dc.contributor.author | Lenkutis, Tadas | |
dc.contributor.author | Čerškus, Aurimas | |
dc.contributor.author | Sitiajev, Nikita Edgar | |
dc.contributor.author | Dumbrava, Kęstutis | |
dc.contributor.author | Staugaitė, Ieva | |
dc.contributor.author | Šešok, Nikolaj | |
dc.contributor.author | Dzedzickis, Andrius | |
dc.contributor.author | Bučinskas, Vytautas | |
dc.date.accessioned | 2023-09-18T20:43:42Z | |
dc.date.available | 2023-09-18T20:43:42Z | |
dc.date.issued | 2021 | |
dc.identifier.uri | https://etalpykla.vilniustech.lt/handle/123456789/152101 | |
dc.description.abstract | Road irregularities are the main effect influencing driving quality, due to its unpredictability driver can not find the best driving parameters easily and fast. Identification of road profile lets us control the vehicle’s damping characteristics and increase driving quality as fast as possible. Power Spectral Density (PSD) could be easily found from the road profile. Deduction of road waviness and amplitudes from PSD could be used to provide the mandatory information required for controllable damping system. Using our developed dynamic model of the car, we performed a simulation of the vehicle passing artificially generated road profiles with different waviness. Obtained results show that the straight-line approximation of PSD of the road profile as recommended by ISO standard doesn’t provide suitable information required for the control of car suspension. We define that, two split approximations of PSD spectra is a better solution for this purpose. It provides reliable results and allows to choose optimal damping coefficient value with a small delay for long distances. | eng |
dc.format | PDF | |
dc.format.extent | p. 146-153 | |
dc.format.medium | tekstas / txt | |
dc.language.iso | eng | |
dc.relation.ispartofseries | Advances in intelligent systems and computing (AISC) vol. 1390 2194-5357 2194-5365 | |
dc.relation.isreferencedby | INSPEC | |
dc.relation.isreferencedby | DBLP | |
dc.relation.isreferencedby | SpringerLink | |
dc.relation.isreferencedby | EI Compendex Plus | |
dc.relation.isreferencedby | Zentralblatt MATH (zbMATH) | |
dc.relation.isreferencedby | Scopus | |
dc.rights | Neprieinamas | |
dc.source.uri | https://doi.org/10.1007/978-3-030-74893-7_15 | |
dc.source.uri | https://link.springer.com/content/pdf/10.1007%2F978-3-030-74893-7.pdf | |
dc.title | Extraction of information from a PSD for the control of vehicle suspension | |
dc.type | Straipsnis konferencijos darbų leidinyje Scopus DB / Paper in conference publication in Scopus DB | |
dcterms.references | 16 | |
dc.type.pubtype | P1b - Straipsnis konferencijos darbų leidinyje Scopus DB / Article in conference proceedings Scopus DB | |
dc.contributor.institution | Vilniaus Gedimino technikos universitetas | |
dc.contributor.faculty | Mechanikos fakultetas / Faculty of Mechanics | |
dc.subject.researchfield | T 009 - Mechanikos inžinerija / Mechanical enginering | |
dc.subject.studydirection | E06 - Mechanikos inžinerija / Mechanical engineering | |
dc.subject.vgtuprioritizedfields | MC03 - Išmaniosios įterptinės sistemos / Smart embedded systems | |
dc.subject.ltspecializations | L104 - Nauji gamybos procesai, medžiagos ir technologijos / New production processes, materials and technologies | |
dc.subject.en | road profile | |
dc.subject.en | power spectra density | |
dc.subject.en | waviness | |
dc.subject.en | damping | |
dcterms.sourcetitle | Automation 2021: Recent achievements in automation, robotics and measurement techniques | |
dc.publisher.name | Springer | |
dc.publisher.city | Cham | |
dc.identifier.doi | 10.1007/978-3-030-74893-7_15 | |
dc.identifier.elaba | 92162095 | |