Year 2020, Volume 7 , Issue 3, Pages 88 - 94 2020-10-05

Estimation of li-ion battery state of charge using adaptive neural fuzzy inference system (ANFIS)

Yusuf KARABACAK [1] , İ̇lker Ali OZKAN [2] , İ̇smail SARİTAS [3]


Thanks to their electrochemical structure, batteries are the elements that can store electrical energy and spend on a load when the electrical energy they store is needed. Today, with the widespread use of electrically powered mobile devices, rechargeable batteries have become widespread and battery technologies have developed. With the idea that the latest technology systems and electric vehicles will become widespread in the future, the studies on batteries are increasing day by day. In this study, charge state estimation of Li-ion battery cell used to provide power in many applications was realized by using adaptive neural fuzzy inference system (ANFIS). A Li-ion battery was discharged using variable electrical loads with a battery discharge circuit modeled on MATLAB Simulink and current, voltage, temperature and current power parameters of the battery were selected as input variables. Battery parameters and charge status data obtained from discharge tests using different electrical loads on MATLAB Simulink were used as training and test parameters of neural network. Using the MATLAB ANFIS toolbox, the system was trained with 80% of the battery parameters obtained in the battery discharge experiments and with 20% as testing data, the success performance was interpreted by applying the adaptive neural fuzzy inference system.
ANFIS, Battery charge status, Charge status, Estimation, Rechargeable batteries
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Primary Language en
Subjects Engineering, Mechanical
Journal Section Research Article
Authors

Orcid: 0000-0001-9864-7512
Author: Yusuf KARABACAK
Institution: Turkish National University
Country: Turkey


Orcid: 0000-0002-5715-1040
Author: İ̇lker Ali OZKAN (Primary Author)
Institution: SELCUK UNIVERSITY
Country: Turkey


Orcid: 0000-0002-5743-4593
Author: İ̇smail SARİTAS
Institution: SELCUK UNIVERSITY
Country: Turkey


Dates

Application Date : August 10, 2020
Acceptance Date : September 29, 2020
Publication Date : October 5, 2020

Bibtex @research article { ijeat778689, journal = {International Journal of Energy Applications and Technologies}, issn = {}, eissn = {2548-060X}, address = {editor.ijeat@gmail.com}, publisher = {İlker ÖRS}, year = {2020}, volume = {7}, pages = {88 - 94}, doi = {10.31593/ijeat.778689}, title = {Estimation of li-ion battery state of charge using adaptive neural fuzzy inference system (ANFIS)}, key = {cite}, author = {Karabacak, Yusuf and Ozkan, İ̇lker Ali and Sari̇tas, İ̇smail} }
APA Karabacak, Y , Ozkan, İ , Sari̇tas, İ . (2020). Estimation of li-ion battery state of charge using adaptive neural fuzzy inference system (ANFIS) . International Journal of Energy Applications and Technologies , 7 (3) , 88-94 . DOI: 10.31593/ijeat.778689
MLA Karabacak, Y , Ozkan, İ , Sari̇tas, İ . "Estimation of li-ion battery state of charge using adaptive neural fuzzy inference system (ANFIS)" . International Journal of Energy Applications and Technologies 7 (2020 ): 88-94 <https://dergipark.org.tr/en/pub/ijeat/issue/57106/778689>
Chicago Karabacak, Y , Ozkan, İ , Sari̇tas, İ . "Estimation of li-ion battery state of charge using adaptive neural fuzzy inference system (ANFIS)". International Journal of Energy Applications and Technologies 7 (2020 ): 88-94
RIS TY - JOUR T1 - Estimation of li-ion battery state of charge using adaptive neural fuzzy inference system (ANFIS) AU - Yusuf Karabacak , İ̇lker Ali Ozkan , İ̇smail Sari̇tas Y1 - 2020 PY - 2020 N1 - doi: 10.31593/ijeat.778689 DO - 10.31593/ijeat.778689 T2 - International Journal of Energy Applications and Technologies JF - Journal JO - JOR SP - 88 EP - 94 VL - 7 IS - 3 SN - -2548-060X M3 - doi: 10.31593/ijeat.778689 UR - https://doi.org/10.31593/ijeat.778689 Y2 - 2020 ER -
EndNote %0 International Journal of Energy Applications and Technologies Estimation of li-ion battery state of charge using adaptive neural fuzzy inference system (ANFIS) %A Yusuf Karabacak , İ̇lker Ali Ozkan , İ̇smail Sari̇tas %T Estimation of li-ion battery state of charge using adaptive neural fuzzy inference system (ANFIS) %D 2020 %J International Journal of Energy Applications and Technologies %P -2548-060X %V 7 %N 3 %R doi: 10.31593/ijeat.778689 %U 10.31593/ijeat.778689
ISNAD Karabacak, Yusuf , Ozkan, İ̇lker Ali , Sari̇tas, İ̇smail . "Estimation of li-ion battery state of charge using adaptive neural fuzzy inference system (ANFIS)". International Journal of Energy Applications and Technologies 7 / 3 (October 2020): 88-94 . https://doi.org/10.31593/ijeat.778689
AMA Karabacak Y , Ozkan İ , Sari̇tas İ . Estimation of li-ion battery state of charge using adaptive neural fuzzy inference system (ANFIS). IJEAT. 2020; 7(3): 88-94.
Vancouver Karabacak Y , Ozkan İ , Sari̇tas İ . Estimation of li-ion battery state of charge using adaptive neural fuzzy inference system (ANFIS). International Journal of Energy Applications and Technologies. 2020; 7(3): 88-94.