Fuel Level Estimation for Heavy Vehicles using a Kalman Filter
Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
The object with this project is to develop a more accurate way to measure the level in the fuel tank in Scaniavehicles. The level should be displayed for the driver and a warning system be implemented to make the driveraware if the fuel level is too low. Furthermore a main goal is to develop an estimation of the distance that thevehicle could travel before refueling is needed.The fuel level estimation system is modeled using Matlab Simulink and simulated with measurement datacollected from real driving scenarios. After evaluating the system it is implemented in one of the electricalcontrol units located on a test vehicle which communicates with other systems. After implementation more testsare performed with the test vehicle to verify that the same functionality achieved during simulations is achievedusing the system implemented in a vehicle.The fuel level estimated with a KF (Kalman filter) that uses fuel consumption and level measurement results ingood performance. A more stable level estimate is achieved and a negative elevation of the estimate most of thetime, as a result of fuel use. Compared to the method Scania vehicles estimate their fuel level with today thenew level estimate is more steady and not that easily affected by fuel movements. The KF is more demanding interms of memory allocation, processor speed and inputs needed, which has to be considered when comparingboth methods. Another disadvantage with the KF is that it is dependent on the samples from the fuel levelsensor to get an initial estimate during startup.Furthermore the KF is easily expanded with more inputs that use information from other sensors on other parts of the vehicle.
Place, publisher, year, edition, pages
2008. , 61 p.
Kalman filter, distance estimation, fuel tanks
Engineering and Technology
IdentifiersURN: urn:nbn:se:liu:diva-15702ISRN: LiTH-ISY-EX--08/4184--SEOAI: oai:DiVA.org:liu-15702DiVA: diva2:127029
2008-11-17, Algoritmen, B-huset , Linköpings Universitet, Linköping, 10:00 (Swedish)
Sundström, Christofer, Ph.D student
Frisk, Erik, Associate Professor