Battery State Estimation

May 1, 2019
SoC PDF SoC Code SoC DOI RUL PDF RUL Code RUL DOI
RUL estimation results on testing data

Using deep LSTMs and Autoencoders to estimate the State of Charge and the Remaining Useful Life of batteries.

Deep Learning LSTM Autoencoder Time Series Batteries
Michael Bosello
Michael Bosello
Senior Researcher, Ph.D. Student

Publications

To Charge or to Sell? EV Pack Useful Life Estimation via LSTMs, CNNs, and Autoencoders
Energies
Michael Bosello, Carlo Falcomer, Claudio Rossi, Giovanni Pau
PDF Cite Code Project DOI
To Charge or to Sell? EV Pack Useful Life Estimation via LSTMs, CNNs, and Autoencoders
Li-Ion Batteries State-of-Charge Estimation Using Deep LSTM at Various Battery Specifications and Discharge Cycles
ACM, Conference on Information Technology for Social Good (GoodIT 2021)
Kei Long Wong, Michael Bosello, Rita Tse, Carlo Falcomer, Claudio Rossi, Giovanni Pau
PDF Cite Code Dataset Project Slides DOI
Li-Ion Batteries State-of-Charge Estimation Using Deep LSTM at Various Battery Specifications and Discharge Cycles