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Maintenance planning of trucks at Scania have previously been done using static cyclic plans with fixed sets of maintenance tasks, determined by mileage, calendar time, and some data driven physical models. Flexible maintenance have improved the maintenance program with the addition of general data driven expert rules and the ability to move sub-sets of maintenance tasks between maintenance occasions. Meanwhile, successful modelling with machine learning on big data, automatic planning using constraint programming, and route optimization are hinting on the ability to achieve even higher fleet utilization by further improvements of the flexible maintenance. The maintenance program have therefore been partitioned into its smallest parts and formulated as individual constraint rules. The overall goal is to maximize the utilization of a fleet, i.e. maximize the ability to perform transport assignments, with respect to maintenance.

Traditionally, an in-vehicle map consists of only one type of data, tailored for a single user function. For example, the navigation maps contain spatial information about the roads. On the other hand, a map built for adaptive cruise control use consists of the detected vehicles and their properties. In autonomous vehicle research, the maps are often built up as an occupancy grid where areas are classified as passable or impassable. Using these kinds of maps separately, however, is not enough to support the traffic safety enhancing and advanced driver assistance systems of today and tomorrow. Instead of using separate systems to handle individual safety or planning tasks, information could be stored in one shared map containing several correlated layers of information. Map information can be collected by any number of different sensor devices, and fusion algorithms can be used to enhance the quality of the information.

Heavy-duty transportation is one of the sectors that contributes to greenhouse gas emissions. One way to reduce CO2 emissions is to use drop-in fuels. However, when drop-in fuels are used, i.e., higher blends of alternative fuels are added to conventional fuels, solubility problems and precipitation in the fuel can occur. As a result, insolubles in the fuel can clog the fuel filters and interfere with the proper functioning of the injectors. This adversely affects engine performance and increases fuel consumption. These problems are expected to increase with the development of more advanced fuel systems to meet upcoming environmental regulations. This work investigates the composition of the deposits formed inside the injectors of the heavy-duty diesel engine and discusses their formation mechanism. Injectors with internal deposits were collected from field trucks throughout Europe. Similar content, location and structure were found for all the deposits in the studied injectors.

Planetary gears in heavy truck gearboxes are normally manufactured by forging a blank, turning, hobbing, shaving and heat-treatment followed by grinding. Due to the size of the gear the net shape capability of PM methods can be cost effective alternatively to conventional manufacturing. Warm compaction and surface densification are two PM methods to reach high density and thereby high strength and fatigue properties. Typical characteristics for PM gears manufactured by these methods are outlined.

Diesel engine manufacturers strive towards further efficiency improvements. Thus, reducing in-cylinder heat losses is becoming increasingly important. Understanding how location, thermal insulation, and engine operating conditions affect the heat transfer to the combustion chamber walls is fundamental for the future reduction of in-cylinder heat losses. This study investigates the effect of a 1mm-thick plasma-sprayed yttria-stabilized zirconia (YSZ) coating on a piston. Such a coated piston and a similar steel piston are compared to each other based on experimental data for the heat release, the heat transfer rate to the oil in the piston cooling gallery, the local instantaneous surface temperature, and the local instantaneous surface heat flux. The surface temperature was measured for different crank angle positions using phosphor thermometry.

When a truck or bus suffers from a breakdown it is important that the vehicle comes back on the road as soon as possible. In this paper we present a prototype diagnostic decision support system capable of automatically identifying possible causes of a failure and propose recommended actions on how to get the vehicle back on the road as cost efficiently as possible. This troubleshooting system is novel in the way it integrates the remote diagnosis with the workshop diagnosis when providing recommendations. To achieve this integration, a novel planning algorithm has been developed that enables the troubleshooting system to guide the different users (driver, help-desk operator, and mechanic) through the entire troubleshooting process. In this paper we formulate the problem of integrated remote and workshop troubleshooting and present a working prototype that has been implemented to demonstrate all parts of the troubleshooting system.

There is a need for reducing fuel consumption and thereby also reducing CO2 and other emissions in all areas of transportation and the forest industry is no exception. In the particular case of timber trucks special care have to be taken when designing such vehicles; they have to be sturdy and operate in harsh conditions and they are being driven empty half the time. It is well known that the aerodynamic resistance constitutes a significant part of the vehicles driving resistance and four areas in particular, front of vehicle, gap, side/underbody and rear of the vehicle contributes about one quarter each. In order to address these issues a wind tunnel investigation was initiated where a 1:6 scale model of a timber truck was designed to operate in a 3.6 m wind tunnel. The present model resembles a generic timber truck with a flexible design such that different configurations could be tested easily.