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Zhihao Yu, Tianle Cui, Shibo Jia, Ruituo Huai
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Fast and highly accurate measurement of electrochemical impedance spectra of power batteries based on optimized multi-sine signals
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Fast characterization of lithium-ion battery impedance and nonlinearity using optimized multisine perturbation signal
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Accelerated and broadband electrochemical impedance spectroscopy of lithium-ion batteries using segmented chirp signals
10.1016/j.ces.2026.123440 · doi-reference
Binary multi-frequency signal for accurate and rapid electrochemical impedance spectroscopy acquisition in lithium-ion batteries
10.1016/j.apenergy.2024.123221 · doi-reference
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10.1016/j.geits.2024.100207 · doi-reference
Improved lumped electrical characteristic modeling and adaptive forgetting factor recursive least squares-linearized particle swarm optimization full-parameter identification strategy for lithium-ion batteries considering the hysteresis component effect
10.1016/j.est.2023.107597 · doi-reference
Parameter identification method for lithium-ion batteries based on recursive least square with sliding window difference forgetting factor
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CPSO-based parameter identification method for the fractional-order modeling of lithium-ion batteries
10.1109/tpel.2021.3073810 · doi-reference
Online estimation of lithium-ion battery equivalent circuit model parameters using decoupled recursive least squares with adaptive moving window forgetting factor
10.1109/tia.2025.3588810 · doi-reference
Research on rapid extraction of internal resistance of lithium battery based on short-time transient response
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A hybrid pulse power characterization-elastic net framework for accurate state-of-health estimation in lithium-ion batteries under thermal aging conditions
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An SMPS-based lithium-ion battery test system for internal resistance measurement
10.1109/tte.2022.3178981 · doi-reference
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Parameter identification method for the variable order fractional-order equivalent model of lithium-ion battery
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Enhanced equivalent circuit model for high current discharge of lithium-ion batteries with application to electric vertical takeoff and landing aircraft
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Early safety warning method for lithium-ion batteries under mechanical abuse conditions based on online electrochemical parameter identification
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Online estimation of model parameters and state of charge for lithium-ion battery using multitimescale recurrent neural networks
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An adaptive hybrid approach for online battery state of charge estimation
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Improved online parameter identification coupled with discrete wavelet transform for state-of-charge estimation under noise-riding discharging/charging battery voltage
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Improved back-propagation neural network-multi-information gain optimization Kalman filter method for high-precision estimation of state-of-energy in lithium-ion batteries
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Online model-based lithium-ion battery state-of-charge estimation using RLS with adaptive three forgetting schemes
10.1109/tte.2025.3635195 · doi-reference
Model parameter identification for lithium batteries using the coevolutionary particle swarm optimization method
10.1109/tie.2017.2677319 · doi-reference
Multi-objective optimization of lithium-ion battery model using genetic algorithm approach
10.1016/j.jpowsour.2014.07.110 · doi-reference
A novel co-estimation framework of state-of-charge, state-of-power and capacity for lithium-ion batteries using multi-parameters fusion method
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A dual-objective data-driven framework combining Bayesian optimization and improved differential evolution for rapid and accurate parameter identification of lithium-ion battery P2D models
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Parameter sensitivity analysis of a multi-physics coupling aging model of lithium-ion batteries
10.1016/j.electacta.2024.143811 · doi-reference
Quantum-inspired grey wolf optimizer for rapid lithium-ion battery parameter identification in electric vehicles
10.1016/j.est.2025.118425 · doi-reference
An improved particle swarm optimization-adaptive square root Unscented Kalman filter algorithm for accurate state of charge estimation of lithium-ion batteries
10.1016/j.energy.2026.140316 · doi-reference
Physics-based parameter identification of an electrochemical model for lithium-ion batteries with two-population optimization method
10.1016/j.apenergy.2024.124748 · doi-reference
Fast parameter identification of lithium-ion batteries via classification model-assisted Bayesian optimization
10.1016/j.energy.2023.129667 · doi-reference
An improved state of energy estimation method for energy storage lithium batteries with strong temperature and noise robustness
10.1016/j.electacta.2026.149058 · doi-reference
Critical review on adaptive modeling and parameter identification for state of power estimation in lithium-ion batteries
10.1016/j.jpowsour.2025.238937 · doi-reference