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Vehicle Mass Estimation Using a Total Least-Squares Approach

Rhode, S.; Gauterin, F.

Abstract:

We introduce an incremental total least-squares vehicle mass estimation algorithm, based on a vehicle longitudinal dynamics model. Available control area network signals are used as model inputs and output. In contrast to common vehicle mass estimation schemes, where noise is only considered at the model output, our algorithm uses an errors-in-variables formulation and considers noise at the model inputs as well. A robust outlier treatment is realized as batch total least-squares routine and hence, the proposed algorithm works in a superior way on a broad range of vehicle acceleration. The results of six test runs on various vehicle masses show highly accurate mass estimation results on high and low dynamics of vehicular operation.


Volltext §
DOI: 10.5445/IR/1000030416
Originalveröffentlichung
DOI: 10.1109/ITSC.2012.6338638
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Zitationen: 18
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Fahrzeugsystemtechnik (FAST)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2012
Sprache Englisch
Identifikator ISBN: 978-1-4673-3064-0
urn:nbn:de:swb:90-304165
KITopen-ID: 1000030416
Erschienen in 15th International IEEE Conference on Intelligent Transportation Systems Intelligent Transportation Systems (ITSC), 2012, Anchorage, Alaska, USA, September 16-19, 2012
Verlag Institute of Electrical and Electronics Engineers (IEEE)
Seiten 1584-1589
Bemerkung zur Veröffentlichung This is the accepted version.

Please find the final version in IEEE Xplore

http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&tp=&arnumber=6338638&contentType=Conference+Publications&refinements%3D4282407474%26sortType%3Dasc_p_Sequence%26filter%3DAND%28p_IS_Number%3A6338591%29
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