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Machine Learning Lithium-Ion Battery Capacity Estimation

version 1.0.1.2 (763 KB) by Wanbin Song
Machine learning based Lithium-Ion battery capacity estimation using multi-Channel charging Profiles

893 Downloads

Updated 07 Jan 2020

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In this script, I've implemented machine learning based Lithium-Ion battery capacity estimation using multi-Channel charging Profiles. Dataset used in this example is from "Battery data set" from NASA[1].
Basic implementation theory and approach is referenced by the recent published paper[2], and they proposed Multi-Channel charging profiles based machine learning and deep learning model for capacity estimation. Through this example, I will capture each approach described in paper.

[1] B. Saha and K. Goebel (2007). "Battery Data Set", NASA Ames Prognostics Data Repository (https://ti.arc.nasa.gov/tech/dash/groups/pcoe/prognostic-data-repository/#battery), NASA Ames Research Center, Moffett Field, CA
[2] Choi, Yohwan, et al. "Machine Learning-Based Lithium-Ion Battery Capacity Estimation Exploiting Multi-Channel Charging Profiles." IEEE Access 7 (2019): 75143-75152.

Cite As

Wanbin Song (2021). Machine Learning Lithium-Ion Battery Capacity Estimation (https://github.com/wanbin-song/BatteryMachineLearning), GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2019b
Compatible with R2019b and later releases
Platform Compatibility
Windows macOS Linux

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To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.