Sampled-Data Observer for Estimating the State of Charge, State of Health, and Temperature of Batteries

Changes in Electrolyte Transmittance at 254 Nm According to the State of Health of Lead Acid Batteries

“…The internal resistance of the battery does not belong to the external parameters of the battery, strictly speaking, the internal resistance is one of the inherent characteristics of the battery. Most battery management systems take internal resistance parameters as auxiliary parameters for battery condition estimation both to determine the state of charge (SoC) as well as SOH (Wang et al, 2020;Gaouzi et al, 2021). Another method is the counting of charge cycles, which is widely employed in the calculation of SOH of laptop batteries, there are also destructive methods in which the battery is uncovered to internally analyse the state by techniques such as Raman spectroscopy, Xray diffraction, electron microscopy in which changes in the internal structure are looked at Xiong research (Xiong et al, 2018).…”

Novel co‐estimation strategy based on forgetting factor dual particle filter algorithm for the state of charge and state of health of the lithium‐ion battery

“…32 At present, there are mainly three kinds of methods for the SOH estimation of Li-ion batteries: experimental evaluation method, adaptive filtering method, and data-driven method. 33 The experimental evaluation method is generally taken advantage of to directly measure the characteristic parameters closely related to SOH of the battery, 34 such as current, OCV, temperature, and AC impedance, by offline method, 35 and the degree of battery aging is directly or indirectly evaluated by combining with the corresponding mechanism model. 36 Zhou et al 37 propose an SOH prediction model that evaluates the prediction uncertainty using data from different batches of batteries under actual working conditions.…”

Improved Particle Swarm Optimization-Extreme Learning Machine Modeling Strategies for the Accurate Lithium-ion Battery State of Health Estimation and High-adaptability Remaining Useful Life Prediction

“…15 The hardship of SOH estimation by the internal resistance approach is to extract the mapping relationship between SOH and internal resistance, in particular by considering SOC, temperature and multiplicity. 16 Furthermore, the extracted characteristic relationship is only available for a certain brand and model of battery and is by no means very widespread. 17 Electrochemical impedance spectrum (EIS) analysis is to evaluate the impedance spectrum at different phases of battery aging first, then connect the EIS curve with the equivalent circuit model parameters of the battery, and then locate the SOH on the basis of the relationship between the model parameters and SOH.…”