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Biofuel can enable a sustainable transport solution and lower greenhouse gas emissions compared to standard fuels. This study focuses on biodiesel, implemented in the easiest way as drop in fuel. When mixing biodiesel into diesel one can run into problems with solubility causing contaminants precipitating out as insolubilities. These insolubilities, also called soft particles, can cause problems such as internal injector deposits and nozzle fouling. One way to overcome the problem of soft particles is by filtration. It is thus of great interest to be able to quantify fuel filters’ ability to intercept soft particles. The aim of this study is to test different fuel filters for heavy-duty engines and their ability to filter out synthetic soft particles. A custom-built fuel filter rig is presented, together with some of its general design requirements. For evaluation of the efficiency of the filters, fuel samples were taken before and after the filters.

Increasingly stringent emission legislation as well as increased demand on fuel efficiency calls for further research and development in the diesel engine field. Spray formation, evaporation and ignition delay are important factors that influence the combustion and emission formation processes in a diesel engine. Increased understanding of the mixture formation process is valuable in the development of low emission, high efficiency diesel engines. In this paper spray formation and ignition under real engine conditions have been studied in an optical engine capable of running close to full load for a real HD diesel engine. Powerful external lights were used to provide the required light intensity for high speed camera images in the combustion chamber prior to ignition. A specially developed software was used for spray edge detection and tracking. The software provides crank angle resolved spray penetration data.

Renewable fuels have an important role to create sustainable energy systems. In this paper the focus is on biodiesel, which is produced from vegetable oils or animal fats. Today biodiesel is mostly used as a drop-in fuel, mixed into conventional diesel fuels to reduce their environmental impact. Low quality drop-in fuel can lead to deposits throughout the fuel systems of heavy duty vehicles. In a previous study fuel filters from the field were collected and analyzed with the objective to determine the main components responsible for fuel filter plugging. The identified compounds were constituents of soft particles. In the current study, the focus was on metal carboxylates since these have been found to be one of the components of the soft particles and associated with other engine malfunctions as well. Hence the measurement of metal carboxylates in the fuel is important for future studies regarding the fuel’s effect on engines.

Knowing the tire pressure during driving is essential since it affects multiple tire properties such as rolling resistance, uneven wear, and how prone the tire is to tire bursts. Tire temperature and cavity pressure are closely tied to each other; a change in tire temperature will cause an alteration in tire cavity pressure. This article gives insights into which tire temperature measurement position is representative enough to estimate pressure changes inside the tire, and whether the pressure changes can be assumed to be nearly isochoric. Climate wind tunnel and road measurements were conducted where tire pressure and temperature at the tire inner liner, the tire shoulder, and the tread surface were monitored. The measurements show that tires do not have a uniform temperature distribution. The ideal gas law is used to estimate the tire pressure from the measured temperatures.

This paper investigates the FPGA resources for the implementation of in-cycle closed-loop combustion control algorithms. Closed-loop combustion control obtains feedback from fast in-cylinder pressure measurements for accurate and reliable information about the combustion progress, synchronized with the flywheel encoder. In-cycle combustion control requires accurate and fast computations for their real-time execution. A compromise between accuracy and computation complexity must be selected for an effective combustion control. The requirements on the signal processing (evaluation rate and digital resolution) are investigated. A common practice for the combustion supervision is to monitor the heat release rate. For its calculation, different methods for the computation of the cylinder volume and heat capacity ratio are compared. Combustion feedback requires of virtual sensors for the misfire detection, burnt fuel mass and pressure prediction.

In order to mitigate the effect of fossil fuels on global warming, biodiesel is used as drop in fuel. However, in the mixture of biodiesel and diesel, soft particles may form. These soft particles are organic compounds, which can originate from the production and degradation of biodiesel. Further when fuel is mixed with unwanted contaminants such as engine oil the amount soft particles can increase. The presence of these particles can cause malfunction in the fuel system of the engine, such as nozzle fouling, internal diesel injector deposits (IDID) or fuel filter plugging. Soft particles and the mechanism of their formation is curtail to understand in order to study and prevent their effects on the fuel system. This paper focuses on one type of soft particles, which are metal soaps. More precisely on the role of the short chain fatty acids (SCFA) during their formation. In order to do so, aged and unaged B10 was studied.

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.

Typically, the combustion in an internal combustion engine is open-loop controlled. The introduction of a cylinder pressure sensor opens the possibility to introduce a virtual combustion sensor. This virtual sensor is a possible enabler for closed-loop combustion control and thus the possibility to counteract the effects of engine part to part variation, component ageing and fuel quality diversity. The extent to which these effects can be counteracted is determined by the detection limits of the virtual combustion sensor. To determine the limitation of the virtual combustion sensor, a virtual combustion sensor system was implemented based on a one-zone heat-release analysis, including the signal processing of the pressure sensor input. The typical error sources in a heavy-duty engine were identified and quantified. The virtual combustion sensor system was presented with flawed signals and the sensor’s sensitivities to the errors were quantified.

Increasing demands for more efficient engines and stricter legislations on exhaust emissions require more accurate control of the engine operating parameters. Engine control is based on sensors monitoring the condition of the engine. Numerous sensors, in a complex control context, increase the complexity, the fragility and the cost of the system. An alternative to physical sensors are virtual sensors, observers used to monitor parameters of the engine thus reducing both the fragility and the production cost but with a slight increase of the complexity. In the current paper a virtual intake manifold cylinder port pressure sensor is presented. The virtual sensor is based on a compressible flow model and on the pressure signal of the intake manifold pressure sensor. It uses the linearized pressure coefficient approach to keep vital performance behaviors while still conserving calibration effort and embedded system memory.

The combustion in a direct injected internal combustion engine is normally open-loop controlled. The introduction of cylinder pressure sensors enables a virtual combustion sensor which in turn enables closed-loop combustion control, and the possibility to counteract effects such as engine part-to-part variation, component ageing and fuel quality diversity. Closed-loop combustion control requires precise, robust and preferably cheap sensors. This paper presents an investigation of the robustness and the limitation of a knock sensor based virtual combustion sensor. This virtual combustion sensor utilize the common heat release analysis using a knock sensor based virtual cylinder pressure signal. Major virtual sensor error sources in a heavy-duty engine were identified as: the specific heat ratio model, the boost pressure and the crank angle phasing. The virtual sensor errors were quantified in relation to both the measured cylinder pressure and the total virtual sensor error.

Typically the combustion in a direct injected compression ignited internal combustion engine is open-loop controlled. The introduction of a cylinder pressure sensor opens up the possibility of a virtual combustion sensor which could enable closed-loop combustion control and thus the potential to counteract effects such as engine part to part variation, component ageing and fuel quality diversity. Closed-loop combustion control requires precise, robust and preferably cheap sensors. This paper presents a virtual cylinder pressure sensor based on the signal from the inexpensive but well proven knock sensor. The method used to convert the knock sensor signal into a pressure estimate included the stages: Phase correcting the raw signal, Filtering the raw signal, Scaling the signal to known thermodynamic laws and provided engine sensors signals and Reconstructing parts of the signal with other known models and assumptions.

Noise encapsulations are widely used in automotive industry to enclose noise sources, such as e.g. the engine or the gearbox, to reduce externally radiated noise. The sound absorption factor of the material on the inside of the noise encapsulation is obviously vital for the sound attenuation. This parameter is in most cases determined experimentally for which there are several methods. The results received from the various methods may vary as different acoustic states are examined and thus influence the choice of method. The absorption factor is crucial since it is used in specifications to material manufacturers as well as being an input parameter in modeling the performance of the noise shield e.g. during a pass-by noise test. In this paper, two standardized measurement methods along with a third, non-standardized method, are applied to determine the properties of an absorbing material used in a commercial noise encapsulation.

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 upcoming European legislation for heavy duty vehicles, EuVI, includes rules on monitoring of urea consumption and urea tank volume. These new rules put new demands on the level sensing system monitoring the urea tank. The normal vehicle mounted liquid level sensing system today consists of a single, more or less vertically placed, sensor. When the vehicle is tilted the level of the fluid at the sensor position normally changes. This results in a measurement error in the calculated volume, as the volume is calculated based only on the information from the level sensor. The presented modeling studies investigate the feasibility of using sensor fusion to improve the accuracy of liquid volume estimation on a heavy duty truck. In the first study, the signals from multiple level sensors located in various liquid containing tanks on the truck are fused.

Improving turbocharger performance to increase engine efficiency has the potential to help meet current and upcoming exhaust legislation. One limiting factor is compressor surge, an air flow instability phenomenon capable of causing severe vibration and noise. To avoid surge, the turbocharger is operated with a safety margin (surge margin) which, as well as avoiding surge in steady state operation, unfortunately also lowers engine performance. This paper investigates the possibility of detecting compressor surge with a conventional engine knock sensor. It further recommends a surge detection algorithm based on their signals during transient engine operation. Three knock sensors were mounted on the turbocharger and placed along the axes of three dimensions of movement. The engine was operated in load steps starting from steady state. The steady state points of operation covered the vital parts of the engine speed and load range.