A Cicuit and Artificial Neural Network Mixed Battery Model for Test Normalization

Battery is the energy source of many power equipment, the quality and reliability of battery is directly related to the reliability of all kinds of equipment, so it needs to be tested reasonably. However, different enterprises or research institutions have different battery quality indicators and te...

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Bibliographic Details
Published in2021 IEEE 4th International Electrical and Energy Conference (CIEEC) pp. 1 - 6
Main Authors Ding, Li, Min, Huaidong, Wang, Ziyu, Tang, Dengping, Xia, Shuibin, Peng, Han, Chen, Yu
Format Conference Proceeding
LanguageEnglish
Published IEEE 28.05.2021
Subjects
Artificial Neural Network
Artificial neural networks
Batteries
battery model
data exchange
Data models
Electric potential
Resistance
US Department of Defense
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Summary:Battery is the energy source of many power equipment, the quality and reliability of battery is directly related to the reliability of all kinds of equipment, so it needs to be tested reasonably. However, different enterprises or research institutions have different battery quality indicators and testing methods, resulting in various test results cannot be compared and referenced. Eventually, the workload is increased and the waste of testing resources is wasted. In this paper, a battery model mixed with circuit and artificial neural network is proposed to realize data exchange and test data normalization.
DOI:10.1109/CIEEC50170.2021.9510491