Dataset Information

Battery health evaluation using a short random segment of constant current charging.

ABSTRACT: Accurately evaluating the health status of lithium-ion batteries (LIBs) is significant to enhance the safety, efficiency, and economy of LIBs deployment. However, the complex degradation processes inside the battery make it a thorny challenge. Data-driven methods are widely used to resolve the problem without exploring the complex aging mechanisms; however, random and incomplete charging-discharging processes in actual applications make the existing methods fail to work. Here, we develop three data-driven methods to estimate battery state of health (SOH) using a short random charging segment (RCS). Four types of commercial LIBs (75 cells), cycled under different temperatures and discharging rates, are employed to validate the methods. Trained on a nominal cycling condition, our models can achieve high-precision SOH estimation under other different conditions. We prove that an RCS with a 10mV voltage window can obtain an average error of less than 5%, and the error plunges as the voltage window increases.

SUBMITTER: Deng Z

PROVIDER: S-EPMC9062330 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature

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Battery health evaluation using a short random segment of constant current charging.

Deng Zhongwei Z Hu Xiaosong X Xie Yi Y Xu Le L Li Penghua P Lin Xianke X Bian Xiaolei X

iScience 20220412 5

Accurately evaluating the health status of lithium-ion batteries (LIBs) is significant to enhance the safety, efficiency, and economy of LIBs deployment. However, the complex degradation processes inside the battery make it a thorny challenge. Data-driven methods are widely used to resolve the problem without exploring the complex aging mechanisms; however, random and incomplete charging-discharging processes in actual applications make the existing methods fail to work. Here, we develop three d ...[more]

PMID: 35521525

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Project description:BACKGROUND:The sweat test (ST) is the gold standard for the diagnosis of cystic fibrosis (CF). However, little is known about sweat induction using different types of currents and waves. In this context, our objective was to develop a device to induce sweat and compare the use of continuous constant current (CCC) and continuous pulsed current (CPC) in individuals with CF and healthy controls. METHODS:A prospective cross-sectional study with experimental intervention. The variables of gender, ethnicity, age, and body mass index (BMI) were considered. The method of Gibson and Cooke was used, and the following markers were evaluated: sweat weight, electrical impedance, sufficient sweat amount, and CF diagnosis. Triangular (TPC) or sinusoidal (SPC) pulsed current was applied to the right arm, and CCC was applied to the left arm. RESULTS:The study analyzed 260 individuals, 141/213 (54.2%) were female participants, 135/260 (51.9%) were Caucasians. The distribution of individuals by concentration of chloride at the ST was: (CF) 26/260 (10%); (borderlines) 109/260 (41.9%); (healthy) 97/260 (37.3%); (insufficient weight in sweat) 28/260 (10.8%). No association was observed between the sufficient sweat amount to perform the ST when we compared the currents. However, the SPC showed a higher amount of sweat weight. Using Bland and Altman plot considering the agreement between the sweat chloride values achieved from CPC [SPC and TPC] and CCC, there was no proportional bias and mean values are unrelated and only explain less than 8% of the variation. Moreover, TPC presented higher electrical impedance when compared with SPC and CCC. SPC presented lower electrical impedance and higher sweat weight than CCC. Male participants presented lower electrical impedance and higher sweat weight with CCC and TPC, and higher sweat weight with SPC. CONCLUSIONS:The evaluated currents are safe and able to induce and produce sweat in sufficient quantities for the ST. SPC presented lower electrical impedance when compared with other currents. The use of SPC is recommended to induce sweat in patients with sweat problems. Finally, ethnicity, gender, age and BMI did not influence sweat induction at the ST, and no side effect was observed in our study.

Dataset Information

Battery health evaluation using a short random segment of constant current charging.

Publications

Battery health evaluation using a short random segment of constant current charging.

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