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The current work investigates a method in 1D modeling of cooling systems including discretized cooling package with non-uniform boundary conditions. In a stacked cooling package the heat transfer through each heat exchanger depends on the mass flows and temperature fields. These are a result of complex three-dimensional phenomena, which take place in the under-hood and are highly non-uniform. A typical approach in 1D simulations is to assume these to be uniform, which reduces the authenticity of the simulation and calls for additional calibrations, normally done with input from test measurements. The presented work employs 3D CFD simulations of complete vehicle in STAR-CCM+ to perform a comprehensive study of mass-flow and thermal distribution over the inlet of the cooling package of a Volvo FM commercial vehicle in several steady-state operating points.

The paper presents a 2-dimensional model for the calculation of the regeneration process in a wall flow diesel particulate filter. The model includes heat transfer by conduction and convection, a model for particle combustion based on diffusive burning of individual particles, and flow through the channels and across the filter walls. It was found that only the pressure drop across the walls need be considered for normal regeneration conditions. Comparisons between model predictions and experimental results for spatial dependent temperature time histories, and integrated degree of regeneration are used to validate the model. The validations were carried out for a series of severe regenerations, where there are large changes in flow and temperature throughout the process. Relative magnitudes of energy flows due to combustion, convection, and conduction are presented, as well as parametric studies of the effects of temperature, oxygen concentration and soot loading.

The low auto-ignition temperature, rapid evaporation and high cetane number of dimethyl ether (DME) enables the use of low-pressure direct injection in compression ignition engines, thus potentially bringing the cost of the injection system down. This in turn holds the promise of bringing CI efficiency to even the smallest engines. A 50cc crankcase scavenged two-stroke CI engine was built based on moped parts. The major alterations were a new cylinder head and a 100 bar DI system using a GDI-type injector. Power is limited by carbon monoxide emission but smoke-free operation and NOx < 200ppm is achieved at all points of operation.

This paper investigates the impact of tread design on the tire-terrain interaction of two similar-sized truck tires with distinctly different tread designs running over various terrains and operating conditions using advanced computation techniques. The two truck tires used in the research are off-road tires sized 315/80R22.5 wide which were designed through Finite Element Analysis (FEA). The truck tire models were validated in static and dynamic domains using several simulation tests and measured data. The terrain includes a flooded surface and a snowed surface which were modelled using Smoothed-Particle Hydrodynamics (SPH) technique and calibrated using pressure-sinkage and direct shear tests. Both truck tire models were subjected to rolling resistance and cornering tests over the various flooded surface and snowed surface terrain conditions on the PAM-CRASH software.

The present work discusses the potential benefits of using computational fluid dynamics (CFD) simulation and artificial intelligence (AI) in the design and optimization of hydrogen internal combustion engines (H2ICEs). A Machine Learning (ML) model is developed and applied to the CFD simulation data to identify optimal injection system parameters on the Sandia H2ICE Engine to improve the mixing. This approach can aid in developing predictive ML models to guide the design of future H2ICEs. For the current engine configuration, it is observed that hydrogen (H2) gas injection contributes mixing of H2 with air. If the injector parameters are optimized, mixture preparation is better and eventually combustion. A base CFD model is validated from the Sandia H2ICE engine data against Particle Image Velocimetry (PIV) data for velocity and Planar Laser Induced Fluorescence (PLIF) data for H2 mass fraction.

In general most engine models for control applications have been constructed using regressions fitting and measured engine data. Such techniques have also been used to model the dynamic performance of engines. Unfortunately regression equation models are very complex and do not show directly the physical reality from which they emerge. This has for example made it impossible to write down explicitly the dymanic equations for, for example, the air exchange process in an SI engine in any form other than as the manifold pressure state equation. In recent a publication a Mean Value Engine Model (MVEM) has been constructed for an SI engine which is physically based and which has a simple physical form which can be immediately understood and manipulated.

Heavy-duty vehicles are primarily powered by diesel fuel, emitting CO2 emissions regardless of the exhaust after-treatment system. Contrastingly, a hydrogen engine has the potential to decarbonize the transportation sector as hydrogen is a carbon free, renewable fuel. In this study, a multi-physics 1D simulation tool (GT-Power) is used to model the gas exchange process and performance prediction of a two-stroke hydrogen engine. The aim is to establish a maximum torque-level for a four-stroke hydrogen engine and then utilize different methods for two-stroke modeling to achieve similar torque by optimizing the gas exchange process. A camless engine is used as base, enabling the flexibility to utilize approximately square valve lift profiles. The preliminary step is the GT-Power model validation, which has been done using diesel and hydrogen engines (single-cylinder heavy-duty) experiments at different operating points (871 rpm, 1200 rpm, 1259 rpm, and 1508 rpm).

In this paper, computation fluid dynamics (CFD) simulations are employed to describe the effect of flow parameters on the formation of soot and NOx in a heavy duty engine under low load and high load. The complexity of diesel combustion, specially when soot, NOx and other emissions are of interest, requires using a detailed chemical mechanism to have a correct estimation of temperature and species distribution. In this work, Multiple Representative Interactive Flamelets (MRIF) method is employed to describe the chemical reactions, ignition, flame propagation and emissions in the engine. A phenomenological model for soot formation, including soot nucleation, coagulation and oxidation with O2 and OH is incorporated into the flamelet combustion model. Different strategies for modelling NOx are chosen to take into account the longer time scale for NOx formation. The numerical results are compared with experimental data to show the validity of the model for the cases under study.

The 4th Workshop of the Engine Combustion Network (ECN) was held September 5-6, 2015 in Kyoto, Japan. This manuscript presents a summary of the progress in experiments and modeling among ECN contributors leading to a better understanding of soot formation under the ECN “Spray A” configuration and some parametric variants. Relevant published and unpublished work from prior ECN workshops is reviewed. Experiments measuring soot particle size and morphology, soot volume fraction (fv), and transient soot mass have been conducted at various international institutions providing target data for improvements to computational models. Multiple modeling contributions using both the Reynolds Averaged Navier-Stokes (RANS) Equations approach and the Large-Eddy Simulation (LES) approach have been submitted. Among these, various chemical mechanisms, soot models, and turbulence-chemistry interaction (TCI) methodologies have been considered.

The reduction of friction losses is a subject of central importance in a diesel engine. The piston frictions of low viscosity engine oil and molybdenum dialkyl dithiocarbamate (MoDTC) have been measured by floating liner method. It was found that the low viscosity engine oil lower than 5W-30 is not effective against the reduction of friction mean effective pressure (FMEP) related to the fuel consumption. MoDTC showed a good performance against the reduction of FMEP. In the friction measurement points, the reduction ratio of 10W-30 with MoDTC to 10W-30 was greater than that of 5W-30 to 10W-30.

An experimental study has been carried out on the homogeneous charge compression ignition (HCCI) combustion of Dimethyl Ether (DME). The study was performed as a parameter variation of engine speed and compression ratio on excess air ratios of approximately 2.5, 3 and 4. The compression ratio was adjusted in steps to find suitable regions of operation, and the effect of engine speed was studied at 1000, 2000 and 3000 RPM. It was found that leaner excess air ratios require higher compression ratios to achieve satisfactory combustion. Engine speed also affects operation significantly.

One of the most important operating modes for SI engines is in the idle speed region. This is because SI engines spend a large part of their time operating in this mode. Moreover, a large measure of operator satisfaction is dependent on an engine operating smoothly and reliably in and around idle. In particular the operator expects that the idle speed will remain constant in spite of the engine loads due to power steering pumps and air conditioning compressors. In the idle speed region an SI engine is thought to be quite nonlinear because the engine loading can be quite significant, thus forcing the engine to be driven through a reasonably large portion of its lower operating range. Many of the earlier studies of idle speed control systems have dealt with linearized models which in principle have limited validity for the problem at hand. In order to improve this situation, it is necessary to deal with the more general nonlinear control problem.

In earlier work it has been shown that a nearly ideal solution to the problem of accurate estimation of the air mass flow to a central fuel injection (CFI) (or throttle body (TBI)) or EFI (or multi-point (MPI)) equipped engine is provided by using a closed loop nonlinear observer for the engine. With proper design this observer was shown to be both accurate and robust with respect to modelling end measurement errors. It is based on a Constant Gain Extended Kalman Filter (CGEKF). Since the publication of this work, another type of observer has emerged in the literature for which claims of great robustness have been made. This observer is based on new developments in the area of nonlinear control theory and is called a Sliding Mode Observer (SMO). In this paper these two types of observers are compared theoretically and experimentally on an engine mounted on a dynamometer. A very aggressive driving scenario is assumed for these tests.

Side mirrors are a known source of aerodynamically generated noise in vehicles. In this work we focus on mirrors for heavy duty trucks, they are large, often not designed with main focus on aero-acoustics and are located in a cumbersome position on the up-right A-pillar of European trucks. First the test method itself is discussed. To allow fast and cost effective design loops a bespoke vehicle, where the powertrain is separated from the cab, is developed. This vehicle can be run on a standard test track. While running the tests the wind speed is monitored, any variations are then compensated for in the post processing allowing averaging over longer time periods. For the mirror tests the door of the vehicle was especially trimmed to reduce other transmission paths into the cab than the side window. Additionally other possible aeroacoustic sources were reduced as much as practically possible.

Constantly lowering emissions legislation and the fact that fuel prices have increased tremendously over recent years, have forced vehicle manufacturers to develop more and more energy-efficient vehicles. The aerodynamic drag is responsible for a substantial part of the total driving resistance for a vehicle, especially at higher velocities; thus it is important to reduce this factor as much as possible for vehicles commonly operating in these conditions. In an attempt to improve transport efficiency, longer vehicle combinations are becoming more common. By replacing some of the shorter vehicle combinations with longer combinations, the same amount of cargo can be transported with fewer vehicles; hence there is large potential for fuel savings. The knowledge of the aerodynamic properties of such vehicles is somewhat limited, and therefore interesting to study.

The novel wave-shaped bowl piston geometry design with protrusions has been proved in previous studies to enhance late-cycle mixing and therefore significantly reduce soot emissions and increase engine thermodynamic efficiency. The wave-shaped piston is characterized by the introduction of evenly spaced protrusions around the inner wall of the bowl, with a matching number with the number of injection holes, i.e., flames. The interactions between adjacent flames strongly affect the in-cylinder flow and the wave shape is designed to guide the near-wall flow. The flow re-circulation produces a radial mixing zone (RMZ) that extends towards the center of the piston bowl, where unused air is available for oxidation promotion. The waves enhance the flow re-circulation and thus increase the mixing intensity of the RMZ.

Optical engines of Bowditch design may suffer from distortion of the in-cylinder volume trace due to mechanical deformation from inertial, pressure and thermal forces. Errors in heat release calculation associated with such deformation were investigated in detail. The deformations were quantified by measuring the squish height during operation using high speed video. Deformations of all-metal engines were also estimated for comparison. The volume change caused by deformations did not change the calculated load significantly but caused errors in the heat release calculations both for optical and all metal engines. The errors at a given operating condition are smaller for all-metal engines but the importance is not necessarily smaller, since these engines normally are operated at higher loads. The errors can be eliminated by a corrected in-cylinder volume equation and a subtraction of heat release from a motored case.

One promising method for reducing fuel consumption and emissions, particularly in heavy duty trucks, is platooning. As the distance between vehicles decreases, the following vehicles will experience less aerodynamic drag on the front of the vehicle. However, reducing the velocity of the air contacting the front of the vehicle could have adverse effects on the temperature of the engine. To compensate for this effect, the energy consumption of the engine cooling system might increase, ultimately limiting the overall improvements obtained with platooning. Understanding the coupling between drag reduction and engine cooling load requirement is key for successfully implementing platooning strategies. Additionally, in a Connected and Automated Vehicle (CAV) environment, where information of the future engine load becomes available, the operation of the cooling system can be optimized in order to achieve the maximum fuel consumption reduction.

The automotive electronic architectures have moved from federated architectures, where one function is implemented in one ECU (Electronic Control Unit), to distributed architectures, where several functions may share resources on an ECU. In addition, multicore ECUs are being adopted because of better performance, cost, size, fault-tolerance and power consumption. In this paper we present an approach for the automatic software functionality assignment to multicore distributed architectures. We consider that the systems use the AUTomotive Open System ARchitecture (AUTOSAR). The functionality is modeled as a set of software components composed of subtasks, called runnables, in AUTOSAR terminology.

Many modern control strategies for engine control are based on event based sampling. Operating the control strategy in the event domain makes it possible to obtain samples at specific crank shaft angles in the engine cycle, which is often desirable for certain control strategies. One of the biggest disadvantages involved with event based strategies is signal aliasing at low engine speeds or a high computational burden at higher engine speeds. This paper presents an easy solution to the aliasing problem above. If the data between the event based samples is stored using a time based strategy, it is shown here that a subsequent treatment of the sampled data as a time series together with a suitable low pass filter structure can avoid aliasing.