Genetic PI based model and path tracking control of four traction electrical vehicle

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dc.authorid0000-0001-9472-2327en_US
dc.authorid0000-0001-7341-1714
dc.authorid0000-0002-5193-7990
dc.contributor.authorDoğan, Muhsin Uğur
dc.contributor.authorGüvenç, Uğur
dc.contributor.authorElmas, Çetin
dc.date.accessioned2021-06-23T19:54:13Z
dc.date.available2021-06-23T19:54:13Z
dc.date.issued2020
dc.departmentBAİBÜ, Bolu Teknik Bilimler Meslek Yüksekokulu, Elektronik Ve Otomasyon Bölümüen_US
dc.description.abstractModeling and control of four-wheel electric vehicles are difficult due to their dynamic parameters and variable road conditions. In this paper, a robust and adaptive electric vehicle model and position control that can be adapted to state variables using a dynamic lateral and longitudinal model of a four-wheel electric vehicle have been proposed. The longitudinal and lateral forces have been modeled according to Newton's second law, depending on the parameters such as the vehicle's size, width, height, weight and slope angle by using dynamic equations of the vehicle. In this paper, a permanent magnet synchronous hub motor has been used for each wheel of the electric vehicle. The magic formula wheel model has been used to determine the relationship between the slip and the friction of the designed vehicle. Using the slip system, the relationship between the speed of the electric vehicle itself and the wheel speeds have been defined. The proportional controller at the position loop and proportional + integral controller at the speed loop of the designed system have been used. In the path tracking control system, position controls have been made in the X and Y coordinate planes. A P position controller and a PI speed controller have been used for each plane. Thus, there are 6 controller coefficients in total. Because of the complicated structure of the system, it is difficult to determine the most suitable controller coefficients by analytical methods. Therefore, the genetic algorithm which is one of the heuristic algorithms has been used in determining these coefficients. Simulation studies have been conducted with a different path and position references to see the effectiveness of the proposed electric vehicle model and position control. The obtained results show that the proposed model and control system are robust, effective and reliable.en_US
dc.identifier.doi10.1007/s00202-020-01015-5
dc.identifier.endpage2073en_US
dc.identifier.issn0948-7921
dc.identifier.issn1432-0487
dc.identifier.issue4en_US
dc.identifier.scopus2-s2.0-85085297610en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage2059en_US
dc.identifier.urihttps://doi.org/10.1007/s00202-020-01015-5
dc.identifier.urihttps://hdl.handle.net/20.500.12491/10464
dc.identifier.volume102en_US
dc.identifier.wosWOS:000534725500001en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorDoğan, Muhsin Uğur
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofElectrical Engineeringen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectElectrical Vehiclesen_US
dc.subjectPosition Controlen_US
dc.subjectGenetic-PI Controlleren_US
dc.subjectPermanent Magnet Synchronous Hub Motoren_US
dc.subjectMagic Formula Modelen_US
dc.titleGenetic PI based model and path tracking control of four traction electrical vehicleen_US
dc.typeArticleen_US

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