Data-driven state of charge estimation of lithium-ion batteries: Algorithms, implementation factors, limitations and future trends

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State of Charge and State of Energy Estimation for Lithium-Ion Batteries Based on a Long Short-Term Memory Neural Network

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Current Trends for State-of-Charge (SoC) Estimation in Lithium-Ion Battery Electric Vehicles

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Real-Time State of Charge Estimation of Lithium-Ion Batteries Using Optimized Random Forest Regression Algorithm

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Open access dataset, code library and benchmarking deep learning approaches for state-of-health estimation of lithium-ion batteries

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Powering the Future: A Comprehensive Review of Battery Energy Storage Systems

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Machine learning for optimised and clean Li-ion battery manufacturing: Revealing the dependency between electrode and cell characteristics

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A comparative study of different adaptive extended/unscented Kalman filters for lithium-ion battery state-of-charge estimation

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State estimation of lithium-ion batteries via physics-machine learning combined methods: A methodological review and future perspectives

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Data-driven method based on deep learning algorithm for detecting fat, oil, and grease (FOG) of sewer networks in urban commercial areas

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Artificial neural network driven prognosis and estimation of Lithium-Ion battery states: Current insights and future perspectives

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A novel data-driven IBA-ELM model for SOH/SOC estimation of lithium-ion batteries

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A comprehensive review of hybrid battery state of charge estimation: Exploring physics-aware AI-based approaches

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Attention-based encoder-decoder networks for state of charge estimation of lithium-ion battery

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A hybrid data-driven method for rapid prediction of lithium-ion battery capacity

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A Cell-to-Pack State Estimation Extension Method Based on a Multilayer Difference Model for Series-Connected Battery Packs

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A novel hybrid machine learning coulomb counting technique for state of charge estimation of lithium-ion batteries

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Empowering Electric Vehicles Batteries: A Comprehensive Look at the Application and Challenges of Second-Life Batteries

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Data-Driven Methods for the State of Charge Estimation of Lithium-Ion Batteries: An Overview

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Data-driven prognosis of failure detection and prediction of lithium-ion batteries

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Data-physics-driven estimation of battery state of charge and capacity

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A method for capacity prediction of lithium-ion batteries under small sample conditions

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Optimized EKF algorithm using TSO-BP neural network for lithium battery state of charge estimation

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A Bayesian optimized machine learning approach for accurate state of charge estimation of lithium ion batteries used for electric vehicle application

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