EXTERNAL MONITORING SYSTEM FOR BATTERY CONDITION AND STATE OF HEALTH OF LITHIUM-ION BATTERIES

<br>Lithium-ion batteries power light electric vehicles such as electric bicycles, but end users typically lack reliable information about true battery health and instead rely on misleading indicators of remaining charge. In this paper is introduced a novel external plug-and-play diagnostic module that connects between the standard charger and a battery of a light electric vehicle. The system uses a precise discrete-time energy integration method during standard charging. It captures dynamic current fluctuations and estimates battery health from the partial charging data. Experimental validation on multiple battery packs demonstrates that the proposed algorithm reliably distinguishes between healthy and degraded batteries. This non-invasive system adds diagnostics to conventional charging, enabling users to assess actual capacity without full discharge cycles.

Authors

Publication Details

Journal
Communications - Scientific letters of the University of Zilina
Published
2026-04-22
DOI
https://doi.org/10.26552/com.c.2026.028
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
0.00
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article

EXTERNAL MONITORING SYSTEM FOR BATTERY CONDITION AND STATE OF HEALTH OF LITHIUM-ION BATTERIES

Juraj Ďuďák, Dušan Maga, Milan Havelka, Matus Necas
Communications - Scientific letters of the University of Zilina
Advanced Battery Technologies Research
article

EXTERNAL MONITORING SYSTEM FOR BATTERY CONDITION AND STATE OF HEALTH OF LITHIUM-ION BATTERIES

Juraj Ďuďák, Dušan Maga, Milan Havelka, Matus Necas
article en

Abstract

<br>Lithium-ion batteries power light electric vehicles such as electric bicycles, but end users typically lack reliable information about true battery health and instead rely on misleading indicators of remaining charge. In this paper is introduced a novel external plug-and-play diagnostic module that connects between the standard charger and a battery of a light electric vehicle. The system uses a precise discrete-time energy integration method during standard charging. It captures dynamic current fluctuations and estimates battery health from the partial charging data. Experimental validation on multiple battery packs demonstrates that the proposed algorithm reliably distinguishes between healthy and degraded batteries. This non-invasive system adds diagnostics to conventional charging, enabling users to assess actual capacity without full discharge cycles.

Communications - Scientific letters of the University of ZilinaVol. 28(2)
Affordable and clean energy
Openalex Percentile: Top 17%
Advanced Battery Technologies Research
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