In this paper, we propose a data-efficient online battery identification method which targets highly informative battery cell data segments based on the driving pattern of the vehicle. We consider the case of a vehicle driving on/off a motorway and construct an Extended Time Regular Expression (ETRE) to detect data segments fitting these driving patterns. Simulation results indicate that by only using up to 10.71% of the data on average, the proposed method provides a low-bias and low-variance estimator under non-negligible current and voltage noise compared to other conventional estimation algorithms.
@article{arxiv.2512.12370,
title = {Data-Selective Online Battery Identification Using Extended Time Regular Expressions},
author = {Nicolai A. Weinreich and Marco Muñiz and Marius Mikučionis and Kim G. Larsen and Remus Teodorescu},
journal= {arXiv preprint arXiv:2512.12370},
year = {2025}
}
Comments
This work has been submitted to IFAC for possible publication