BetaCitation Atlas

RESEARCH PAPER · SN Computer Science · 2024

Machine Learning in Lithium-Ion Battery: Applications, Challenges, and Future Trends

Alireza Valizadeh, Mohammad Hossein Amirhosseini

Read original paper ↗

See where this research leads.

55 direct citing papers in this saved network. Explore the next layer with second-order citations.

Open in your workspace →Saved 2026-10-14 · complete coverage
Filter Citing Papers
Press Enter or comma to add · × to remove · searches titles and available abstracts
Journals
All journals
Most represented first · select one or more
Explore Terms In These PapersHide SuggestionsShow Suggestions

Original and current center papers stay visible as anchors.
Numbers show citations received
42 direct citing works

Machine Learning in Lithium-Ion Battery: Applications, Challenges, and Future TrendsOriginalLeveraging Boosting Algorithms for Accurate Battery Life Prediction in Autonomous Robots0Next-Gen Electric Vehicle Battery Optimization: Enhancing RUL Prediction with Regression-Based Algorithms1Advancements and Challenges in Lithium-Ion Battery Lifecycle Management Toward a Sustainable Circular Economy for Electric Vehicles19Capacity Correction Enhances Battery Health Diagnosis Accuracy in Data Loss Scenarios for New Energy Vehicles0A Brief Overview of Modeling Estimation of State of Health for an Electric Vehicle’s Li-Ion Batteries13Comparative Analysis of LSTM and Bayesian Neural Networks for Lithium-Ion Battery Capacity Degradation Prediction2Carbonaceous Materials as Anodes for Lithium-Ion and Sodium-Ion Batteries48Utilizing Machine Learning to Predict the Charge Storage Capability of Lithium-Ion Battery Materials0Accelerating Battery Thermal Analysis by Integrating CFD Simulation and Machine Learning Techniques1A critical review on lithium ion battery modeling, battery management system and thermal runaway issues13Real Time Capacity Estimation For Lithium-Ion Battery Using Deep Transfer Learning1Fault Detection for Power Batteries Using a Generative Adversarial Network with a Convolutional Long Short-Term Memory (GAN-CNN-LSTM) Hybrid Model10MoExSOC: A Mixture of Experts Approach for Enhanced Battery State of Charge Estimation0Machine learning approach to the possible synergy between co-doped elements in the case of LiFePO4/C20State‐of‐the‐Art Machine Learning Technology for Sustainable Lithium Battery Cathode Design: A Perspective13Quantum Chemistry-Guided Machine Learning for Accelerated Design of CO 2 -Solubilizing Deep Eutectic Solvents14Next-generation battery energy management systems in electric vehicles: An overview of artificial intelligence14A Concise Overview of the Use of Low-Dimensional Molybdenum Disulfide as an Electrode Material for Li-Ion Batteries and Beyond3Capacity correction enhances battery health diagnosis accuracy in data loss scenarios for new energy vehicles1Artificial Intelligence and Digital Twin Technologies for Intelligent Lithium-Ion Battery Management Systems: A Comprehensive Review of State Estimation, Lifecycle Optimization, and Cloud-Edge Integration99Machine Learning-Based State of Charge Prediction for 21700 Lithium-Ion Batteries: A Comparative Study0AI Applications in Predictive Maintenance and Reliability of Batteries: Challenges and Future Directions0Interface engineering and safety in solid-state batteries: Advancing from human-centered insights to AI-driven innovations22Reinforcement learning for adaptive fault detection in lithium-ion batteries: a next-generation approach for electric vehicles2Machine Learning Techniques for Battery State of Health Prediction: A Comparative Review16AI-driven next-generation lithium-ion battery design automation (BDA) software5Battery management in electric aviation: A bibliometric review of technologies, regulations, and international collaborations3Data‐Driven Electrolyte Design for Advanced Rechargeable Lithium Batteries †17Data-Driven Performance Prediction of Lead–Carbon Batteries: Integrating Experimental Validation and Reduced-Order Model-Guided Neural Networks0Prediction of the Remaining Useful Life of Lithium-Ion Batteries Based on the Optimized TTAO-VMD-BiLSTM1Hybrid approach to battery management: Application of optimization and machine learning for sustainable energy solutions0NeuralProphet-Based Forecasting of State of Health (SOH) and Remaining Useful Life (RUL) in Lithium-ion Batteries0Unlocking a shortcut: acceleration of non-aqueous electrolyte development by active machine learning for sodium-based batteries0Machine learning-based battery life prediction and smart charging optimization for renewable energy storage systems1Theoretical modeling and performance prediction of magic-angle twisted bilayer graphene Sodium-Ion batteries: a multi-scale computational framework0Integration of Electro-Thermal Modelling and Temporal Deep Learning for Reliable State-of-Charge Estimation0Explainable Datadriven Digital Twins for Predicting Battery States in Electric Vehicles Using Deep Learning Models0A Review of Smart Lithium-Ion Battery Manufacturing: AI-enabled Decision and Control Approaches0Roadmaps for dendrite suppression in next generation lithium-ion batteries: Toward sustainable energy solutions3Enhancing lithium-ion battery analysis: A machine learning approach to investigate innovative silicon thin film anode parameters and discharge capacity2Intelligent Thermal and Power Behavior Prediction in Laptop Systems using Machine Learning0Condition-invariant frequency selection and Transformer-Graph autoregressive reconstruction for full-spectrum electrochemical impedance of lithium-ion batteries0Transfer learning for state-of-health prognostics of lithium-ion batteries: A survey4Review: next-generation metal hydride systems for sustainable hydrogen storage—kinetics, nanostructuring, and intelligent materials discovery4Toward data-driven lithium metal batteries: Machine learning for materials design, mechanistic insight, and autonomous optimization0A review on thermal runaway warning technologies for aviation lithium-ion batteries: Progress, challenges, and prospects3Smart AI based Degradation Converter Control for EV Charging Battery0Hybrid simulation–learning model for predicting degradation in lead–carbon batteries0The future of sustainable lithium-ion batteries: Ecodesign recommendations for solid-state technologies1Reinforcement Learning for Cathode Material Design Through Sequential Decision-Making Frameworks0A battery life prediction method based on graph neural network assisted by deep reinforcement learning0Chemistry-transferable physics-informed neural network surrogate for lithium-ion cells with online continual learning0Artificial intelligence driven lithium-ion battery recycling: from materials recovery to intelligent circular energy systems0A comprehensive review of data-driven electrochemical impedance spectroscopy (EIS) approaches for Li-ion battery SoH and RUL estimations0A Comprehensive Review of Artificial Intelligence-Driven Battery Management and Emerging Battery Technologies for Electric Vehicles0

Arrows point to the paper being cited. Selecting a paper shows its incoming citations and its known path back to the original paper.

Drag to pan · Use + / − to zoom · Escape to close43 nodes / 53 citation links
Browse Matching Papers

Papers that cite this work

55 direct citing papers saved. Showing the first 50 here; use Browse Matching Papers in the map for all loaded papers.

  1. Leveraging Boosting Algorithms for Accurate Battery Life Prediction in Autonomous Robots

    Unknown journal · 2024-11-20

    Vaishnavi V Rao, Kapil G. Ratan, Maitri Bewoor, Rashmi Benni

    Read original paper ↗ ·

  2. Next-Gen Electric Vehicle Battery Optimization: Enhancing RUL Prediction with Regression-Based Algorithms

    Unknown journal · 2024-11-20

    Aditya Purohit, Abhirama R Adiga, E Tierney Jessica, Rashmi Benni

    Read original paper ↗ ·

  3. Advancements and Challenges in Lithium-Ion Battery Lifecycle Management Toward a Sustainable Circular Economy for Electric Vehicles

    IEEE Open Journal of Power Electronics · 2025-01-01

    Sureshkumar Alagarsamy, Pradeep Vishnuram, Yuvaraja Shanmugam, T. M. Thamizh Thentral, Radomír Goňo, Miroslava Goňo, Rajamanickam Narayanamoorthi

    Read original paper ↗ ·

  4. Capacity Correction Enhances Battery Health Diagnosis Accuracy in Data Loss Scenarios for New Energy Vehicles

    SSRN Electronic Journal · 2025-01-01

    Yonghuan Ren, Liang Su, Guangji Song, Weijia Sun

    Read original paper ↗ ·

  5. A Brief Overview of Modeling Estimation of State of Health for an Electric Vehicle’s Li-Ion Batteries

    World Electric Vehicle Journal · 2025-02-01

    Ehab H.E. Bayoumi, Michele De Santis, Hilmy El-sayed Awad

    Read original paper ↗ ·

  6. Comparative Analysis of LSTM and Bayesian Neural Networks for Lithium-Ion Battery Capacity Degradation Prediction

    International Renewable Energy Congress · 2025-02-02

    Banawaz Marwa, Hanen Berriri, Med Faouzi Mimouni

    Read original paper ↗ ·

  7. Carbonaceous Materials as Anodes for Lithium-Ion and Sodium-Ion Batteries

    Batteries · 2025-03-25

    Koorosh Nikgoftar, Anil Kumar Madikere Raghunatha Reddy, M. V. Reddy, Karim Zaghib

    Read original paper ↗ ·

  8. Utilizing Machine Learning to Predict the Charge Storage Capability of Lithium-Ion Battery Materials

    Eurasian Chemico-Technological Journal · 2025-04-10

    Manoj Chhetri, Karen S. Martirosyan

    Read original paper ↗ ·

  9. Accelerating Battery Thermal Analysis by Integrating CFD Simulation and Machine Learning Techniques

    SAE technical papers on CD-ROM/SAE technical paper series · 2025-04-17

    G. V. Devarajan, Ganesh Vaidyanathan, Ajinkya Y. Bhave, Ji Liang, Jiao Wang, Wei Zhou, Jijun He, Pengfei Shi

    Read original paper ↗ ·

  10. A critical review on lithium ion battery modeling, battery management system and thermal runaway issues

    Electrical Engineering · 2025-05-02

    K. Dhananjay Rao, K. Dhananjay Rao, Kuna Dhanunjaya Rao, Kuna Dhanunjaya Rao, P. Pavani, Kapu V. Sri Ram Prasad, Indira Damarla, B. Phaniteja

    Read original paper ↗ ·

  11. Real Time Capacity Estimation For Lithium-Ion Battery Using Deep Transfer Learning

    Unknown journal · 2025-05-11

    Sk Bittu, Sukanta Halder, Nilanjan Das, Malay Jana

    Read original paper ↗ ·

  12. Fault Detection for Power Batteries Using a Generative Adversarial Network with a Convolutional Long Short-Term Memory (GAN-CNN-LSTM) Hybrid Model

    Applied Sciences · 2025-05-22

    Shaofan Liu, Tianbao Xie, Yanxin Li, Siyu Liu

    Read original paper ↗ ·

  13. MoExSOC: A Mixture of Experts Approach for Enhanced Battery State of Charge Estimation

    IEEE World AI IoT Congress (AIIoT) · 2025-05-28

    Itamar P. Ryan, Kundan Nepal

    Read original paper ↗ ·

  14. Machine learning approach to the possible synergy between co-doped elements in the case of LiFePO4/C

    Journal of Alloys and Compounds · 2025-06-01

    Z. M. S. Elbarbary, Priya A. Hoskeri, Ali Asghar Javidparvar, Mohammed M. Alammar, Amuthakkannan Rajakannu, Theodore Azemtsop Manfo

    Read original paper ↗ ·

  15. State‐of‐the‐Art Machine Learning Technology for Sustainable Lithium Battery Cathode Design: A Perspective

    Advanced Energy Materials · 2025-06-16

    Adil Saleem, Leon L. Shaw, Zhiqian Chen, Wei Lai

    Read original paper ↗ ·

  16. Quantum Chemistry-Guided Machine Learning for Accelerated Design of CO 2 -Solubilizing Deep Eutectic Solvents

    ACS Sustainable Chemistry & Engineering · 2025-06-17

    Dingkai Hu, Dezhi Cao, Shijian Lu, Qiang Wang, Bohak Yoon

    Read original paper ↗ ·

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

    Future Batteries · 2025-06-23

    Nayan Kumar, Prabhansu

    Read original paper ↗ ·

  18. A Concise Overview of the Use of Low-Dimensional Molybdenum Disulfide as an Electrode Material for Li-Ion Batteries and Beyond

    Batteries · 2025-07-16

    Mattia Bartoli, Meltem Babayiğit Cinali, Özlem Duyar Coşkun, Silvia Porporato, Diego Pugliese, Erik Piatti, Francesco Geobaldo, Giuseppe Antonio Elia, Claudio Gerbaldi, Giuseppina Meligrana, Alessandro Piovano

    Read original paper ↗ ·

  19. Capacity correction enhances battery health diagnosis accuracy in data loss scenarios for new energy vehicles

    Journal of Power Sources · 2025-08-01

    Yonghuan Ren, Liang Su, Guangji Song, Weijia Sun

    Read original paper ↗ ·

  20. Artificial Intelligence and Digital Twin Technologies for Intelligent Lithium-Ion Battery Management Systems: A Comprehensive Review of State Estimation, Lifecycle Optimization, and Cloud-Edge Integration

    Batteries · 2025-08-05

    Seyed Saeed Madani, Yasmin Shabeer, Michael William Fowler, Satyam Panchal, Hicham Chaoui, Saad Mekhilef, Shi Xue Dou, Khay Wai See

    Read original paper ↗ ·

  21. Machine Learning-Based State of Charge Prediction for 21700 Lithium-Ion Batteries: A Comparative Study

    Unknown journal · 2025-08-26

    Auzan Izzaturrahman, Bandiyah Sri Aprillia, Marsha Clarabell

    Read original paper ↗ ·

  22. AI Applications in Predictive Maintenance and Reliability of Batteries: Challenges and Future Directions

    International Conference on Future Energy Solutions (FES) · 2025-09-24

    Ioana Cristina Sechel, Aron Csato, Florin Emil Mariasiu

    Read original paper ↗ ·

  23. Interface engineering and safety in solid-state batteries: Advancing from human-centered insights to AI-driven innovations

    Advances in Colloid and Interface Science · 2025-10-10

    Elnaz Karimi, Stefan Iglauer, Muhammad Rizwan Azhar

    Read original paper ↗ ·

  24. Reinforcement learning for adaptive fault detection in lithium-ion batteries: a next-generation approach for electric vehicles

    Engineering Research Express · 2025-10-23

    Hethu Avinash Dasari, A Rammohan

    Read original paper ↗ ·

  25. Machine Learning Techniques for Battery State of Health Prediction: A Comparative Review

    World Electric Vehicle Journal · 2025-10-28

    Leila Mbagaya, Kumeshan Reddy, Annelize Botes

    Read original paper ↗ ·

  26. AI-driven next-generation lithium-ion battery design automation (BDA) software

    National Science Open · 2025-11-01

    Zekai Liu, Genming Lai, Yunxing Zuo, Xiaohe Song, Qinghua Liu, Fan Zhang, Ziyi Wang, Qi Ji, Jiaxin Zheng, Jiadong Gong, Bo Xu, Chuying Ouyang

    Read original paper ↗ ·

  27. Battery management in electric aviation: A bibliometric review of technologies, regulations, and international collaborations

    Journal of Energy Storage · 2025-11-25

    Abdeen Osman, Aghyad B. Al Tahhan, Tariq M. Younes, Mohamad Ramadan, Mohammed Asaad Ghazal, Mohammad A. AlKhedher

    Read original paper ↗ ·

  28. Data‐Driven Electrolyte Design for Advanced Rechargeable Lithium Batteries †

    Chinese Journal of Chemistry · 2025-11-27

    Jiaojiao Deng, Xiaozhen Chen, Yu Bai, Jinhan Mo, Xiaoliang Yu

    Read original paper ↗ ·

  29. Data-Driven Performance Prediction of Lead–Carbon Batteries: Integrating Experimental Validation and Reduced-Order Model-Guided Neural Networks

    Korean Journal of Chemical Engineering · 2025-12-09

    Aleksey Ni, Ahmad Syauqi, Pham Tan Thong, Hosanna Uwitonze, Heehyang Kim, Vijay Mohan Nagulapati, Inkyung Song, Ho‐Young Jung, Hankwon Lim

    Read original paper ↗ ·

  30. Prediction of the Remaining Useful Life of Lithium-Ion Batteries Based on the Optimized TTAO-VMD-BiLSTM

    Batteries · 2025-12-26

    Pengcheng Wang, Lu Liu, Qun Yu, Dongdong Hou, Enjie Li, Haijun Yu, Shumin Liu, Lizhen Qin, Yunhai Zhu

    Read original paper ↗ ·

  31. Hybrid approach to battery management: Application of optimization and machine learning for sustainable energy solutions

    AIP conference proceedings · 2026-01-01

    Hari Prasadarao Pydi, Balaji Vasudevan, Duraisamy Premkumar, Giddi Venkateswara Rao, Piramanayagam Sethu Ramalingam, Jyoti Moni Devi

    Read original paper ↗ ·

  32. NeuralProphet-Based Forecasting of State of Health (SOH) and Remaining Useful Life (RUL) in Lithium-ion Batteries

    Lecture notes in mechanical engineering · 2026-01-01

    Patrick Dale G. Cuartero, Catherine R. Alimboyong

    Read original paper ↗ ·

  33. Unlocking a shortcut: acceleration of non-aqueous electrolyte development by active machine learning for sodium-based batteries

    Digital Discovery · 2026-01-01

    Mirko Fischer, Robert Tobias Hinz, Christian Wölke, Isidora Cekić-Lasković, Martin Winter, Andreas Heuer

    Read original paper ↗ ·

  34. Machine learning-based battery life prediction and smart charging optimization for renewable energy storage systems

    Future Batteries · 2026-01-13

    Subhash Kumar Mandal, Pankaj Pateriya, Yogendra Singh Dohare

    Read original paper ↗ ·

  35. Theoretical modeling and performance prediction of magic-angle twisted bilayer graphene Sodium-Ion batteries: a multi-scale computational framework

    Applied Surface Science · 2026-01-18

    Qinyou Yang, Niwei Zhu, Xinran Wang, Yumo Cai

    Read original paper ↗ ·

  36. Integration of Electro-Thermal Modelling and Temporal Deep Learning for Reliable State-of-Charge Estimation

    Unknown journal · 2026-01-21

    M. Rama Prasad Reddy, Nagaladinne Mohammed Ghouse, Varda Mahesh Babu, Kondeti Shiva

    Read original paper ↗ ·

  37. Explainable Datadriven Digital Twins for Predicting Battery States in Electric Vehicles Using Deep Learning Models

    International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT) · 2026-02-04

    P. Phanindra Kumar Reddy, Davanam Ganesh, N. Poojitha, P. Shathvika Vishal, S Kaliprasad Karthik, Shaik Afreen

    Read original paper ↗ ·

  38. A Review of Smart Lithium-Ion Battery Manufacturing: AI-enabled Decision and Control Approaches

    International Conference on Intelligent Control and Information Processing · 2026-02-21

    Feng Ding, Xiaoshu Zhu, Chuqi Wu, Jun Li, Qifeng He

    Read original paper ↗ ·

  39. Roadmaps for dendrite suppression in next generation lithium-ion batteries: Toward sustainable energy solutions

    Energy storage materials · 2026-02-23

    Yi Li, Sachin Poudel, Kumari Sweta, Erfan Azqadan, Anil Kunwar, Nele Moelans B

    Read original paper ↗ ·

  40. Enhancing lithium-ion battery analysis: A machine learning approach to investigate innovative silicon thin film anode parameters and discharge capacity

    Journal of Power Sources · 2026-03-07

    Elif Muslu, Ayşegül Uygun Öksüz, Satoshi Hamaguchi, Elif Ceren Gok Yildirim, Murat Onur Yildirim, Kazumasa Ikuse, Pierre Vinchon, Nicolas Aini Mauchamp, Esin Eren

    Read original paper ↗ ·

  41. Intelligent Thermal and Power Behavior Prediction in Laptop Systems using Machine Learning

    Unknown journal · 2026-04-13

    Manisha Rajesh Mhetre, Tejas R. Kulkarni, Anuj A. Khomane, Samadhan S. Kendre, Aditya V. Kulsange, Soham S. Vaidya

    Read original paper ↗ ·

  42. Condition-invariant frequency selection and Transformer-Graph autoregressive reconstruction for full-spectrum electrochemical impedance of lithium-ion batteries

    Journal of Energy Storage · 2026-04-16

    Honghao Liang, Syed Abbas Ali Shah, Mahrukh, Ziqiang Xu, Mengqiang Wu

    Read original paper ↗ ·

  43. Transfer learning for state-of-health prognostics of lithium-ion batteries: A survey

    Journal of Energy Storage · 2026-04-16

    Jingchen Wang, Jinye Lu, Yongliang Liu, Li Li, Kai Wang

    Read original paper ↗ ·

  44. Review: next-generation metal hydride systems for sustainable hydrogen storage—kinetics, nanostructuring, and intelligent materials discovery

    Journal of Materials Science · 2026-05-13

    Ashutosh Das, Arka Ghosh, Bansod Sneha Bharat, Nityananda Sahoo, Uddeshya Shukla, Parth Patel, Kalyani Tiwari, S.S.K. Deepak, Bappa Das, Pankaj Shrivastava, Velaphi Msomi

    Read original paper ↗ ·

  45. Toward data-driven lithium metal batteries: Machine learning for materials design, mechanistic insight, and autonomous optimization

    Energy storage materials · 2026-05-24

    Yu Lou, Hongyang Zhao, J Li, Wenxuan Xu, Chaocang Weng, J Li, Likun Pan

    Read original paper ↗ ·

  46. A review on thermal runaway warning technologies for aviation lithium-ion batteries: Progress, challenges, and prospects

    Renewable and Sustainable Energy Reviews · 2026-06-05

    Shaonan Liu, 吕松 Lü Song, J Huang, Junchao Zhao, Heping Zhang

    Read original paper ↗ ·

  47. Smart AI based Degradation Converter Control for EV Charging Battery

    International Conference on Inventive Computing and Informatics (ICICI) · 2026-06-10

    M.P. Mohandass, R. Kanish, A.Dinesh, S. Joyal Goodwin

    Read original paper ↗ ·

  48. Hybrid simulation–learning model for predicting degradation in lead–carbon batteries

    Journal of Energy Storage · 2026-06-11

    Aleksey Ni, Pham Tan Thong, Hosanna Uwitonze, Heehyang Kim, Inkyung Song, Ho-Young Jung, Hankwon Lim

    Read original paper ↗ ·

  49. The future of sustainable lithium-ion batteries: Ecodesign recommendations for solid-state technologies

    Energy storage materials · 2026-06-19

    Joana R. Gouveia, Inês Ribeiro, Luís Oliveira, Emanuel Lourenço, Belmira Neto

    Read original paper ↗ ·

  50. Reinforcement Learning for Cathode Material Design Through Sequential Decision-Making Frameworks

    Nanomaterials · 2026-08-10

    Taimoor Muzaffar Gondal, Muhammad Qasim, Yasir Arafat

    Read original paper ↗ ·
More citing papers →
Citation Atlas · A map of research, not a ranking.