@Article{CaldeiraCarvCost:2017:EsTrVe,
author = "Caldeira, Ald{\'e}lio Bueno and Carvalho, Michelle Soraia de and
Costa Neto, Ricardo Teixeira da",
affiliation = "{Instituto Militar de Engenharia (IME)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)} and {Instituto Militar de Engenharia
(IME)}",
title = "Estimation of tracked vehicle suspension parameters",
journal = "Acta Scientiarum - Technology",
year = "2017",
volume = "39",
number = "1",
pages = "51--57",
month = "jan./mar.",
keywords = "vehicle suspension, inverse problem, R2W, PSO.",
abstract = "This work aims to estimate the suspension stiffness and damping
coefficient of a tracked vehicle by using an inverse problem
technique based on Particle Swarm Optimization ( PSO) and on
Random Restricted Window (R2W). The tracked vehicle has ten road
wheels. Each road wheel is linked to a passive and independent
suspension. A half car model with seven degrees of freedom
describes the bounce and pitch dynamics of the chassis and the
vertical dynamics of the wheels. Bounce and pitch accelerations
are evaluated when the vehicle traverses a bump terrain. The
inverse problem approach minimizes the total quadratic error
between estimated and pseudo-experimental data for bounce and
pitch accelerations. The viability of a field experiment to
estimate the suspension parameters is analyzed, as well as the
performance of the employed optimization methods and the effects
of the noise on pseudo-experimental data.",
doi = "10.4025/actascitechnol.v39i1.29385",
url = "http://dx.doi.org/10.4025/actascitechnol.v39i1.29385",
issn = "1806-2563",
language = "en",
targetfile = "caldeira.pdf",
urlaccessdate = "27 abr. 2024"
}