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Optimally Fuel Ecient Speed Adaptation
KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik.
2008 (engelsk)Independent thesis Advanced level (professional degree), 20 poäng / 30 hpOppgave
Abstract [en]

An optimal velocity trajectory for a heavy duty vehicle, obtained with the aid of modern GPS and digital map devices, depends on several variables. Curvature speed limitations, road grade, and posted road speed are common constraints imposed by the road travelled. This thesis presents a method for modelling and analysing a switching controller through the use of the former mentioned constraints. A non-linear model for the heavy duty vehicle is derived, enabling suitable control methods to be applied. Pontryagin’s Principal and LQR are discussed to get a profound understanding of how the controller should be designed. It is discovered that a switching controller based on optimal control and engineering experience is most favourable for the problem at hand. The controller is designed to address the main objectives set in this paper of minimising fuel consumption, travelling time, and brake wear.

Gauss-Newtons’s algorithm for non-linear equations is used to estimate curve radii. Other input parameters are presumed to be available. GPS data error is discussed to perform a sensitivity analysis. An electronic horizon is produced on three road segments, entailed with data of the future road topology. Finally the switching controller is applied to the road segments. Experimental results show that the controller produces a velocity trajectory, which reduces fuel consumption by 5-15% and brake wear by 15-35%, while the travelling time is only increased by 1-2%.

sted, utgiver, år, opplag, sider
2008. , s. 57
HSV kategori
Identifikatorer
URN: urn:nbn:se:kth:diva-105886OAI: oai:DiVA.org:kth-105886DiVA, id: diva2:572713
Fag / kurs
Automatic Control
Utdanningsprogram
Master of Science in Engineering
Uppsök
Technology
Examiner
Tilgjengelig fra: 2012-12-03 Laget: 2012-11-28 Sist oppdatert: 2012-12-03bibliografisk kontrollert

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