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One way to reduce carbon dioxide emissions from the current heavy-duty vehicles fleet is to replace fossil fuel with renewable fuel. This can be done by blending so-called drop-in fuels into the standard diesel fuel. However, problems such as insoluble impurities may arise when the fuels are mixed. These precipitates, known as soft particles, can cause deposits in the fuel system, e.g., injectors and fuel filters, reducing the engine´s performance. The most used drop-in fuel today is biodiesel which, is blended with different concentrations. To better understand how soft particles are formed in the vehicle´s fuel system, the degradation of biodiesel blends in the engine has been investigated. This study explores biodiesel blends´ degradation process by comparing the incoming fuel with the return fuel from a modern diesel engine to investigate how the fuel is affected by this process. The engine was run using different blends of biodiesel fuel.

Renewable fuels from different feedstocks can enable sustainable transport solutions with significant reduction in greenhouse gas emissions compared to conventional petroleum-derived fuels. Nevertheless, the use of biofuels in diesel engines will still require similar exhaust gas cleaning systems as for conventional diesel. Hence, the use of diesel particulate filters (DPF) will persist as a much needed part of the vehicle’s aftertreatment system. Combustion of renewable fuels can potentially yield soot and ash with different properties as well as larger amounts of ash compared to conventional fossil fuels. The faster ash build-up and altered ash deposition pattern lead to an increase in pressure drop over the DPF, increase the fuel consumption and call for premature DPF maintenance or replacement. Prolonging the maintenance interval of the DPF for heavy-duty trucks, having a demand for high up-time, is highly desirable.

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.

The effect of blockage due to the presence of the wind tunnel walls has been known since the early days of wind tunnel testing. Today there are several blockage correction methods available for correcting the measured aerodynamic drag. Due to the shape of the test object, test conditions and wind tunnel dimensions the effect on the flow may be different for two cab variants. This will result in a difference in the drag delta between so-called open-road conditions and the wind tunnel. This makes it more difficult to evaluate the performance of two different test objects when they are both tested in a wind tunnel and simulated in CFD. A numerical study where two different cab shapes were compared in both open road condition, and in a digital wind tunnel environment was performed.

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.

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.

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.

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.