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arXiv · 2512.12370

Data-Selective Online Battery Identification Using Extended Time Regular Expressions

Nicolai A. Weinreich·Marco Muñiz·Marius Mikučionis·Kim G. Larsen·Remus Teodorescu
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Abstract

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.

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Nicolai A. Weinreich, Marco Muñiz, Marius Mikučionis, Kim G. Larsen, Remus Teodorescu. 2025-12-13. Data-Selective Online Battery Identification Using Extended Time Regular Expressions. https://arxiv.org/abs/2512.12370

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