{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T18:00:31Z","timestamp":1778608831849,"version":"3.51.4"},"reference-count":32,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2017,4,17]],"date-time":"2017-04-17T00:00:00Z","timestamp":1492387200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Li-Ion batteries are widely preferred in electric vehicles. The charge status of batteries is a critical evaluation issue, and many researchers are studying in this area. State of charge gives information about how much longer the battery can be used and when the charging process will be cut off. Incorrect predictions may cause overcharging or over-discharging of the battery. In this study, a low-cost embedded system is used to determine the state of charge of an electric car. A Li-Ion battery cell is trained using a feed-forward neural network via Matlab\/Neural Network Toolbox. The trained cell is adapted to the whole battery pack of the electric car and embedded via Matlab\/Simulink to a low-cost microcontroller that proposed a system in real-time. The experimental results indicated that accurate robust estimation results could be obtained by the proposed system.<\/jats:p>","DOI":"10.3390\/e19040146","type":"journal-article","created":{"date-parts":[[2017,4,18]],"date-time":"2017-04-18T11:22:04Z","timestamp":1492514524000},"page":"146","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Design and Implementation of SOC Prediction for a Li-Ion Battery Pack in an Electric Car with an Embedded System"],"prefix":"10.3390","volume":"19","author":[{"given":"Emel","family":"Soylu","sequence":"first","affiliation":[{"name":"Department of Mechatronics Engineering, Technology Faculty, Karab\u00fck University, Karab\u00fck 78050, Turkey"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tuncay","family":"Soylu","sequence":"additional","affiliation":[{"name":"Department of Electric and Electronics Engineering, Graduate School of Natural and Applied Sciences, Karab\u00fck University, Karab\u00fck 78050, Turkey"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3155-8771","authenticated-orcid":false,"given":"Raif","family":"Bayir","sequence":"additional","affiliation":[{"name":"Department of Mechatronics Engineering, Technology Faculty, Karab\u00fck University, Karab\u00fck 78050, Turkey"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2017,4,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Dhameja, S. 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