عنوان
پدید آورنده
موضوع
رده
کتابخانه
محل استقرار
TLpq2446477230
انگلیسی
A Complete Machine Learning Approach for Predicting Lithium-Ion Cell Combustion
[Thesis]
Almagro Yravedra, Fernando
Li, Zuyi
Illinois Institute of Technology
2020
139
M.S.
Illinois Institute of Technology
2020
The object of the herein thesis work document is to develop a functional predictive model, able to predict the combustion of a US18650 Sony Lithium-Ion cell given its current and previous states. In order to build the model, a realistic electro-thermal model of the cell under study is developed in Matlab Simulink, being used to recreate the cell's behavior under a set of real operating conditions. The data generated by the electro-thermal model is used to train a recurrent neural network, which returns the chance of future combustion of the US18650 Sony Lithium-Ion cell. Independently obtained data is used to test and validate the developed recurrent neural network using advanced metrics.
Artificial intelligence
Electrical engineering
Almagro Yravedra, Fernando
Li, Zuyi
مطالعه متن کتاب p
[Thesis]
276903
a
Y
