仅表示这篇论文与本数据集在文献网络中相邻, 不代表该论文确实使用了本数据集。

• Feature Extraction for Lithium-Ion Battery State of Health Estimation: Methods and Applications 2026 · 综述收录
• Estimation of SoC, SoH, and RUL in battery management systems using artificial intelligence: A tertiary mapping study 2026 · 综述收录
• Artificial intelligence for estimating State of Health and Remaining Useful Life of EV batteries: A systematic review 2025 · 综述收录
• A comprehensive review of lithium-ion battery remaining useful life prediction: methodologies, datasets, performance metrics, and future perspectives 2025 · 综述收录
• An Overview of Remaining Useful Life Prediction of Battery Using Deep Learning and Ensemble Learning Algorithms on Data‐Dependent Models 2025 · 综述收录
• Predictive Modeling for Electric Vehicle Battery State of Health: A Comprehensive Literature Review 2025 · 综述收录
• A Brief Overview of Modeling Estimation of State of Health for an Electric Vehicle’s Li-Ion Batteries 2025 · 综述收录
• Overview and Analysis of Publicly Available Degradation Data Sets for Tasks within Prognostics and Health Management 2025 · 综述收录
• Next-Generation Battery Monitoring Using AI for Sustainable Electric Mobility 2025 · 综述收录
• Review on Lithium-ion Battery PHM from the Perspective of Key PHM Steps 2024 · 综述收录
• Lithium-ion battery data and where to find it 2021 · 综述收录
• A Comprehensive Review of Available Battery Datasets, RUL Prediction Approaches, and Advanced Battery Management 2021 · 综述收录
• A Bayesian optimized neural network model for lithium-ion battery state of charge estimation 2026 · 用于方法验证
• Health monitoring systems for EV battery 2026 · 使用该数据集
• Hybrid State-of-Charge Estimation Method for Lithium-Ion Batteries Considering Uncertainty Quantification and Innovation Adaptation 2026 · 用于方法验证
• A Lithium-Ion Battery SOH Estimation Method via Integrating Mechanism Priors with Data-Driven Graph Structure Learning 2026 · 用于方法验证
• PL-LSTM-Based State of Health Estimation and TTE Prediction for Lithium-Ion Batteries 2026 · 使用该数据集
• An Adaptive-Weight Physics-Informed Neural Network Optimized by Grey Wolf Optimizer for Lithium-Ion Battery State of Health Estimation 2026 · 用于方法验证
• Continuous ageing trajectory representations for knee-aware lifetime prediction of lithium-ion batteries across heterogeneous dataset 2026 · 用于方法验证
• Dynamic Coherence–Based Battery Health Assessment via Longitudinal Trajectory Analysis 2026 · 使用该数据集

仅列前 20 篇(首发/综述优先,按年份倒序);全量见 API。