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Naslov:A genetic algorithm based ESC model to handle the unknown initial conditions of state of charge for lithium ion battery cell
Avtorji:ID Korez, Kristijan (Avtor)
ID Fister, Dušan (Avtor)
ID Šafarič, Riko (Avtor)
Datoteke:.pdf batteries-11-00001.pdf (5,96 MB)
MD5: D26421DA114C58D742B43B54DDD16373
 
Jezik:Angleški jezik
Vrsta gradiva:Članek v reviji
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:FERI - Fakulteta za elektrotehniko, računalništvo in informatiko
Opis:Classic enhanced self-correcting battery equivalent models require proper model parameters and initial conditions such as the initial state of charge for its unbiased functioning. Obtaining parameters is often conducted by optimization using evolutionary algorithms. Obtaining the initial state of charge is often conducted by measurements, which can be burdensome in practice. Incorrect initial conditions can introduce bias, leading to long-term drift and inaccurate state of charge readings. To address this, we propose two simple and efficient equivalent model frameworks that are optimized by a genetic algorithm and are able to determine the initial conditions autonomously. The first framework applies the feedback loop mechanism that gradually with time corrects the externally given initial condition that is originally a biased arbitrary value within a certain domain. The second framework applies the genetic algorithm to search for an unbiased estimate of the initial condition. Long-term experiments have demonstrated that these frameworks do not deviate from controlled benchmarks with known initial conditions. Additionally, our experiments have shown that all implemented models significantly outperformed the well-known ampere-hour coulomb counter integration method, which is prone to drift over time and the extended Kalman filter, that acted with bias.
Ključne besede:enhanced self-correcting model, state of charge estimation, lithium-ion cell parameter identification
Verzija publikacije:Objavljena publikacija
Poslano v recenzijo:01.12.2024
Datum sprejetja članka:18.12.2024
Datum objave:24.12.2024
Založnik:MDPI
Leto izida:2025
Št. strani:26 str.
Številčenje:Vol. 11, iss. 1
PID:20.500.12556/DKUM-91502 Novo okno
UDK:681.5
COBISS.SI-ID:221279747 Novo okno
DOI:10.3390/batteries11010001 Novo okno
ISSN pri članku:2313-0105
Avtorske pravice:© 2024 by the authors
Datum objave v DKUM:08.01.2025
Število ogledov:0
Število prenosov:4
Metapodatki:XML DC-XML DC-RDF
Področja:Ostalo
:
KOREZ, Kristijan, FISTER, Dušan in ŠAFARIČ, Riko, 2025, A genetic algorithm based ESC model to handle the unknown initial conditions of state of charge for lithium ion battery cell. Batteries [na spletu]. 2025. Vol. 11, no. 1. [Dostopano 22 april 2025]. DOI 10.3390/batteries11010001. Pridobljeno s: https://dk.um.si/IzpisGradiva.php?lang=slv&id=91502
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Gradivo je del revije

Naslov:Batteries
Skrajšan naslov:Batteries
Založnik:MDPI AG
ISSN:2313-0105
COBISS.SI-ID:525652761 Novo okno

Gradivo je financirano iz projekta

Financer:ARIS - Javna agencija za znanstvenoraziskovalno in inovacijsko dejavnost Republike Slovenije
Številka projekta:P2-0028-2019
Naslov:Mehatronski sistemi

Licence

Licenca:CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
Povezava:http://creativecommons.org/licenses/by/4.0/deed.sl
Opis:To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.

Sekundarni jezik

Jezik:Slovenski jezik
Ključne besede:baterije, življenjska doba, naprave


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