JOURNAL OF POWER SOURCES (2017)
A Database for Comparative Electrochemical Performance of Commercial 18650-Format Lithium-Ion Cells
Heather M. Barkholtz et al.
JOURNAL OF THE ELECTROCHEMICAL SOCIETY (2017)
An improved wrapper-based feature selection method for machinery fault diagnosis
Kar Hoou Hui et al.
PLOS ONE (2017)
Combined cycling and calendar capacity fade modeling of a Nickel-Manganese-Cobalt Oxide Cell with real-life profile validation
Joris de Hoog et al.
APPLIED ENERGY (2017)
Quantifying Uncertainties in Reusing Lithium-Ion Batteries from Electric Vehicles
S. Rohr et al.
14TH GLOBAL CONFERENCE ON SUSTAINABLE MANUFACTURING, GCSM 2016 (2017)
Impact of battery degradation on energy arbitrage revenue of grid-level energy storage
Florian Wankmueller et al.
JOURNAL OF ENERGY STORAGE (2017)
Energy state of health estimation for battery packs based on the degradation and inconsistency
Weiping Diao et al.
PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON APPLIED ENERGY (2017)
Realistic lifetime prediction approach for Li-ion batteries
E. Sarasketa-Zabala et al.
APPLIED ENERGY (2016)
Forecasting the State of Health of Electric Vehicle Batteries to Evaluate the Viability of Car Sharing Practices
Ivana Semanjski et al.
ENERGIES (2016)
A novel state of health estimation method of Li-ion battery using group method of data handling
Ji Wu et al.
JOURNAL OF POWER SOURCES (2016)
Modelling and experimental evaluation of parallel connected lithium ion cells for an electric vehicle battery system
Thomas Bruen et al.
JOURNAL OF POWER SOURCES (2016)
Cycle life testing and modeling of graphite/LiCoO2 cells under different state of charge ranges
Saurabh Saxena et al.
JOURNAL OF POWER SOURCES (2016)
Review of the Remaining Useful Life Prognostics of Vehicle Lithium-Ion Batteries Using Data-Driven Methodologies
Lifeng Wu et al.
APPLIED SCIENCES-BASEL (2016)
Capacity and power fade cycle-life model for plug-in hybrid electric vehicle lithium-ion battery cells containing blended spinel and layered-oxide positive electrodes
Andrea Cordoba-Arenas et al.
JOURNAL OF POWER SOURCES (2015)
A Bayesian approach for Li-Ion battery capacity fade modeling and cycles to failure prognostics
Jian Guo et al.
JOURNAL OF POWER SOURCES (2015)
A multi time-scale state-of-charge and state-of-health estimation framework using nonlinear predictive filter for lithium-ion battery pack with passive balance control
Yin Hua et al.
JOURNAL OF POWER SOURCES (2015)
Critical review of on-board capacity estimation techniques for lithium-ion batteries in electric and hybrid electric vehicles
Alexander Farmann et al.
JOURNAL OF POWER SOURCES (2015)
Transfer Learning for Visual Categorization: A Survey
Ling Shao et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2015)
A Capacity Fading Model of Lithium-Ion Battery Cycle Life Based on the Kinetics of Side Reactions for Electric Vehicle Applications
Weijun Gu et al.
ELECTROCHIMICA ACTA (2014)
Optimal scheduling of electric vehicle charging and vehicle-to-grid services at household level including battery degradation and price uncertainty
Miguel A. Ortega-Vazquez
IET GENERATION TRANSMISSION & DISTRIBUTION (2014)
The impact of range anxiety and home, workplace, and public charging infrastructure on simulated battery electric vehicle lifetime utility
Jeremy Neubauer et al.
JOURNAL OF POWER SOURCES (2014)
Review and recent advances in battery health monitoring and prognostics technologies for electric vehicle (EV) safety and mobility
Seyed Mohammad Rezvanizaniani et al.
JOURNAL OF POWER SOURCES (2014)
Statistical analysis for understanding and predicting battery degradations in real-life electric vehicle use
Anthony Barre et al.
JOURNAL OF POWER SOURCES (2014)
State of health estimation for lithium ion batteries based on charging curves
Zhen Guo et al.
JOURNAL OF POWER SOURCES (2014)
Calendar aging of commercial graphite/LiFePO4 cell - Predicting capacity fade under time dependent storage conditions
Sebastien Grolleau et al.
JOURNAL OF POWER SOURCES (2014)
Production caused variation in capacity aging trend and correlation to initial cell performance
Thorsten Baumhoefer et al.
JOURNAL OF POWER SOURCES (2014)
Critical review of the methods for monitoring of lithium-ion batteries in electric and hybrid vehicles
Wladislaw Waag et al.
JOURNAL OF POWER SOURCES (2014)
Health diagnosis and remaining useful life prognostics of lithium-ion batteries using data-driven methods
Adnan Nuhic et al.
JOURNAL OF POWER SOURCES (2013)
A review on the key issues for lithium-ion battery management in electric vehicles
Languang Lu et al.
JOURNAL OF POWER SOURCES (2013)
On-board state-of-health monitoring of lithium-ion batteries using linear parameter-varying models
Juergen Remmlinger et al.
JOURNAL OF POWER SOURCES (2013)
A review on lithium-ion battery ageing mechanisms and estimations for automotive applications
Anthony Barre 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)
Prognostics for state of health estimation of lithium-ion batteries based on combination Gaussian process functional regression
Datong Liu et al.
MICROELECTRONICS RELIABILITY (2013)
Degradation of Lithium Ion Batteries under Complex Conditions of Use
Heinz Wenzl et al.
ZEITSCHRIFT FUR PHYSIKALISCHE CHEMIE-INTERNATIONAL JOURNAL OF RESEARCH IN PHYSICAL CHEMISTRY & CHEMICAL PHYSICS (2013)
Rate-based degradation modeling of lithium-ion cells
E. V. Thomas et al.
JOURNAL OF POWER SOURCES (2012)
Development of a lifetime prediction model for lithium-ion batteries based on extended accelerated aging test data
Madeleine Ecker et al.
JOURNAL OF POWER SOURCES (2012)
Prognostics of lithium-ion batteries based on Dempster-Shafer theory and the Bayesian Monte Carlo method
Wei He et al.
JOURNAL OF POWER SOURCES (2011)
A review on prognostics and health monitoring of Li-ion battery
Jingliang Zhang et al.
JOURNAL OF POWER SOURCES (2011)
A Survey on Transfer Learning
Sinno Jialin Pan et al.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING (2010)
Life Prediction Methods for Lithium-Ion Batteries Derived from a Fatigue Approach II. Capacity-Loss Prediction of Batteries Subjected to Complex Current Profiles
M. Safari et al.
JOURNAL OF THE ELECTROCHEMICAL SOCIETY (2010)
Gaussian process functional regression Modeling for batch data
J. Q. Shi et al.
BIOMETRICS (2007)
A review on machinery diagnostics and prognostics implementing condition-based maintenance
Andrew K. S. Jardine et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2006)
Life prediction of batteries for selecting the technically most suitable and cost effective battery
H Wenzl et al.
JOURNAL OF POWER SOURCES (2005)
The challenge to the automotive battery industry: the battery has to become an increasingly integrated component within the vehicle electric power system
E Meissner et al.
JOURNAL OF POWER SOURCES (2005)
Capacity fade study of lithium-ion batteries cycled at high discharge rates
G Ning et al.
JOURNAL OF POWER SOURCES (2003)
A model for battery lifetime analysis for organizing applications on a pocket computer
D Rakhmatov et al.
IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS (2003)
A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking
MS Arulampalam et al.
IEEE TRANSACTIONS ON SIGNAL PROCESSING (2002)
Improving neural network training solutions using regularisation
S Mc Loone et al.
NEUROCOMPUTING (2001)