Search Results

A potential route to reduce CO2 emissions from heavy-duty trucks is to combine low-carbon fuels and a hybrid-electric powertrain to maximize overall efficiency. A hybrid electric powertrain can reduce the peak power required from the internal combustion engine, leading to opportunities to reduce the engine size but still meet vehicle performance requirements. Although engine downsizing in the light-duty sector can offer significant fuel economy savings mainly due to increased part-load efficiency, its benefits and downsides in heavy-duty engines are less clear. As there has been limited published research in this area to date, there is a lack of a standardized engine downsizing procedure.

The development and calibration of modern combustion engines is challenging in the area of continuously tightening emission limits and the necessity for meeting real driving emissions regulations. A focus is on the knowledge of the internal engine processes and the determination of pollutants formations in order to predict the engine emissions. A physical model-based development provides an insight into hardly measurable phenomena properties and is robust against changing input data. With increasing modeling depth the required computing capacities increase. As an alternative to physical modeling, data-driven machine learning methods can be used to enable high-performance modeling accuracy. However, these are dependent on the learned data. To combine the performance and robustness of both types of modeling a hybrid application of data-driven and physical models is developed in this paper as a grey box model for the exhaust emission prediction of a commercial vehicle diesel engine.

This paper investigates an optimal design of a diesel engine and after-treatment systems for a series hybrid electric forklift application. A holistic modeling approach is developed in GT-Suite® to establish a model-based hardware definition for a diesel engine and an after-treatment system to accurately predict engine performance and emissions. The used engine model is validated with the experimental data. The engine design parameters including compression ratio, boost level, air-fuel ratio (AFR), injection timing, and injection pressure are optimized at a single operating point for the series hybrid electric vehicle, together with the performance of the after-treatment components. The engine and after-treatment models are then coupled with a series hybrid electric powertrain to evaluate the performance of the forklift in the standard VDI 2198 drive cycle.

The effects of Variable Valve Timing (VVT) on Homogeneous Charge Compression Ignition (HCCI) engine energy distribution and waste heat recovery are investigated using a fully flexible Electromagnetic Variable Valve Timing (EVVT) system. The experiment is carried out in a single cylinder, 657 cc, port fuel injection engine fueled with n-heptane. Exergy analysis is performed to understand the relative contribution of different loss mechanisms in HCCI engines and how VVT changes these contributions. It is found that HCCI engine brake thermal efficiency, the Combined Heat and Power (CHP) power to heat ratio, the first and the second law efficiencies are improved with proper valve timing. Further analysis is performed by applying the first and second law of thermodynamics to compare HCCI energy and exergy distribution to Spark Ignition (SI) combustion using Primary Reference Fuel (PRF). HCCI demonstrates higher fuel efficiency and power to heat and energy loss ratios compared to SI.

The foremost aim of the work presented in this paper is to improve fuel economy and decrease CO2 emissions by reducing the aerodynamic drag of passenger vehicles. In vehicle development, computer aided engineering (CAE) methods have become a development driver tool rather than a design assessment tool. Exploring and developing the capabilities of current CAE tools is therefore of great importance. An efficient method for vehicle shape optimization has been developed using recent years' advancements in neural networks and evolutionary optimization. The proposed method requires the definition of design variables as the only manual work. The optimization is performed on a solver approximation instead of the real solver, which considerably reduces computation time. A database is generated from simulations of sampled configurations within the pre-defined design space. The database is used to train an artificial neural network which acts as an approximation to the simulations.

This paper presents measurements on Vehicle to Vehicle (V2V) communication between participants in a platooning application. Platooning, according to the SARTRE concept, implies several vehicles travelling together in tight formation, with a manually driven heavy lead vehicle. The platoon being studied consists of five vehicles; two trucks in the lead and three passenger cars. The V2V-communication node in each vehicle contains an 802.11p radio at 5,9 GHz. It is used to send messages between vehicles to coordinate movements and maintain safety in the platoon. Another cooperative application that relies on V2V-communication is multiple UAVs flying in formation; as investigated in KARYON. This project also investigates cooperative autonomous vehicles. In both applications, V2V-communication is an enabling technology. Two metrics are studied to quantify the V2V-communication quality: system packet error rate and consecutive packet loss.

There are a number of numerical and experimental studies of the aerodynamic performance of wheels that have been published. They show that wheels and wheel-housing flows are responsible for a substantial part of the total aerodynamic drag on passenger vehicles. Previous investigations have also shown that aerodynamic resistance moment acting on rotating wheels, sometimes referred to as ventilation resistance or ventilation torque is a significant contributor to the total aerodynamic resistance of the vehicle; therefore it should not be neglected when designing the wheel-housing area. This work presents a numerical study of the wheel ventilation resistance moment and factors that affect it, using computational fluid dynamics (CFD). It is demonstrated how pressure and shear forces acting on different rotating parts of the wheel affect the ventilation torque. It is also shown how a simple change of rim design can lead to a significant decrease in power consumption of the vehicle.

Under a global impulse for less man-made emissions, the automotive manufacturers search for innovative methods to reduce the fuel consumption and hence the CO2-emissions. Aerodynamics has great potential to aid the emission reduction since aerodynamic drag is an important parameter in the overall driving resistance force. As vehicles are considered bluff bodies, the main drag source is pressure drag, caused by the difference between front and rear pressure. Therefore increasing the base pressure is a key parameter to reduce the aerodynamic drag. From previous research on small-scale and full-scale vehicles, rear-end extensions are known to have a positive effect on the base pressure, enhancing pressure recovery and reducing the wake area. This paper investigates the effect of several parameters of these extensions on the forces, on the surface pressures of an SUV in the Volvo Cars Aerodynamic Wind Tunnel and compares them with numerical results.

Gasoline direct injection engines can greatly improve the fuel economy, but the idea mixture distribution cannot be easily controlled. In this paper, the linearized instability sheet atomization (LISA) and large eddy simulation (LES) implemented into KIVA-3V code were used to study the gasoline hollow cone spray process for gasoline direct injection (GDI) in a constant volume vessel. The three-dimensional results show that the LISA model can effectively simulate the gasoline hollow cone spray and obtain the string structure compared to the experiment data. And the velocity interpolation method can reduce the grid dependency of spray simulation. Using dense grid (about 8 million cells) in LES and RANS all can obtain the good spray tip penetration and width. Unlike diesel spray, for gasoline spray there are not big difference between the results using LES and RANS. In additional the ambient pressure significantly influence the gasoline spray shape.

In this work, large eddy simulation (LES) with a K-equation subgrid turbulent kinetic energy model is implemented into the CFD code KIVA3V to study the features of liquid fuel spray and combustion using gradually varying grid in a constant volume chamber. The characteristic time-scale combustion model (CTC) incorporating a turbulent timescale is adopted to predict the combustion process and the SHELL auto-ignition model is used to predict auto-ignition. Combustion is also simulated using Parallel Detailed Chemistry with Lu's n-heptane reduced mechanism (58 species), which has been added into the KIVA3V-LES code. The computational results are compared with Sandia experimental data for non-reacting and reacting cases. As a result, LES can capture the complex structure of the spray and temperature distribution as well as the trend of ignition delay and flame lift-off length variations. Better results are obtained using the Parallel Detailed Chemistry than the CTC model.

This paper presents a large eddy simulation study of the liquid spray mixing with hot ambient gas in a constant volume vessel under engine-like conditions with the injection pressure of 1500 bar, ambient density 22.8 kg/m₃, ambient temperature of 900 K and an injector nozzle of 0.09 mm. The simulation results are compared with the experiments carried out by Pickett et al., under similar conditions. Under modern direct injection diesel engine conditions, it has been argued that the liquid core region is small and the droplets after atomization are fine so that the process of spray evaporation and mixing with the air is controlled by the heat and mass transfer between the ambient hot gas and central fuel flow. To examine this hypothesis a simple spray breakup model is tested in the present LES simulation. The simulations are performed using an open source compressible flow solver, in OpenFOAM.

In the early stages of an aerodynamic development programme of a road vehicle it is common to use wind tunnel scale models. The obvious reasons for using scale models are that they are less costly to build and model scale wind tunnels are relatively inexpensive to operate. It is therefore desirable for model scale testing to be utilized even more than it is today. This however, requires that the scale models are highly detailed and that the results correlate with those of the full size vehicle. This paper presents a correlation study that was carried out in the Chalmers and Volvo Car Aerodynamic Wind Tunnels. The aim of the study was to investigate how successfully a correlation of the cooling air flow between a detailed scale model and a real full size vehicle could be achieved. Results show limited correlation on absolute global aerodynamic loads, but relative good correlation in drag and lift increments.

Automotive wind tunnel testing is a key element in the development of the aerodynamics of road vehicles. Continuous advancements are made in order to decrease the differences between actual on-road conditions and wind tunnel test properties and the importance of ground simulation with relative motion of the ground and rotating wheels has been the topic of several studies. This work presents a study on the effect of active ground simulation, using moving ground and rotating wheels, on the aerodynamic coefficients on a passenger car in yawed conditions. Most of the published studies on the effects of ground simulation cover only zero yaw conditions and only a few earlier investigations covering ground simulation during yaw were found in the existing literature and all considered simplified models. To further investigate this, a study on a full size sedan type vehicle of production status was performed in the Volvo Aerodynamic Wind Tunnel.

This study focus on the aerodynamic influence of the engine bay packaging, with special emphasis on the density of packaging and its effect on cooling and exterior flow. For the study, numerical and experimental methods where combined to exploit the advantages of each method. The geometry used for the study was a model of Volvo S60 sedan type passenger car, carrying a detailed representation of the cooling package, engine bay and underbody area. In the study it was found that there is an influence on the exterior aerodynamics of the vehicle with respect to the packaging of the engine bay. Furthermore, it is shown that by evacuating a large amount of the cooling air through the wheel houses a reduction in drag can be achieved.

Natural gas is a challenging fuel for HCCI engines because its single-stage ignition and rapid combustion make it difficult to optimize combustion timing over a significant load range. This study investigates direct injection of a pilot quantity of high-cetane fuel near TDC as a range extension and combustion control mechanism for natural gas HCCI engines. The EGR and load range is studied in a supercharged natural gas HCCI engine equipped with external EGR, intake heating and a direct injection system for n-heptane pilot fuel. The operating range and emissions are of primary interest and are compared between both the baseline HCCI engine with variable intake temperature and the direct injected HCCI (DI-HCCI) engine with constant intake temperature. Test results show the EGR and load range at fixed intake temperature can be extended using pilot direct injection.

A physics-based control-oriented model is developed to dynamically predict cycle-to-cycle combustion timing in transient fueling conditions for Homogeneous Charge Compression Ignition (HCCI) engines. The model simulates the engine cycle from the intake stroke to the exhaust stroke and includes the thermal coupling dynamics caused by the residual gases from one cycle to the next cycle. A residual gas model, a modified knock integral model, a fuel burn rate model, and thermodynamic models for the gas state in combustion and exhaust strokes are incorporated to simulate the engine cycle. The gas exchange process, generated work and completeness of combustion are predicted using semi-empirical correlations. The resulting model is parameterized for the combustion of Primary Reference Fuel (PRF) blends using 5703 simulations from a detailed thermo-kinetic model. Semi-empirical correlations in the model are parameterized using the experimental data obtained from a single-cylinder engine.

The paper describes a novel method for calculating the residual gas fraction and the trapping efficiency in a 2 stroke engine. Assuming one dimensional compressible flow through the inlet and exhaust ports, the method estimates the instantaneous mass flowing in and out from the combustion chamber; later the residual gas fraction and trapping efficiency are estimated combining together the perfect displacement and perfect mixing scavenging models. It is assumed that when the intake port opens, the fresh mixture is pushing out the burned charge without any mixing and after a multiple of the time needed for the largest eddy to perform one rotation, the two gasses are instantly mixed up together and expelled. The result is a very simple algorithm that does not require much computational time and is able to estimate with high level of precision the trapping efficiency and the residual gas fraction in 2 stroke engines.

It has been known from multi-zone simulations that HCCI combustion can be significantly affected by temperature stratification of the in-cylinder gas. With the same combustion timing (i.e. crank angles at 50% heat release, denoted as CA50), large temperature stratification tends to prolong the combustion duration and lower down the in-cylinder pressure-rise-rate. With low pressure-rise-rate HCCI engines can be operated at high load, therefore it is of practical importance to look into more details about how temperature stratification affects the auto-ignition process. It has been realized that multi-zone simulations can not account for the effects of spatial structures of the stratified temperature field, i.e. how the size of the hot and cold spots in the temperature field could affect the auto-ignition process. This question is investigated in the present work by large eddy simulation (LES) method which is capable of resolving the in-cylinder turbulence field in space and time.

Nowadays for small-scale power generation there are electrochemical batteries and mini engines. Many efforts have been done for improving the power density of the batteries but unfortunately the value of 1 MJ/kg seems to be asymptotic. If the energy source is an organic fuel which has an energy density of around 29 MJ/kg with a minimum overall efficiency of only 3.5%, this device would surpass the batteries. This paper is the fifth of a series of publications aimed to study the HCCI combustion process in the milli domain at high engine speed in order to design and develop VIMPA, Vibrating Microengine for Low Power Generation and Microsystems Actuation. Previous studies ranged from general characterization of the HCCI combustion process by using metal and optical engines, to more specific topics for instance the influence of the boundary layer and quenching distance on the quality of the combustion.

Although HCCI engines promise low NOx emissions with high efficiency, they suffer from a narrow operating range between knock and misfire because they lack a direct means of controlling combustion timing. A series of previous studies showed that reformer gas, (RG, defined as a mixture of light gases dominated by hydrogen and carbon monoxide), can be used to control combustion timing without changing mixture dilution, (λ or EGR) which control engine load. The effect of RG blending on combustion timing was found to be mainly related to the difference in auto-ignition characteristics between the RG and base fuel. The practical effectiveness of RG depends on local production using a fuel processor that consumes the same base fuel as the engine and efficiently produces high-hydrogen RG as a blending additive.