The role of artificial intelligence in the mass adoption of electric vehicles
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Title
The role of artificial intelligence in the mass adoption of electric vehicles
Authors
Keywords
artificial intelligence, electric vehicle, electric vehicle charging station, smart grid
Journal
Joule
Volume 5, Issue 9, Pages 2296-2322
Publisher
Elsevier BV
Online
2021-08-11
DOI
10.1016/j.joule.2021.07.012
References
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Note: Only part of the references are listed.- A novel intelligent method for fault diagnosis of electric vehicle battery system based on wavelet neural network
- (2020) Lei Yao et al. JOURNAL OF POWER SOURCES
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- (2020) Peter M. Attia et al. NATURE
- A Critical Review of Machine Learning of Energy Materials
- (2020) Chi Chen et al. Advanced Energy Materials
- Real-time range estimation in electric vehicles using fuzzy logic classifier
- (2020) Süleyman Çeven et al. COMPUTERS & ELECTRICAL ENGINEERING
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- (2020) Qingqing Yang et al. ENERGY
- Optimization of Heterogeneous Ternary Li3PO4-Li3BO3-Li2SO4 Mixture for Li-ion Conductivity by Machine Learning
- (2020) Kenji Homma et al. Journal of Physical Chemistry C
- Co-estimation of lithium-ion battery state of charge and state of temperature based on a hybrid electrochemical-thermal-neural-network model
- (2020) Fei Feng et al. JOURNAL OF POWER SOURCES
- Evolutionary algorithms and their applications to engineering problems
- (2020) Adam Slowik et al. NEURAL COMPUTING & APPLICATIONS
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- (2020) Konstantina Valogianni et al. PRODUCTION AND OPERATIONS MANAGEMENT
- Toward Enhanced State of Charge Estimation of Lithium-ion Batteries Using Optimized Machine Learning Techniques
- (2020) M. A. Hannan et al. Scientific Reports
- Intelligent Controller Design by the Artificial Intelligence Methods
- (2020) Jana Nowaková et al. SENSORS
- Pores for thought: generative adversarial networks for stochastic reconstruction of 3D multi-phase electrode microstructures with periodic boundaries
- (2020) Andrea Gayon-Lombardo et al. npj Computational Materials
- Digital twin for battery systems: Cloud battery management system with online state-of-charge and state-of-health estimation
- (2020) Weihan Li et al. Journal of Energy Storage
- Artificial intelligence and machine learning for targeted energy storage solutions
- (2020) Dean H. Barrett et al. Current Opinion in Electrochemistry
- Machine learning for chemical discovery
- (2020) Alexandre Tkatchenko Nature Communications
- Machine learning‐based model for lithium‐ion batteries in BMS of electric/hybrid electric aircraft
- (2020) Seyed Reza Hashemi et al. INTERNATIONAL JOURNAL OF ENERGY RESEARCH
- Data-driven assessment of electrode calendering process by combining experimental results, in silico mesostructures generation and machine learning
- (2020) Marc Duquesnoy et al. JOURNAL OF POWER SOURCES
- The Application of Data-Driven Methods and Physics-Based Learning for Improving Battery Safety
- (2020) Donal P. Finegan et al. Joule
- Mass load prediction for lithium-ion battery electrode clean production: A machine learning approach
- (2020) Kailong Liu et al. JOURNAL OF CLEANER PRODUCTION
- A Neural Network Based Method for Thermal Fault Detection in Lithium-Ion Batteries
- (2020) Olaoluwa Ojo et al. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
- Connected and Autonomous Electric Vehicles (CAEVs)
- (2019) Ala Abu Alkheir et al. IT Professional
- Data-driven prediction of battery cycle life before capacity degradation
- (2019) Kristen A. Severson et al. Nature Energy
- Predicting the Electrochemical Properties of Lithium-Ion Battery Electrode Materials with the Quantum Neural Network Algorithm
- (2019) Hwanho Choi et al. Journal of Physical Chemistry C
- Prediction of Electric Vehicle Range: A Comprehensive Review of Current Issues and Challenges
- (2019) Bogdan Varga et al. Energies
- Implementation of machine learning based real time range estimation method without destination knowledge for BEVs
- (2019) H.A. Yavasoglu et al. ENERGY
- State-of-charge estimation of lithium-ion batteries based on gated recurrent neural network
- (2019) Fangfang Yang et al. ENERGY
- Density functional theory calculations: A powerful tool to simulate and design high-performance energy storage and conversion materials
- (2019) Xi Wu et al. Progress in Natural Science-Materials International
- A Stochastic Range Estimation Algorithm for Electric Vehicles Using Traffic Phase Classification
- (2019) Stefan Scheubner et al. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
- A Comprehensive Approach for the Clustering of Similar-Performance Cells for the Design of a Lithium-Ion Battery Module for Electric Vehicles
- (2019) Wei Li et al. Engineering
- Electric Vehicle Charging Load Forecasting: A Comparative Study of Deep Learning Approaches
- (2019) Juncheng Zhu et al. Energies
- Data‐Driven Materials Science: Status, Challenges, and Perspectives
- (2019) Lauri Himanen et al. Advanced Science
- Ensemble machine learning-based algorithm for electric vehicle user behavior prediction
- (2019) Yu-Wei Chung et al. APPLIED ENERGY
- An intelligent braking system composed single-pedal and multi-objective optimization neural network braking control strategies for electric vehicle
- (2019) Hongwen He et al. APPLIED ENERGY
- Nature-Inspired Optimization Algorithms Applied for Solving Charging Station Placement Problem: Overview and Comparison
- (2019) Sanchari Deb et al. ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
- State-of-Health Estimation of Li-ion Batteries in Electric Vehicle Using IndRNN under Variable Load Condition
- (2019) Prakash Venugopal et al. Energies
- A survey of deep learning techniques for autonomous driving
- (2019) Sorin Grigorescu et al. Journal of Field Robotics
- Recycling lithium-ion batteries from electric vehicles
- (2019) Gavin Harper et al. NATURE
- Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review
- (2019) Yi Li et al. RENEWABLE & SUSTAINABLE ENERGY REVIEWS
- Electric vehicle charging station locations: Elastic demand, station congestion, and network equilibrium
- (2019) Yantao Huang et al. TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
- Power prediction for electric vehicles using online machine learning
- (2019) Stephan Rhode et al. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- Equivalent circuit model recognition of electrochemical impedance spectroscopy via machine learning
- (2019) Shan Zhu et al. JOURNAL OF ELECTROANALYTICAL CHEMISTRY
- Evaluation of batteries residual energy for battery pack recycling: Proposition of stack stress-coupled-AI approach
- (2019) Akhil Garg et al. Journal of Energy Storage
- Swarm-Intelligence Tuned Current Reduction for Power-Assisted Steering Control in Electric Vehicles
- (2018) Rabiatuladawiah Abu Hanifah et al. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
- A data-driven statistical approach for extending electric vehicle charging infrastructure
- (2018) Dario Pevec et al. INTERNATIONAL JOURNAL OF ENERGY RESEARCH
- Application of artificial neural networks in design of lithium-ion batteries
- (2018) Bin Wu et al. JOURNAL OF POWER SOURCES
- A New Method for Determining the Concentration of Electrolyte Components in Lithium-Ion Cells, Using Fourier Transform Infrared Spectroscopy and Machine Learning
- (2018) L. D. Ellis et al. JOURNAL OF THE ELECTROCHEMICAL SOCIETY
- Critical Review on the Battery State of Charge Estimation Methods for Electric Vehicles
- (2018) Rui Xiong et al. IEEE Access
- Safety modelling and testing of lithium-ion batteries in electrified vehicles
- (2018) Jie Deng et al. Nature Energy
- Machine learning assisted optimization of electrochemical properties for Ni-rich cathode materials
- (2018) Kyoungmin Min et al. Scientific Reports
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- (2018) Austin D. Sendek et al. CHEMISTRY OF MATERIALS
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- (2018) Jorge García Álvarez et al. Energies
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- (2018) Xingshuo Li et al. RENEWABLE ENERGY
- Fabrication of Anode of Aqueous Energy Storage System via Supersonic Cold Spraying
- (2018) Moin Ahmed et al. ChemElectroChem
- Development of a Bayesian network model for optimal site selection of electric vehicle charging station
- (2018) Seyedmohsen Hosseini et al. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
- Research on the Optimal Charging Strategy for Li-Ion Batteries Based on Multi-Objective Optimization
- (2017) Haitao Min et al. Energies
- Optimal Planning of Charging for Plug-In Electric Vehicles Focusing on Users’ Benefits
- (2017) Su Su et al. Energies
- A Comprehensive Study of Key Electric Vehicle (EV) Components, Technologies, Challenges, Impacts, and Future Direction of Development
- (2017) Fuad Un-Noor et al. Energies
- Optimal planning of electric vehicle charging station at the distribution system using hybrid optimization algorithm
- (2017) Abhishek Awasthi et al. ENERGY
- Artificial Intelligence Techniques in Smart Grid and Renewable Energy Systems—Some Example Applications
- (2017) Bimal K. Bose PROCEEDINGS OF THE IEEE
- Driving range estimation for electric vehicles based on driving condition identification and forecast
- (2017) Chaofeng Pan et al. AIP Advances
- A data-driven approach for characterising the charging demand of electric vehicles: A UK case study
- (2016) Erotokritos Xydas et al. APPLIED ENERGY
- A demand-side approach to the optimal deployment of electric vehicle charging stations in metropolitan areas
- (2016) N. Andrenacci et al. APPLIED ENERGY
- Application of machine learning methods for the prediction of crystal system of cathode materials in lithium-ion batteries
- (2016) M. Attarian Shandiz et al. COMPUTATIONAL MATERIALS SCIENCE
- Multi-agent based modeling for electric vehicle integration in a distribution network operation
- (2016) Junjie Hu et al. ELECTRIC POWER SYSTEMS RESEARCH
- Power reduction optimization with swarm based technique in electric power assist steering system
- (2016) Rabiatuladawiyah Abu Hanifah et al. ENERGY
- Methodology for assessing electric vehicle charging infrastructure business models
- (2016) Carlos Madina et al. ENERGY POLICY
- Integration of electric vehicles in smart grid: A review on vehicle to grid technologies and optimization techniques
- (2016) Kang Miao Tan et al. RENEWABLE & SUSTAINABLE ENERGY REVIEWS
- The Chemical Space Project
- (2015) Jean-Louis Reymond ACCOUNTS OF CHEMICAL RESEARCH
- A PSO-Based Fuzzy-Controlled Searching for the Optimal Charge Pattern of Li-Ion Batteries
- (2015) Shun-Chung Wang et al. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
- Fault detection of the connection of lithium-ion power batteries based on entropy for electric vehicles
- (2015) Lei Yao et al. JOURNAL OF POWER SOURCES
- Robust Optimization for Bidirectional Dispatch Coordination of Large-Scale V2G
- (2015) Xiaoqing Bai et al. IEEE Transactions on Smart Grid
- A Novel Big Data Modeling Method for Improving Driving Range Estimation of EVs
- (2015) Chung-Hong Lee et al. IEEE Access
- Electric Vehicle Charging on Residential Distribution Systems: Impacts and Mitigations
- (2015) Anamika Dubey et al. IEEE Access
- Regenerative Braking System of Electric Vehicle Driven by Brushless DC Motor
- (2014) Xiaohong Nian et al. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
- The impact of range anxiety and home, workplace, and public charging infrastructure on simulated battery electric vehicle lifetime utility
- (2014) Jeremy Neubauer et al. JOURNAL OF POWER SOURCES
- Electric vehicles and smart grid interaction: A review on vehicle to grid and renewable energy sources integration
- (2014) Francis Mwasilu et al. RENEWABLE & SUSTAINABLE ENERGY REVIEWS
- Statistical modeling of Electric Vehicle electricity consumption in the Victorian EV Trial, Australia
- (2014) Yong Bing Khoo et al. TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
- Smart Scheduling and Cost-Benefit Analysis of Grid-Enabled Electric Vehicles for Wind Power Integration
- (2014) Mahmoud Ghofrani et al. IEEE Transactions on Smart Grid
- Grid Power Peak Shaving and Valley Filling Using Vehicle-to-Grid Systems
- (2013) Zhenpo Wang et al. IEEE TRANSACTIONS ON POWER DELIVERY
- Accelerated Materials Design of Lithium Superionic Conductors Based on First-Principles Calculations and Machine Learning Algorithms
- (2013) Koji Fujimura et al. Advanced Energy Materials
- Commentary: The Materials Project: A materials genome approach to accelerating materials innovation
- (2013) Anubhav Jain et al. APL Materials
- Health diagnosis and remaining useful life prognostics of lithium-ion batteries using data-driven methods
- (2012) Adnan Nuhic et al. JOURNAL OF POWER SOURCES
- An Intelligent Regenerative Braking Strategy for Electric Vehicles
- (2011) Guoqing Xu et al. Energies
- Dynamic, Stochastic, Computational, and Scalable Technologies for Smart Grids
- (2011) Ganesh Venayagamoorthy IEEE Computational Intelligence Magazine
- Finding Nature’s Missing Ternary Oxide Compounds Using Machine Learning and Density Functional Theory
- (2010) Geoffroy Hautier et al. CHEMISTRY OF MATERIALS
- State-of-Charge Estimation for Lithium-Ion Batteries Using Neural Networks and EKF
- (2010) Mohammad Charkhgard et al. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
- Battery-Management System (BMS) and SOC Development for Electrical Vehicles
- (2010) K. W. E. Cheng et al. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
- Artificial intelligence applications in Permanent Magnet Brushless DC motor drives
- (2009) R. A. Gupta et al. ARTIFICIAL INTELLIGENCE REVIEW
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