{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T11:11:51Z","timestamp":1777893111428,"version":"3.51.4"},"reference-count":26,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2025,2,27]],"date-time":"2025-02-27T00:00:00Z","timestamp":1740614400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Tecnol\u00f3gico Nacional de M\u00e9xico"},{"name":"project PID2022-137593OBI00"},{"name":"MCIN\/AEI\/10.13039\/501100011033\/FEDER, UE, and FSE+"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>Power quality is one of the most critical fields in the energy sector. The connection of electric vehicles to the electrical grid can cause a degradation of energy quality when charging or discharging the battery. Identifying sudden voltage drops, surges, and network interruptions is essential to avoid network failure. A multiple fault classification\/monitoring system has been developed based on artificial neural networks and implemented in an FPGA. The system\u2019s performance has been evaluated using a set of data obtained from MATLAB\/Simulink 2024. Different dataset combinations are implemented, trained, validated, and tested on three multilayer perceptron (MLP) models of various configurations. The analysis shows that the MLP designed with 12-bit fixed-point data precision is the most efficient MLP implementation in classification accuracy, compared to 8, 12, 20, and 24-bit fixed-point data. The system achieved 99.95% classification accuracy across various fault conditions, demonstrating its capability for real-time deployment.<\/jats:p>","DOI":"10.3390\/info16030180","type":"journal-article","created":{"date-parts":[[2025,2,27]],"date-time":"2025-02-27T03:37:57Z","timestamp":1740627477000},"page":"180","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["FPGA Implementation of Multilayer Perceptron for Real-Time Detection of Power Quality Disturbances for Electric Vehicle Charger"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1752-3126","authenticated-orcid":false,"given":"Luis-Fernando","family":"Gaona-C\u00e1rdenas","sequence":"first","affiliation":[{"name":"Electronics Department, Tecnol\u00f3gico Nacional de M\u00e9xico en Celaya, Celaya 38010, Mexico"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6363-513X","authenticated-orcid":false,"given":"Nimrod","family":"Vazquez","sequence":"additional","affiliation":[{"name":"Electronics Department, Tecnol\u00f3gico Nacional de M\u00e9xico en Celaya, Celaya 38010, Mexico"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4542-3598","authenticated-orcid":false,"given":"Leonel","family":"Estrada","sequence":"additional","affiliation":[{"name":"Electronics Department, Tecnol\u00f3gico Nacional de M\u00e9xico en Celaya, Celaya 38010, Mexico"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4622-1269","authenticated-orcid":false,"given":"Elyas","family":"Zamiri","sequence":"additional","affiliation":[{"name":"HCTLab Research Group, Electronics and Communications Technology Department, Universidad Aut\u00f3noma de Madrid, 28049 Madrid, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4357-7857","authenticated-orcid":false,"given":"Angel","family":"de Castro","sequence":"additional","affiliation":[{"name":"HCTLab Research Group, Electronics and Communications Technology Department, Universidad Aut\u00f3noma de Madrid, 28049 Madrid, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7512-6615","authenticated-orcid":false,"given":"Sergio","family":"Pinto","sequence":"additional","affiliation":[{"name":"Faculty of Informatics, Electronics, and Communications, Central Campus, Universidad de Panama, Panama City 3366, Panama"},{"name":"School of Digital Innovation, Instituto T\u00e9cnico Superior Especializado (ITSE) de Panama, Tocumen, Avenida Domingo D\u00edaz, Panama City 07202, Panama"}]}],"member":"1968","published-online":{"date-parts":[[2025,2,27]]},"reference":[{"key":"ref_1","unstructured":"Kumar, K., Roy, S., and Raiu, M. 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