State of health (SOH) prediction for Lithium-ion batteries using regression and LSTM
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Updated
Jul 25, 2022 - Jupyter Notebook
State of health (SOH) prediction for Lithium-ion batteries using regression and LSTM
A comprehensive simulation platform integrating vehicle dynamics, environment emulation, body controls, and battery management for holistic testing and validation of automated vehicles.
Repository of my master’s thesis "Development and evaluation of a model for predicting the state of health of traction batteries based on artificial neural networks"
Sunwoda Electronic Co., Ltd, and Tsinghua Berkeley Shenzhen Institute (TBSI) generate the TBSI Sunwoda Battery Dataset. We open-source this dataset to inspire more data-driven novel material verification, battery management research and applications.
translation for paper Machine learning pipeline for battery state-of-health estimation
Master Thesis in Data Science and Engineering
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