State of health (SOH) prediction for Lithium-ion batteries using regression and LSTM
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Updated
Jun 30, 2024 - Jupyter Notebook
State of health (SOH) prediction for Lithium-ion batteries using regression and LSTM
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.
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"
translation for paper Machine learning pipeline for battery state-of-health estimation
Code and models for estimating the State of Charge (SoC) and of battery cells. Utilizing advanced deep learning techniques.
Master Thesis in Data Science and Engineering
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