Health-Aware Charging of Li-Ion Batteries Using MPC and Bayesian Degradation Models

Taranjitsingh Singh, Jeroen Willems, Bruno Depraetere, Erik Hostens

2025

Abstract

We propose a Model Predictive Control (MPC) approach for health-aware optimal charging of Lithium-ion Nickel Manganese Cobalt (Li-NMC) batteries. Our method integrates electrical, thermal, and degradation models using Bayesian Networks (BNs) to estimate the battery’s State of Health (SOH). These models are embedded into an MPC framework to generate charging profiles that reduce long-term degradation while ensuring fast charging performance. Validation is performed through high-fidelity simulations using the PyBaMM battery modeling environment. Results show improved SOH retention compared to conventional Constant Current-Constant Voltage (CC-CV) strategy.

Paper Citation

in Harvard Style

Singh T., Willems J., Depraetere B. and Hostens E. (2025). Health-Aware Charging of Li-Ion Batteries Using MPC and Bayesian Degradation Models. In Proceedings of the 22nd International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO; ISBN 978-989-758-770-2, SciTePress, pages 37-46. DOI: 10.5220/0013691400003982

in Bibtex Style

@conference{icinco25,
author={Taranjitsingh Singh and Jeroen Willems and Bruno Depraetere and Erik Hostens},
title={Health-Aware Charging of Li-Ion Batteries Using MPC and Bayesian Degradation Models},
booktitle={Proceedings of the 22nd International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO},
year={2025},
pages={37-46},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013691400003982},
isbn={978-989-758-770-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 22nd International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO
TI - Health-Aware Charging of Li-Ion Batteries Using MPC and Bayesian Degradation Models
SN - 978-989-758-770-2
AU - Singh T.
AU - Willems J.
AU - Depraetere B.
AU - Hostens E.
PY - 2025
SP - 37
EP - 46
DO - 10.5220/0013691400003982
PB - SciTePress