<p>The Automated Manual Transmission system Opticruise is dependent on signals from sensors located in different parts of the Scania trucks. These signals are of different qualities and have different update frequencies. Some signals and quantities that are hard or impossible to measure are also of importance to this system.</p><p>In this thesis a driveline observer for the purpose of signal improvement is developed and estimations of unknown quantities such as road incline and mass of the vehicle are performed. The outputs of the observer are produced at a rate of 100 Hz, and include in addition to the mass and road incline also the speed of the engine, output shaft of the gearbox, wheel and the torsion in the driveline. Further the use of an accelerometer and the advantages gained from using it in the observer are investigated.</p><p>The outputs show an increased quality and much of the measurement noise is successfully removed without introducing any time delays. A simulation frequency of 100 Hz is possible, but some dependency toward the stiffness of the driveline is found. The observer manages to estimate the road slope accurately. With the use of an accelerometer the road slope estimation is further improved and a quickly converging mass estimation is obtained.</p>

The Automated Manual Transmission system Opticruise is dependent on signals from sensors located in different parts of the Scania trucks. These signals are of different qualities and have different update frequencies. Some signals and quantities that are hard or impossible to measure are also of importance to this system. In this thesis a driveline observer for the purpose of signal improvement is developed and estimations of unknown quantities such as road incline and mass of the vehicle are performed. The outputs of the observer are produced at a rate of 100 Hz, and include in addition to the mass and road incline also the speed of the engine, output shaft of the gearbox, wheel and the torsion in the driveline. Further the use of an accelerometer and the advantages gained from using it in the observer are investigated. The outputs show an increased quality and much of the measurement noise is successfully removed without introducing any time delays. A simulation frequency of 100 Hz is possible, but some dependency toward the stiffness of the driveline is found. The observer manages to estimate the road slope accurately. With the use of an accelerometer the road slope estimation is further improved and a quickly converging mass estimation is obtained.

<p>Knowledge about the current road slope can improve several applications in a heavy-duty vehicle such as predictive cruise control and automated gearbox control. In this thesis the possibility of estimating the road slope based on signals from a vehicles air suspension system has been studied. More specifically, the measurement consists of a pressure signal measuring the axle load, and a vertical distance sensor.</p><p>A variety of suspension systems can be mounted on a Scania truck. During this thesis, two discrete-time models based on two different rear axle air suspension systems have been proposed. The models use the effect of alternating axle load during a change in the road slope and the estimates are computed using an extended Kalman filter.</p><p>The first model is based on a rear axle suspension known as the 2-bellow system. This type of suspension is strongly affected by the driveshaft torque, which results in a behaviour where the rear end is pushed upwards and thus decreasing the rear axle load during uphill driving. A model was developed in order to compensate for this behaviour. Unfortunately, the estimates showed less promising results and all attempts to determine the error was unsuccessful.</p><p>The latter model is based on the 4-bellow system. This suspension system is not affected by the driveshaft torque and a less complex model could be derived. The experimental results indicated that road slope estimation was possible and with a fairly accurate result. However, more work is needed since the estimate is affected by road surface irregularities and since the algorithm requires knowledge about the vehicles mass and the location of the centre of gravity.</p><p>All the presented results have been estimated based on real data from a test track at Scania Technical Centre in Södertälje.</p>

Knowledge about the current road slope can improve several applications in a heavy-duty vehicle such as predictive cruise control and automated gearbox control. In this thesis the possibility of estimating the road slope based on signals from a vehicles air suspension system has been studied. More specifically, the measurement consists of a pressure signal measuring the axle load, and a vertical distance sensor. A variety of suspension systems can be mounted on a Scania truck. During this thesis, two discrete-time models based on two different rear axle air suspension systems have been proposed. The models use the effect of alternating axle load during a change in the road slope and the estimates are computed using an extended Kalman filter. The first model is based on a rear axle suspension known as the 2-bellow system. This type of suspension is strongly affected by the driveshaft torque, which results in a behaviour where the rear end is pushed upwards and thus decreasing the rear axle load during uphill driving. A model was developed in order to compensate for this behaviour. Unfortunately, the estimates showed less promising results and all attempts to determine the error was unsuccessful. The latter model is based on the 4-bellow system. This suspension system is not affected by the driveshaft torque and a less complex model could be derived. The experimental results indicated that road slope estimation was possible and with a fairly accurate result. However, more work is needed since the estimate is affected by road surface irregularities and since the algorithm requires knowledge about the vehicles mass and the location of the centre of gravity. All the presented results have been estimated based on real data from a test track at Scania Technical Centre in Södertälje.

NVDB contains information of Sweden’s roads and a large number of properties concerning them. This information is provided as open data and is commonly usedin routing. For an optimal route optimization, several attributes are needed based on the road properties. At the time that this report was written, there was no attribute for slopes. The purpose of this report was, in collaboration with the Swedish transport Administration, to develop a new property “slope” for route optimization based on fuel consumption. The development of the slope phenomenon was built with FME where a script was created that calculated inclination on road links.The script calculated the inclination using a variation of the linear equation. Where x, y and z coordinates and attributes from NVDB were used to obtain values for the equation.The testing and validation of the generated slope property was performed with route optimization in the ArcMap application. The results from route optimization and previous research show a significant reduction in fuel consumption within routes with regard to slope. / NVDB innehåller information om Sveriges vägar och ett stort antal egenskaper för vägarna. Informationen tillhandahålls som öppen data och används ofta inom ruttning. För en optimal ruttoptimering behövs det ett flertal attribut baserat på vägegenskaper. Under tiden den här rapporten skapades så saknades det ett attribut för lutning. Syftet med den här rapporten var att i samarbete med Trafikverket ta fram en ny egenskap “lutning” vid ruttoptimering baserat på bränsleförbrukning. Framtagandet av lutningsföreteelsen var uppbyggt med hjälp av FME där ett skript skapades som beräknade lutningen i väglänkarna. §Skriptet beräknade lutning med hjälp av en variation av räta linjens ekvation. Därx, y och z koordinater samt attribut från NVDB användes för att få fram värden för ekvationen. Testandet och valideringen av den framtagna lutningsegenskapen framfördes med ruttoptimering i programmet ArcMap. Resultatet av ruttoptimeringen och tidigare forskning visar markant reduktion av bränsleförbrukning inom rutter med hänsyntill lutning.