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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.

In the automotive industry, the piezo-based in-cylinder pressure sensor is getting commercialized and used in production vehicles. For example, the pressure sensor offers the opportunity to design algorithms for estimation of engine emissions, such as soot and NO , during a combustion cycle. In this paper a zero-dimensional NO model for a diesel engine is implemented that will be used in real time. The model is based on the thermal NO formation and the Zeldovich mechanism using two non-geometrical zones: burned and unburned zone. The influence of EGR on combustion temperature was modeled using a well-known thermodynamic identity where specific heat at constant pressure is included. Specific heat will vary with temperature and the gas composition. The model was implemented in LabVIEW using tools specific for an FPGA (Field-Programmable Gate Array).

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 make efficient use of a Diesel engine equipped with an SCR system, it's important to have a complete system approach when it comes to calibration of the engine and the aftertreatment system. This paper presents a complete model of a heavy duty diesel engine equipped with a vanadia based SCR system. The diesel engine uses common rail fuel injection, a variable geometry turbocharger (VGT) and cooled EGR. The engine model consists of a quasi steady gas exchange model combined with a two-zone zero dimensional combustion model. The combustion model is a predictive heat release model. Using the calculated zone temperatures, the corresponding NOx concentration is given by the original Zeldovich mechanism. The SCR catalyst model is of the state space type. The basic model structure is a series of continuously stirred tank reactors and the catalyst walls are discretized to describe mass transport inside the porous structure.

Achieving upcoming HD emissions legislation, Euro VI/EPA 10, is a challenge for all engine manufacturers. A likely solution to meet the NOx limit is to use a combination of EGR and SCR. Combining these two technologies poses new challenges and possibilities when it comes to optimization and calibration. Using a complete system approach, i.e., considering the engine and the aftertreatment system as a single unit, is important in order to achieve good performance. Optimizing the complete system is a tedious task; first there are a large number of variables which affect both emissions and fuel consumption (injection timing, EGR rate, urea dosing, injection pressure, pilot/post injections, for example). Secondly, the chemical reactions in the SCR catalyst are substantially slower than the dynamics of the diesel engine and the rest of the system, making the optimization problem time dependent.

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.

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.

With stricter emission legislations and demands on low fuel consumption, new engine technologies are continuously investigated. At the same time the accuracy in the over all engine control and diagnosis and hence also the required estimation accuracy is tightened. Central for the internal combustion control is the trapped cylinder charge and composition Traditionally cylinder charge is estimated using mean intake manifold pressure and engine speed in a two dimensional lookup table. With the introduction of variable valve timing, two additional degrees of freedom are introduced that makes this approach very time consuming and therefore expensive. Especially if the cam phasers are given large enough authority to offer powerful thermal management possibilities. The paper presents a physical model for estimating in-cylinder trapped mass and residual gas fraction utilizing cylinder pressure measurements, and intake and exhaust valve lift profiles.

Modern vehicles use Electronic Control Units (ECU), connected via Controller Area Network (CAN) to perform functions. Many of these functions are distributed across several ECUs. This network interconnection enables the sharing of sensors, calculated information and actuators. As new functionality is added, the number of ECUs and their complexity increase. This paper describes the values and possibilities of a Hardware-In-the-Loop (HIL) based Integration Lab, which enables a wide range of automatic tests to be performed on networked ECUs. The Integration Lab is the complex rebuild of a Scania truck/bus, containing the ECU superset, for connecting and testing networked ECUs. It involves more than 30 ECUs and eleven CAN networks.

Heavy trucks contribute significantly to the overall air pollution, especially NOx and PM emissions. Models to predict the emissions from heavy trucks in real world on road conditions are therefore of great interest. Most such models are based on data achieved from stationary measurements, i.e. engine maps. This type of “quasi stationary” models could also be of interest in other applications where emission models of low complexity are desired, such as engine control and simulation and control of exhaust aftertreatment systems. In this paper, results from quasi stationary calculations of fuel consumption, CO, HC, NOx and PM emissions are compared with time resolved measurements of the corresponding quantities. Measurement data from three Euro 3-class engines is used. The differences are discussed in terms of the conditions during transients and correction models for quasi stationary calculations are presented. Simply using engine maps without transient correction is not sufficient.

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.

Global warming and climate change have led to a greater interest in the implementation of biofuels in internal combustion engines. In spark ignited engines, biofuels have been shown to improve efficiency and knock resistance while decreasing emissions of unburned hydrocarbons, carbon monoxide and particles. This study investigates the effect of biofuels on SI engine combustion through a graphical compilation of previously reported results. Experimental data from 88 articles were used to evaluate the trends of the addition of different biofuels in gasoline. Graphs illustrating engine performance, combustion phasing and emissions are presented in conjunction with data on the physiochemical properties of each biofuel component to understand the observed trends. Internal combustion engines have the ability to handle a wide variety of fuels resulting in a broad range of biofuel candidates.

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.

With increasing demands to reduce fuel consumption and CO2 emissions, it is necessary to recover waste heat from modern Heavy Duty (HD) truck engines. Organic Rankine Cycle (ORC) has been acknowledged as one of the most effective systems for Waste Heat Recovery (WHR) due to its simplicity, reliability and improved overall efficiency. The expander and working fluid used in ORC WHR greatly impact the overall performance of an integrated engine and WHR system. This paper presents the effects of volumetric expanders on the ORC WHR system of a long haulage HD truck engine at a steady-state engine operating point chosen from a real-time road data. Performance of a long haulage HD truck engine is analyzed, based on the choice of three volumetric expanders for its WHR system, using their actual performance values. The expanders are: an oil-free open-drive scroll, a hermetic scroll and an axial piston expander with working fluids R123, R245fa and ethanol, respectively.

The formation of deposits in the fuel systems of heavy-duty engines, using drop-in fuels, has been reported in recent years. Drop-in fuels are of interest because they allow higher levels of alternative fuels to be blended with conventional fuels that are compatible with today’s engines. The precipitation of insolubles in the drop-in fuel can lead to clogging of fuel filters and internal injector deposits, resulting in increased fuel consumption and engine drivability problems. The possible mechanisms for the formation of the deposits in the fuel system are not yet fully understood. Several explanations such as operating conditions, fuel quality and contamination have been reported. To investigate injector deposit formation, several screening laboratory test methods have been developed to avoid the use of more costly and complex engine testing.

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.