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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.

Modern spark-ignited (SI) engines offer excellent emission reduction when operated with a stoichiometric mixture and a three-way catalytic converter. A challenge with stoichiometric compared to diluted operation is the knock propensity due to the high reactivity of the mixture. This limits the compression ratio, thus reducing engine efficiency and increasing exhaust temperature. The current work evaluated a model of conditions at inlet valve closing (IVC) and top dead center (TDC) for steady state operation. The IVC temperature model is achieved by a cycle-to-cycle resolved residual gas fraction estimator. Due to the potential charge cooling effect from methanol, a method was proposed to determine the fraction of fuel sourced from a wall film. Determining the level of charge cooling is important as it heavily impacts the IVC and TDC temperatures.

An afterburner-assisted turbocharged single-cylinder 425 cc two-stroke SI-engine is described in this simulation study. This engine is intended as a Backup Range Extender (REX) application for heavy-duty battery electric vehicles (BEV) when external electric charging is unavailable. The 425 cc engine is an upscaled version of a 125 cc port-injected engine [26] which demonstrated that the selected technology could provide a specific power level of 400 kW/L and the desired 150 kW in a heavy duty BEV application. The 425 cc single cylinder two-stroke engine is an existing engine as one half of a 850 cc snowmobile engine. This simulation study includes upscaling of the swept volume, impact on engine speed and gas exchange properties. In the same way as for the 125cc engine [26], the exhaust gases reaches the turbine through a tuned exhaust pipe and an afterburner or oxidation catalyst.

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.

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.

Adaptation of predictive combustion models for their use in in-cycle closed-loop combustion control of a multi-cylinder engine is studied in this article. Closed-loop combustion control can adjust the operation of the engine closer to the optimal point despite production tolerances, component variations, normal disturbances, ageing or fuel type. In the fastest loop, in-cycle closed-loop combustion control was proved to reduce normal variations around the operational point to increase the efficiency. However, these algorithms require highly accurate predictive models, whilst having low complexity for their implementation. Three models were used to exemplify the proposed adaptation methods: the pilot injection’s ignition delay, the pilot burned mass, and the main injection’s ignition delay. Different approaches for the adaptation of the models are studied to obtain the demanded accuracy under the implementation constraints.

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.

The global demand for decreased emission from engines and increased efficiency drives manufactures to develop more advanced fuel injection systems. Today's compression-ignited engines use common rail systems with high injection pressures and fuel injector nozzles with small orifice diameters. These systems are highly sensitive to small changes in orifice diameters since these could lead to deteriorations in spray characteristics, thus reducing engine performance and increasing emissions. Phenomena that could create problems include nozzle fouling caused by metal carboxylates or biofuels. The problems increase with extended use of biofuels. This paper reports on an experimental study of nozzle hole fouling performed on a single-cylinder engine. The aim was to identify if the solubility of the fuel has an effect on deposit build-up and, thus, the reduction in fuelling with associated torque loss, and if there is a probability of regenerating the contaminated injectors.

Fuel filters serve as a safety belt for modern compression ignition engines. To meet the requirements from environmental regulations these engines use the common rail injection system, which is highly susceptible to contamination from the fuel. Furthermore, the public awareness towards global warming is raising the need for renewable fuels such as biodiesel. An increased fuel variety brings a higher requirement for fuel filters as well. To better understand the process of filtration, awareness of the different possible contaminants from the field is needed. This study used several chemical characterization techniques to examine the deposits from plugged fuel filters collected from the field. The vehicle was run with a biodiesel blend available on the market.

Ducted fuel injection (DFI) has been shown to be an effective method to significantly reduce soot formation in mixing controlled compression ignition (MCCI) diesel combustion. This reduction has been demonstrated in both combustion vessels and in an optical engine. The mechanisms driving the soot reduction are to date not fully understood. Optimal duct configurations are also not immediately evident. The objective of this study is to show the effects of two geometric variables, namely distance from fuel injector orifice exit to duct inlet (0.1-6 mm) for a 2x14 mm duct, and duct length variation (8-14 mm) at a given stand-off distance of 0.1 mm. A 138 μm on-axis single-orifice injector operated at 100-250 MPa was used in a heated, continuous flow, constant pressure vessel with optical access.

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.

Clean combustion is one of the inherent benefits of using a high methane content fuel, natural gas or biogas. A single carbon atom in the fuel molecule results, to a large extent, in particle-free combustion. This is due to the high energy required for binding multiple carbon atoms together during the combustion process, required to form soot particles. When scaling up this process and applying it in the internal combustion engine, the resulting emissions from the engine have not been observed to be as particle free as the theory on methane combustion indicates. These particles stem from the combustion of engine oil and its ash content. One common practice has been to lower the ash content to regulate the particulate emissions, as was done for diesel engines. For a gas engine, this approach has been difficult to apply, as the piston and valvetrain lubrication becomes insufficient.

With the rapid development of artificial intelligence, autonomous driving technology will finally reshape an automotive industry. Although fully autonomous cars are not commercially available to common consumers at this stage, partially autonomous vehicles, which are defined as level 2 and level 3 autonomous vehicles by SAE J3016 standard, are widely tested by automakers and researchers. A typical Human-Machine-Interface (HMI) for a vehicle takes a form to support a human domination role. Although modern driving assistance systems allow vehicles to take over control at certain scenarios, the typical human-machine-interface has not changed dramatically for a long time. With deep learning neural network technologies penetrating into automotive applications, multi-modal communications between a driver and a vehicle can be enabled by a cost-effective solution.

Troubleshooting trees are traditionally used to guide technicians through the process of identifying the cause of vehicle problems and solving them. These static trees can successfully visualize complex information. However, for modular vehicles, the trees become difficult to create and maintain due to the numerous different configurations of vehicles that can be constructed. These issues can be overcome by using a model-based approach. This paper describes a prototype tool for guided troubleshooting and shows its application to a selective catalytic reduction system used in many heavy vehicles. The troubleshooting tool guides the technician through the troubleshooting process by presenting the most likely fault candidates and recommending the most useful actions to perform. The list of candidates and recommendations are updated continuously to reflect the outcomes of past actions.

This paper presents a simulation environment and methodology for noise and vibration analyses of a driven rear axle in a bus application, with particular focus on medium to high frequency range (400 Hz to 3 kHz). The workflow demonstrates structure borne noise and sound radiation analyses. The fully flexible Multi-Body Dynamics (MBD) model - serving to cover the actual mechanical excitation mechanisms and the structural domain - includes geometrical contacts of hypoid gear in the central gear and planetary gear integrated at hubs, considering non-linear meshing stiffness. Contribution of aforementioned gear stages, as well as the propeller shaft universal joint at the pinion axle, on overall axle noise levels is investigated by means of sensitivity analysis. Based on the surface velocities computed at the vibrating axle-housing structure the Wave Based Technique (WBT) is employed to solve the airborne noise problem and predict the radiated sound.

The automotive industry is dramatically changing. Many automotive Original Equipment Manufacturers (OEMs) proposed new prototype models or concept vehicles to promote a green vehicle image. Non-traditional players bring many latest technologies in the Information Technology (IT) industry to the automotive industry. Typical vehicle’s characteristics became wider compared to those of vehicles a decade ago, and they include not only a driving range, mileage per gallon and acceleration rating, but also many features adopted in the IT industry, such as usability, connectivity, vehicle software upgrade capability and backward compatibility. Consumers expect the latest technology features in vehicles as they enjoy in using digital applications in laptops and mobile phones. These features create a huge challenge for a design of a new vehicle, especially for a human-machine-interface (HMI) system.

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.

In this paper, residual stress distributions in rectangular bars due to rolling or burnishing at very high rolling or burnishing loads are investigated by roll burnishing experiments and three-dimensional finite element analyses using ABAQUS. First, roll burnishing experiments on rectangular bars at two roller burnishing loads are presented. The results indicate the higher burnishing load induces lower residual stresses and the higher burnishing load does not improve fatigue lives. Next, in the corresponding finite element analyses, the roller is modeled as rigid and the roller rolls on the flat surface of the bar with a low coefficient of friction. The bar material is modeled as an elastic-plastic strain hardening material with a nonlinear kinematic hardening rule for loading and unloading.

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.