DocumentCode :
1806146
Title :
Road slope and vehicle mass estimation for light commercial vehicle using linear Kalman filter and RLS with forgetting factor integrated approach
Author :
Raffone, Enrico
Author_Institution :
VRT - Chassis Control Syst. & Performances, Centro Ric. FIAT S.c.p.A., Orbassano, Italy
fYear :
2013
fDate :
9-12 July 2013
Firstpage :
1167
Lastpage :
1172
Abstract :
This paper explains application of Kalman filter theory and recursive least squares algorithm with forgetting factor on real time estimation problem of light commercial vehicle mass and road grade on which motor vehicle moves. After a brief survey on mass and slope estimating in literature, there are proposed algorithms theoretical approaches and implementations on a real-time ECU. The test data are obtained from urban, extra-urban and highway experiments with prototypal vehicles.
Keywords :
Kalman filters; least squares approximations; road vehicles; state estimation; RLS; forgetting factor integrated approach; light commercial vehicle mass estimation; linear Kalman filter; motor vehicle; real-time ECU; real-time estimation problem; recursive least square estimation algorithm; road grade; road slope estimation; vehicle mass estimation; Acceleration; Equations; Estimation; Kalman filters; Mathematical model; Roads; Vehicles; Autoregressive processes; Estimation Observers; Filtering algorithms; Kalman filters; Least square method; Parameter estimation; Recursive estimation; State estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Fusion (FUSION), 2013 16th International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-605-86311-1-3
Type :
conf
Filename :
6641128
Link To Document :
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