Robust and Regularized Algorithms for Vehicle Tractive Force Prediction and Mass Estimation

This work provides novel robust and regularized algorithms for parameter estimation with applications in vehicle tractive force prediction and mass estimation. Given a large record of real world data from test runs on public roads, recursive algorithms adjusted the unknown vehicle parameters under a...

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Bibliographic Details
Main Author: Rhode, Stephan (auth)
Format: Electronic Book Chapter
Language:English
Published: KIT Scientific Publishing 2018
Series:Karlsruher Schriftenreihe Fahrzeugsystemtechnik / Institut für Fahrzeugsystemtechnik
Subjects:
Online Access:DOAB: download the publication
DOAB: description of the publication
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520 |a This work provides novel robust and regularized algorithms for parameter estimation with applications in vehicle tractive force prediction and mass estimation. Given a large record of real world data from test runs on public roads, recursive algorithms adjusted the unknown vehicle parameters under a broad variation of statistical assumptions for two linear gray-box models. 
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653 |a errors-in-variables 
653 |a robust estimation 
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653 |a Robuste Schätzer 
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653 |a system identification 
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