Change search
ReferencesLink to record
Permanent link

Direct link
Vehicle Mass and Road Grade Estimation Using Kalman Filter
Linköping University, Department of Electrical Engineering, Vehicular Systems.
2011 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

This Master's thesis presents a method for on-line estimation of vehicle mass and road grade using Kalman filter. Many control strategies aiming for better fuel economy, drivability and safety in today's vehicles rely on precise vehicle operating information. In this context, vehicle mass and road grade are crucial parameters. The method is based on an extended Kalman filter (EKF) and a longitudinal vehicle model. The main advantage of this method is its applicability on drivelines with continuous power output during gear shifts and cost effectiveness compared to hardware solutions. The performance has been tested on both simulated data and on real measurement data, collected with a truck on road. Two estimators were developed; one estimates both vehicle mass and road grade and the other estimates only vehicle mass using an inclination sensor as an additional measurement. Tests of the former estimator demonstrate that a reliable mass estimate with less than 5 % error is often achievable within 5 minutes of driving. Furthermore, the root mean square error of the grade estimate is often within 0.5°. Tests of the latter estimator show that this is more accurate and robust than the former estimator with a mass error often within 2 %. A sensitivity analysis shows that the former estimator is fairly robust towards minor modelling errors. Also, an observability analysis shows under which circumstances simultaneous vehicle mass and road grade is possible.

Place, publisher, year, edition, pages
2011. , 38 p.
Keyword [en]
Vehicle mass estimation, Road grade estimation, Extended Kalman filter, Vehicle model, Nonlinear observability, Truck sensors
National Category
Control Engineering
URN: urn:nbn:se:liu:diva-70266ISRN: LiTH-ISY-EX--11/4491--SEOAI: diva2:437583
Subject / course
Vehicular Systems
2011-08-16, Algoritmen, Linköping, 10:15 (Swedish)
Available from: 2011-08-30 Created: 2011-08-29 Last updated: 2011-08-30Bibliographically approved

Open Access in DiVA

Vehicle Mass and Road Grade Estimation Using Kalman Filter(904 kB)1476 downloads
File information
File name FULLTEXT01.pdfFile size 904 kBChecksum SHA-512
Type fulltextMimetype application/pdf

By organisation
Vehicular Systems
Control Engineering

Search outside of DiVA

GoogleGoogle Scholar
Total: 1476 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 510 hits
ReferencesLink to record
Permanent link

Direct link