Vehicle mass estimation using a total least-squares approach

Stephan Rhode, Frank Gauterin
2012 2012 15th International IEEE Conference on Intelligent Transportation Systems  
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 outliner treatment is realized as batch total least-squares routine and
more » ... nce, 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.
doi:10.1109/itsc.2012.6338638 dblp:conf/itsc/RhodeG12 fatcat:ctrlklosyrddzo5q3gt36i5uk4