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Approximately 25 % of a passenger vehicle’s aerodynamic drag comes directly or indirectly from its wheels, indicating that the rim geometry is highly relevant for increasing the vehicle’s overall energy efficiency. An extensive experimental study is presented where a parametric model of the rim design was developed, and statistical methods were employed to isolate the aerodynamic effects of certain geometric rim parameters. In addition to wind tunnel force measurements, this study employed the flowfield measurement techniques of wake surveys, wheelhouse pressure measurements, and base pressure measurements to investigate and explain the most important parameters’ effects on the flowfield. In addition, a numerical model of the vehicle with various rim geometries was developed and used to further elucidate the effects of certain geometric parameters on the flow field.

48V mild hybrid powertrains are promising technologies for cost-effective compliance with future CO2 emissions standards. Current 48V powertrains with integrated belt starter generators (P0) with downsized engines achieve CO2 emissions of 95 g/km in the NEDC. However, to reach 75 g/km, it may be necessary to combine new 48V powertrain architectures with alternative fuels. Therefore, this paper compares CO2 emissions from different 48V powertrain architectures (P0, P1, P2, P3) with different electric power levels under various driving cycles (NEDC, WLTC, and RTS95). A numerical model of a compact class passenger car with a 48V powertrain was created and experimental fuel consumption maps for engines running on different fuels (gasoline, Diesel, E85, CNG) were used to simulate its CO2 emissions. The simulation results were analysed to determine why specific powertrain combinations were more efficient under certain driving conditions.

Modelling is widely used for the development of hybrid electric vehicle (HEV) powertrain technologies, since it can provide accurate prediction of fuel consumption and CO₂ emissions, for a fraction of the resources required in experiments. For comparison of different technologies or powertrain parameters, the results should be accurate relative to each other, since powertrains are simulated under identical model details and simulation parameters. However, when CO₂ emissions of a vehicle model are simulated under a driving cycle, significant deviances may occur between actual tests and simulation results, compromising the integrity of simulations. Therefore, this paper investigates the effects of certain modelling and simulation parameters on CO₂ emission results, for a parallel HEV under three driving cycles (NEDC, WLTC and RTS95 to simulate real driving emissions (RDE)).

With progressing electrification of automotive powertrains and demands to meet increasingly stringent emission regulations, a combination of an electric motor and downsized turbocharged spark-ignited engine has been recognized as a viable solution. The SI engine must be optimized, and preferentially downsized, to reduce tailpipe CO2 and other emissions. However, drives to increase BMEP (Brake Mean Effective Pressure) and compression ratio/thermal efficiency increase propensities of knocking (auto-ignition of residual unburnt charge before the propagating flame reaches it) in downsized engines. Currently, knock is mitigated by retarding the ignition timing, but this has several limitations. Another option identified in the last decade (following trials of similar technology in aircraft combustion engines) is water injection, which suppresses knocking largely by reducing local in-cylinder mixture temperatures due to its latent heat of vaporization.

In light of the drive for energy efficiency and low CO2 emissions, extensive research is performed to reduce vehicle aerodynamic drag. The wheels are relatively shielded from the main flow compared to the exterior of the passenger car; however, they are typically responsible for around 25% of the overall vehicle drag. This contribution is large as the wheels and tyres protrude into the flow and change the flow structure around the vehicle underbody. Given that the tyre is the first part of the wheel to get in contact with the oncoming flow, its shape and features have a significant impact on the flow pattern that develops. This study aims at identifying the general effects of two main tyre features, the longitudinal rain grooves and lateral pattern grooves, using both Computational Fluid Dynamics (CFD) and wind tunnel tests. This is performed by cutting generic representations of these details into identical slick tyres.

Due to stricter emission regulations and more environmental awareness, the powertrain systems are moving toward higher fuel efficiency and lower emissions. In response to these pressing needs, new technologies have been designed and implemented by manufacturers. As a result of increasing complexity of the powertrain systems, their control and optimization become more and more challenging. Virtual powertrain calibration, also known as model-based calibration, has been introduced to transfer a part of test bench testing into a virtual environment, and hence considerably reduce time and cost of product development process while increasing the product quality. Nevertheless, virtual calibration has not yet reached its full potential in industrial applications. Volvo Penta has recently developed a virtual test cell named VIRTEC, which is used in an ongoing pilot project to meet the Stage V emission standards.

This work utilizes previously developed VSB2 (VSB2 Stochastic Blob and Bubble) multicomponent fuel spray model to study significance of using non-ideal thermodynamics for droplet evaporation under direct injection engine like operating conditions. Non-ideal thermodynamics is used to account for vapor-liquid equilibrium arising from evaporation of multicomponent fuel droplets. In specific, the evaporation of ethanol/iso-octane blend is studied in this work. Two compositions of the blend are tested, E-10 and E-85 respectively (the number denotes percentage of ethanol in blend). The VSB2 spray model is implemented into OpenFoam CFD code which is used to study evaporation of the blend in constant volume combustion vessel. Liquid and vapor penetration lengths for the E-10 case are calculated and compared with the experiment. The simulation results show reasonable agreement with the experiment. Simulation is performed with two methods- ideal and non-ideal thermodynamics respectively.

The present paper aims at developing an innovative procedure to create a one-dimensional (1D) real-time capable simulation model for a heavy-duty diesel engine. The novelty of this approach is the use of the top-level engine configuration, test cell measurement data, and manufacturer maps as opposite to common practice of utilizing a detailed 1D engine model. The objective is to facilitate effective model adjustments and hence further increase the application of Hardware-in-the-Loop (HiL) simulations in powertrain development. This work describes the development of Fast Running Model (FRM) in GT-SUITE simulation software. The cylinder and gas-path modeling and calibration are described in detail. The results for engine performance and exhaust emissions produced satisfactory agreement with both steady-state and transient experimental data.

In order to meet emissions and power requirements, modern engine design has evolved in complexity and control. The cost and time restraints of calibration and testing of various control strategies have made virtual testing environments increasingly popular. Using Hardware-in-the-Loop (HiL), Volvo Penta has built a virtual test rig named VIRTEC for efficient engine testing, using a model simulating a fully instrumented engine. This paper presents an innovative Artificial Neural Network (ANN) based model for engine simulations in HiL environment. The engine model, herein called Artificial Neural Network Engine (ANN-E), was built for D8-600 hp Volvo Penta engine, and directly implemented in the VIRTEC system. ANN-E uses a combination of feedforward and recursive ANNs, processing 7 actuator signals from the engine management system (EMS) to provide 30 output signals.

Exterior turbulent flow is an important source of automobile cabin interior noise. The turbulent flow impacts the windows of the cabins to excite the structural vibration that emits the interior noise. Meanwhile, the exterior noise generated from the turbulent flow can also cause the window vibration and generate the interior noise. Side-view mirrors mounted upstream of the windows are one of the predominant body parts inducing the turbulent flow. In this paper, we investigate the interior noise caused by a generic side-view mirror. The interior noise propagates in a cuboid cavity with a rectangular glass window. The exterior flow and the exterior noise are computed using advanced CFD methods: compressible large eddy simulation, compressible detached eddy simulation (DES), incompressible DES, and incompressible DES coupled with an acoustic wave model. The last method is used to simulate the hydrodynamic and acoustic pressure separately.

In this paper, the turbulent flow induced by a production side-view mirror assembled on a full-scale production truck is simulated using a compressible k-ω SST detached eddy simulation (DES) approach -- the improved delayed DES (IDDES). The truck configuration consists of a compartment and a trailer. Due to the large size and geometric complexity of the configuration, some simplifications are applied to the simulation. A purpose of this work is to investigate whether the simplifications are suitable to obtain the reasonable properties of the flow near the side-view mirror. Another objective is to study the aerodynamic performances of the mirror. The configuration is simplified regarding two treatments. The first treatment is to retain the key exterior components of the truck body while removing the small gaps and structures. Furthermore, the trailer is shaped in an apex-truncated square pyramid.

Due to an ongoing trend of high injection pressures in the realm of internal combustion engines, the role of cavitation that typically happens inside the injector nozzle has become increasingly important. In this work, a large Eddy Simulation (LES) with cavitation modeled on the basis of an Eulerian Stochastic Field (ESF) method and a homogeneous mixture model is performed to investigate the role of cavitation on the Engine Combustion Network (ECN) spray G2. The Eulerian stochastic field cavitation model is coupled to a pressure based solver for the flow, which lowers the computational cost, thereby making the methodology highly applicable to realistic injector geometries. Moreover, the nature of the Eulerian stochastic field method makes it more convenient to achieve a high scalability when applied to parallel cases, which gives the method the edge over cavitation models that are based on Lagrangian tracking.

In engine research and development there are often different engine parameters that produce similar effects on the end-point results. When calibrating modern engines, a huge number of parameters needs to be set, which also includes compensation parameters for model imperfections. In this context, simpler, more robust, and physically based models should be beneficial both for calibration work load and powertrain performance. In this study, we present an experimental methodology that uses intermediate (“intrinsic”) variables instead of engine parameters. By using simple thermodynamic models, the engine parameters EGR, IVC, and PBoost could be translated into oxygen concentration, temperature and gas density at the start of injection. The reason for this transformation of data is to “move” the Design of Experiment (DoE) closer to the situation of interest (i.e. the combustion) and to be able to construct simpler and more physically based models.

A two-state forward dynamic programming algorithm is evaluated in a series hybrid drive-train application with the objective to minimize fuel consumption when look-ahead information is available. The states in the new method are battery state-of-charge and engine speed. The new method is compared to one-state dynamic programming optimization methods where the requested generator power is found such that the fuel consumption is minimized and engine speed is given by the optimum power-speed efficiency line. The other method compared is to run the engine at a given operating point where the system efficiency is highest, finding the combination of engine run requests over the drive-cycle that minimizes the fuel consumption. The work has included the engine torque and generator power as control signals and is evaluated in a full vehicle-simulation model based on the Volvo Car Corporation VSIM tool.

Today numerical models are a major part of the diesel engine development. They are applied during several stages of the development process to perform extensive parameter studies and to investigate flow and combustion phenomena in detail. The models are divided by complexity and computational costs since one has to decide what the best choice for the task is. 0D models are suitable for problems with large parameter spaces and multiple operating points, e.g. engine map simulation and parameter sweeps. Therefore, it is necessary to incorporate physical models to improve the predictive capability of these models. This work focuses on turbulence and mixing modeling within a 0D direct injection stochastic reactor model. The model is based on a probability density function approach and incorporates submodels for direct fuel injection, vaporization, heat transfer, turbulent mixing and detailed chemistry.

Many technological developments in automobile powertrains have been implemented in order to increase efficiency and comply with emission regulations. Although most of these technologies show promising results in official fuel economy tests, their benefits in real driving conditions and real driving emissions can vary significantly, since driving profiles of many drivers are different than the official driving cycles. Therefore, it is important to assess these technologies under different driving conditions and this paper aims to offer an overall perspective, with a numerical study in simulations. The simulations are carried out on a compact passenger car model with eight powertrain configurations including: a naturally aspirated spark ignition engine, a start-stop system, a downsized engine with a turbocharger, a Miller cycle engine, cylinder deactivation, turbocharged downsized Miller engine, a parallel hybrid electric vehicle powertrain and an electric vehicle powertrain.

Many aerodynamic wind tunnels used for testing of ground vehicles have advanced ground simulation systems to account for the relative motion between the ground and the vehicle. One commonly used approach for ground simulation is a five belt system, where moving belts are used, often in conjunction with distributed suction and tangential blowing that reduces the displacement thickness of the boundary layer along the wind tunnel floor. This paper investigates the effects from aft-belt tangential blowing in the Volvo Cars Aerodynamic wind tunnel. First the uniformity of the boundary layer thickness downstream of the blowing slots is examined in the empty tunnel. This is followed by investigations of how the measured performance of different vehicle types in several configurations, typically tested in routine aerodynamic development work, depends on whether the tangential blowing system is active or not.

Presented are results from numerical investigations of buoyancy driven flow in a simplified representation of an engine bay. A main motivation for this study is the necessity for a valid correlation of results from numerical methods and procedures with physical measurements in order to evaluate the accuracy and feasibility of the available numerical tools for prediction of natural convection. This analysis is based on previously performed PIV and temperature measurements in a controlled physical setup, which reproduced thermal soak conditions in the engine compartment as they occur for a vehicle parked in a quiescent ambient after sustaining high thermal loads. Thermal soak is an important phenomenon in the engine bay primarily driven by natural convection and radiation after there had been a high power demand on the engine. With the cooling fan turned off and in quiescent environment, buoyancy driven convection and radiation are the dominating modes of heat transfer.

Flow visualization techniques are widely used in aerodynamics to investigate the surface trace pattern. In this experimental investigation, the surface flow pattern over the rear end of a full-scale passenger car is studied using tufts. The movement of the tufts is recorded with a DSLR still camera, which continuously takes pictures. A novel and efficient tuft image processing algorithm has been developed to extract the tuft orientations in each image. This allows the extraction of the mean tuft angle and other such statistics. From the extracted tuft angles, streamline plots are created to identify points of interest, such as saddle points as well as separation and reattachment lines. Furthermore, the information about the tuft orientation in each time step allows studying steady and unsteady flow phenomena. Hence, the tuft image processing algorithm provides more detailed information about the surface flow than the traditional tuft method.

The aerodynamic drag, fuel consumption and hence CO2 emissions, of a road vehicle depend strongly on its flow structures and the pressure drag generated. The rear end flow which is an area of complex three-dimensional flow structures, contributes to the wake development and the overall aerodynamic performance of the vehicle. This paper seeks to provide improved insight into this flow region to better inform future drag reduction strategies. Using experimental and numerical techniques, two vehicle shapes have been studied; a 30% scale model of a Volvo S60 representing a 2003MY vehicle and a full scale 2010MY S60. First the surface topology of the rear end (rear window and trunk deck) of both configurations is analysed, using paint to visualise the skin friction pattern. By means of critical points, the pattern is characterized and changes are identified studying the location and type of the occurring singularities.