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Bushing elasticity is one of the most important compliance factors that significantly influence driving behavior. The deformations of the bushings change the wheel orientations under external forces. Another important factor of bushing compliance is to provide a comfortable driving experience by isolating the vibrations from road irregularities. However, the driving comfort and driving dynamics are often in conflict and need to be balanced in terms of bushing compliance design. Specifically, lateral force steer and brake force steer are closely related to safety and stability and comprises must be minimized. The sensitivity analysis helps engineers to understand the critical bushing for certain compliance attributes, but optimal balancing is complicated to understand. The combination of individual bushing stiffness must be carefully set to achieve an acceptable level of all the attributes.

We describe experiments and numerical modeling of snow surface contamination on two simplified automotive bluff bodies: The Ahmed body and a wedge. The purpose was twofold: 1) To obtain well defined experimental results of snow contamination on simple geometries; 2) To propose a numerical modeling approach for snow contamination. The experiments were performed in a climatic wind tunnel using a snow cannon at −15 °C and the results show that the snow accumulation depends on the aerodynamics of the studied bluff bodies. Snow accumulates on surfaces in proximity to the aerodynamic wakes of the bodies and characteristic snow patterns are obtained on side surfaces. The numerical modeling approach consisted of an aerodynamic setup coupled with Lagrangian particle tracking. Particles were determined to adhere or rebound depending on an adhesion model combined with a resuspension criterion.

Squeak and rattle (S&R) are nonstationary annoying and unwanted noises in the car cabin that result in considerable warranty costs for car manufacturers. Introduction of cars with remarkably lower background noises and the recent emphasis on electrification and autonomous driving further stress the need for producing squeak- and rattle-free cars. Automotive manufacturers use several road disturbances for physical evaluation and verification of S&R. The excitation signals collected from these road profiles are also employed in subsystem shaker rigs and virtual simulations that are gradually replacing physical complete vehicle test and verification. Considering the need for a shorter lead time and the introduction of optimisation loops, it is necessary to have efficient and inclusive excitation load cases for robust S&R evaluation.

The aim of the presented research is to propose and benchmark two brake models, namely the novel dynamic ILVO (Ilmenau-Volvo) model and a neural-network based regression. These can estimate the evolution of the brake friction between pad and disc under different load conditions, which are typically experienced in vehicle applications. The research also aims improving the knowledge of the underlying mechanism related to the evolution of the BLFC (boundary layer friction coefficient), the reliability of virtual environment simulations to speed up the product development time and reducing the amount of vehicle test in later phases and finally improving brake control functions. With the support of extensive brake dynamometer testing, the proposed models are benchmarked against State-of-the-Art. Both approaches are parametrized to render the friction coefficient dynamics with respect to the same input parameters.

Increasing demand for simulation accuracy often leads to increased finite element model complexity, which in turn, results in higher computational costs. As a provision, component mode synthesis approaches are employed to approximate the system response by using dynamic substructuring and model reduction techniques in linear systems. However, the use of available model reduction techniques in nonlinear problems containing the contact type of nonlinearities remains an interesting topic. In this paper, the application of a component mode synthesis method in squeak and rattle nonlinear simulation has been investigated. Critical regions for squeak and rattle of the side door model of a passenger car were modelled by nonlinear contact definition in finite element simulation. Craig-Bampton model reduction method was employed to substructure the finite element model while keeping the nonlinear contacts in the model.

The objective of this investigation was to improve the thermal properties of plasma sprayed thermal barrier coatings (TBC) for internal combustion engines. There is a need for further reduction of thermal conductivity and volumetric heat capacity and the negative effects on heat loss and combustion phasing of surface roughness and permeable porosity, typical for plasma sprayed coatings, should be minimized. Four measures for improvement of TBC properties were evaluated: i) modification of the coating's microstructure by using a novel suspension plasma spraying method, ii) application of gadolinium-zirconate, a novel ceramic material with low thermal conductivity, iii) polishing of the coating to achieve low surface roughness, and iv) sealing of the porous coating surface with a polysilazane. Six coating variants with different combinations of the selected measures were applied on the piston crown and evaluated in a single cylinder light duty diesel engine.

The need for a more complete understanding of the flow behavior in aerodynamic wind tunnels has increased as they have become vital tools not only for vehicle development, but also for vehicle certification. One important aspect of the behavior is the empty test section flow, which in a conventional tunnel should be as uniform as possible. In order to assess the uniformity and ensure consistent behavior over time, accurate measurements need to be performed regularly. Furthermore, the uncertainties and errors of the measurements need to be minimized in order to resolve small non-uniformities. In this work, the quantification of the measurement uncertainties from the full measurement chain of the new flow uniformity measurement rig for the Volvo Cars aerodynamic wind tunnel is presented. The simulation based method used to account for flow interference of the probe mount is also discussed.

Two imaging techniques are used to investigate the interaction between developed combustion from earlier injections and partially oxidized fuel (POF) of a subsequent injection. The latter is visualized by using planar laser induced fluorescence (PLIF) of formaldehyde and poly-cyclic aromatic hydrocarbons. High speed imaging captures the natural luminescence (NL) of the prevailing combustion. Three different fuel injection strategies are studied. One strategy consists of two pilot injections, with modest separations after each, followed by single main and post injections. Both of the other two strategies have three pilots followed by single main and post injections. The separations after the second and third pilots are several times shorter than in the reference case (making them closely-coupled). The closely-coupled cases have more linear heat release rates (HRR) which lead to much lower combustion noise levels.

In aerodynamic development of ground vehicles, the use of Computational Fluid Dynamics (CFD) is crucial for improving the aerodynamic performance, stability and comfort of the vehicle. Simulation time and accuracy are two key factors of a well working CFD procedure. Using scale-resolving simulations, accurate predictions of the flow field and aerodynamic forces are possible, but often leads to long simulation time. For a given solver, one of the most significant aspects of the simulation time/cost is the temporal resolution. In this study, this aspect is investigated using the realistic vehicle model DrivAer with the notchback geometry as the test case. To ensure a direct and accurate comparison with wind tunnel measurements, performed at TU Berlin, a large section of the wind tunnel is included in the simulation domain. All simulations are performed at a Reynolds number of 3.12 million, based on the vehicle length.

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.

1 Turbocharging plays an important role in the downsizing of engines. Model-based approaches for boost control are going to increasing the necessity for controlling the wastegate flow more accurately. In today’s cars, the wastegate is usually only controlled with a duty cycle and without position feedback. Due to nonlinearities and varying disturbances a duty cycle does not correspond to a certain position. Currently the most frequently used feedback controller strategy is to use the boost pressure as the controller reference. This means that there is a large time constant from actuation command to effect in boost pressure, which can impair dynamic performance. In this paper, the performance of an electrically controlled vacuum-actuated waste-gate, subsequently referred to as vacuum wastegate, is compared to an electrical servo-controlled wastegate, also referred to as electric wastegate.

The demands for a future diesel engine in terms of emission compliance, CO2 emissions, performance and cost effectiveness set new requirements for the development process of the combustion system. This paper focuses on the development of the next generation Volvo Cars diesel combustion system, which should comply with Euro 6d including Real Driving Emissions (RDE), with emphasis on the novel methods applied throughout the process. The foundation of a high performing combustion system is formed by first determining the requirements for the system, after which the key factors that affect system performance are selected, such as the charge motion, combustion chamber geometry and injector nozzle geometry. Based on the requirements, a robust charge motion with desired flow characteristics is defined. A new automated CFD optimization process for combustion chamber geometry and spray target is developed.

Passive sensor (HVAC) manikins have been developed to obtain high-resolution measurements of environmental conditions across a representative human body form. These manikins incorporate numerous sensors that measure air velocity, air temperature, radiant heat flux, and relative humidity. The effect of a vehicle’s climate control system on occupant comfort can be characterized from the data collected by an HVAC manikin. Equivalent homogeneous temperature (EHT) is often used as a first step in a cabin comfort analysis, particularly since it reduces a large data set to a single intuitive number. However, the applicability of the EHT for thermal comfort assessment is limited since it does not account for human homeostasis, i.e., that the human body actively counter-balances heat flow with the environment to maintain a constant core temperature. For this reason, a thermo-physiological human model is required to accurately simulate the body’s dynamic response to a changing environment.

This paper describes the experimental study of a tumble-flap mounted in the intake port of a single-cylinder spark-ignited gasoline engine. The research question addressed was whether an optimal tumble level could be found for the combustion system under investigation. Indicated fuel consumption was measured for a number of part-load operating points with the tumble-flap either open or closed. The experimental results were subjected to an energy balance analysis to understand which portion of the fuel energy was converted to work and how much was lost by incomplete combustion, heat losses to walls and to the exhaust gases, as well as to pumping losses. Closing the tumble-flap resulted in reduced fuel consumption only in a small area of the operating map: only at low-speed, low-load operation, a benefit could be obtained.

To improve fuel efficiency and facilitate handling of the vehicle in a dense city environment, it should be as small as possible given its intended application. This downsizing trend impacts the size of the engine bay, where the air filter box has to be packed in a reduced space, still without increased pressure drop, reduced load capacity nor lower filtering efficiency. Due to its flexibility and reduced cost, CFD simulations play an important role in the optimization process of the filter design. Even though the air-flow through the filter box changes as the dust load increases, the current modeling framework seldom account for such time dependence. Volvo Car Corporation presents an industrial affordable model to solve the time-dependent dust load on filter elements and calculate the corresponding flow behavior over the life time of the air filter box.

With alternative fuels having moved more into market in light of their reduction of emissions of CO2 and other air pollutants, the spark ignited internal combustion engine design has only been affected to small extent. The development of combustion engines running on natural gas or Biogas have been focused to maintain driveability on gasoline, creating a multi fuel platform which does not fully utilise the alternative fuels’ potential. However, optimising these concepts on a fundamental level for gas operation shows a great potential to increase the level of utilisation and effectiveness of the engine and thereby meeting the emissions legislation. The project described in this paper has focused on optimising a combustion concept for CNG combustion on a single cylinder research engine. The ICE’s efficiency at full load and the fuels characteristics, including its knock resistance, is of primary interest - together with part load performance and overall fuel consumption.

Heat loss is one of the greatest energy losses in engines. More than half of the heat is lost to cooling media and exhaust losses, and they thus dominate the internal combustion engine energy balance. Complex processes affect heat loss to the cylinder walls, including gas motion, spray-wall interaction and turbulence levels. The aim of this work was to experimentally compare the heat transfer characteristics of a stepped-bowl piston geometry to a conventional re-entrant diesel bowl studied previously and here used as the baseline geometry. The stepped-bowl geometry features a low surface-to-volume ratio compared to the baseline bowl, which is considered beneficial for low heat losses. Speed, load, injection pressure, swirl level, EGR rate and air/fuel ratio (λ) were varied in a multi-cylinder light duty engine operated in conventional diesel combustion (CDC) mode.

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.

The focus on engine thermal management is rapidly increasing due to the significant effect of heat losses on fuel consumption, engine performance and emissions. This work presents a time resolved, high resolution 3D engine heat balance model, including all relevant components. Notably, the model calculates the conjugated heat transfer between the solid engine components, the coolant and the oil. Both coolant and oil circuits are simultaneously resolved with a CFD solver in the same finite volume model as the entire engine solid parts. The model includes external convection and radiation. The necessary boundary conditions of the thermodynamic cycle (gas side) are mapped from a calibrated 1D gas exchange model of the same engine. The boundary conditions for the coolant and at the oil circuits are estimated with 1D models of the systems. The model is calibrated and verified with measurement data from the same engine as modeled.