Evaluating the heat generation characteristics of cylindrical lithium-ion battery considering the discharge rates and N/P ratio

Wu, Longxing; Li, Kai; Pang, Hui

doi:10.1016/j.est.2023.107182

Cited by 34 publications

(14 citation statements)

References 58 publications

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“…Notably, due to their smaller mass and higher mechanical resonance frequencies, the single-layer and two-layer FENGs do not exhibit this resonance peak. The difference in resonance behavior among these FENG configurations highlights the importance of understanding their mechanical properties and how they can affect the device’s output in different frequency ranges. , …”

Section: Parameters Of Interest and Measurementsmentioning

confidence: 99%

Recent Advances in Flexible Nanogenerators for Microphone and Loudspeaker Applications

Yang,

Zhang,

Wang

et al. 2023

ACS Appl. Electron. Mater.

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Nowadays, ferroelectret nanogenerators have been proposed as a possible alternative method for kinetic energy collection. We describe the component’s inherent features, which enable the bidirectional transfer of energy between the electrical and mechanical fields, expanding its potential application in wearable electronics beyond power production. Such electromechanical linkage gives the device dual-functional transducing features, demonstrating its application as a small, portable, and self-powered loudspeaker or microphone patch. This coupling, together with the flexibility and thin-film-like shape, gives the device these characteristics. For three alternative configurations, the sound pressure level is assessed in the spatial and frequency domains to ascertain the device’s functionality and usability. Also, dependencies of sound pressure levels (SPLs) generated by a FENG due to an AC voltage stimulus, surface area, geometric shape, and addition of layers are presented here.

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Section: Parameters Of Interest and Measurementsmentioning

confidence: 99%

Recent Advances in Flexible Nanogenerators for Microphone and Loudspeaker Applications

Yang,

Zhang,

Wang

et al. 2023

ACS Appl. Electron. Mater.

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show abstract

“…General Steps. Generally speaking, ML can be divided into four steps, namely, analyzing and defining problems, data preprocessing, model (algorithm) selection, model training, evaluation and optimization, and model deployment and application, 15 as shown in Figure 5.…”

Section: Machine Learningmentioning

confidence: 99%

Triboelectric Nanogenerator Assisted by Machine Learning

Yang,

Shang,

et al. 2023

ACS Appl. Electron. Mater.

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“…Then, K-type thermocouple was attached to the battery surface, and temperature readings were captured using the data gathering equipment. The battery test system (ITS 5300) was also activated at the same time to record the terminal voltage during the discharge process, with the sample time set to 1 s. The detailed descriptions about the voltage and temperature acquisition are as follows: 31 (1) Apply the standard charging protocol constant current (1 C)constant voltage (3.6 V) to charge the battery fully, i.e., SOC = 100%. (2) Set a thermal-controlled chamber temperature, and let it stand for 30 min to make the surface and internal temperature of the battery completely consistent with the ambient temperature.…”

Section: Battery Model Parameter Identification With Experimental Datamentioning

confidence: 99%

Thermal-Coupled Single Particle Modeling and Multi-Objective Stepwise Parameter Identification of Lithium-Ion Batteries Over Different Temperatures

Liu

Pang

Geng

et al. 2023

J. Electrochem. Soc.

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The establishment of an electrochemical-thermal coupling model for a lithium-ion battery (LIB) is an important issue in developing an appropriate thermal management system of LIB packs. In this paper, a novel thermal-coupled single particle model with few parameters is first developed to promote battery parameter identification at various temperatures. Then, after collecting the experimental profiles of battery voltage, current, and temperature, a multi-objective stepwise identification scheme based on genetic algorithm is proposed to identify the classified parameters of LIB at different temperatures. Finally, the proposed battery model and the stepwise parameter identification are validated in terms of the simulations and experiments. The results demonstrate that this proposed battery model and parameter identification method can not only describe inherent electrochemical and thermal characteristics of the battery, but also identify the battery electrochemical states with high precision, which provides a strong foundation for the development and implementation of battery thermal management system.

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Evaluating the heat generation characteristics of cylindrical lithium-ion battery considering the discharge rates and N/P ratio

Cited by 34 publications

References 58 publications

Recent Advances in Flexible Nanogenerators for Microphone and Loudspeaker Applications

Recent Advances in Flexible Nanogenerators for Microphone and Loudspeaker Applications

Triboelectric Nanogenerator Assisted by Machine Learning

Thermal-Coupled Single Particle Modeling and Multi-Objective Stepwise Parameter Identification of Lithium-Ion Batteries Over Different Temperatures

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