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Car manufacturers put large efforts into reducing wind noise to improve the comfort level of their cars. Each component of the vehicle is designed to meet its individual noise target to ensure the wind noise passenger comfort level inside the vehicle is met. Sunroof designs are tested to meet low-frequency buffeting (also known as boom) targets and broadband noise targets for the fully open sunroof with deflector and for the sunroof in vent position. Experimentally testing designs and making changes to meet these design targets typically involves high cost prototypes, expensive wind tunnel sessions, and potentially late design changes. To reduce the associated costs as well as development times, there is strong motivation for the use of a reliable numerical prediction capability early in the vehicle design process.

In an era of rapidly increasing vehicle electrification, the gasoline engine remains a vital part of the passenger car powertrain portfolio. Lean-burn combustion is a formidable means for reducing the CO2 emissions of gasoline engines but demands the use of sophisticated emissions control. A 2.0 litre turbocharged direct-injection gasoline engine has been developed with a lean homogeneous combustion system matched to a robust lean and stoichiometric-capable exhaust aftertreatment. The aftertreatment system includes an SCR system and a GPF with filtration down to 10 nm particle size. The engine is equipped with a continuously variable valve-lift system, high-tumble ports and a high-energy ignition system; the boosting system comprises a variable geometry turbocharger and a 48 V electrical supercharger. The work reported formed part of the PaREGEn (Particle Reduced, Efficient Gasoline Engines) project under the Horizon 2020 framework programme.

Complexity of electronics and embedded software systems in automobiles has been increasing over the years. This necessitates the need for an effective and exhaustive development and validation process in order to deliver fault free vehicles at reduced time to market. Model-based Product Engineering (MBPE) is a new process for development and validation of embedded control software. The process is generic and defines the engineering activities to plan and assess the progress and quality of the software developed for automotive applications. The MBPE process is comprised of six levels (one design level and five verification and validation levels) ranging from the vehicle requirements phase to the start of production. The process describes the work products to be delivered during the course of product development and also aligns the delivery plan to overall vehicle development milestones.

The advent of 3D displays offers Human-Machine Interface (HMI) designers and engineers new opportunities to shape the user's experience of information within the vehicle. However, the application of 3D displays to the in-vehicle environment introduces a number of new parameters that must be carefully considered in order to optimise the user experience. In addition, there is potential for 3D displays to increase driver inattention, either through diverting the driver's attention away from the road or by increasing the time taken to assimilate information. Manufacturers must therefore take great care in establishing the ‘do’s and ‘don’t's of 3D interface design for the automotive context, providing a sound basis upon which HMI designers can innovate. This paper describes the approach and findings of a three-part investigation into the use of 3D displays in the instrument cluster of a road car, the overall aim of which was to define the boundaries of the 3D HMI design space.

Many electric (EV) and hybrid-electric (HEV) vehicles are designed to operate using only electric propulsion at low road speeds. This has resulted in significantly reduced vehicle noise levels in urban situations. Although this may be viewed by many as a benefit, a risk to safety exists for those who rely on the engine noise to help detect the presence, location and behaviour of a vehicle in their vicinity. In recognition of this, legislation is being introduced globally which will require automotive manufacturers to implement external warning sound systems. A key challenge for premium vehicle manufacturers is the development of a suitable warning sound signature which also conveys the appropriate brand aspirations for the product. A further major difficulty exists when trying to robustly evaluate potential exterior sounds by running large-scale trials in the real world.

Simulation of local flow structures in the A-pillar/side glass region of bluff SUV geometries, typical of Land Rover vehicles, presents a considerable challenge. Features such as relatively tight A-pillar radii and upright windscreens produce flows that are difficult to simulate. However, the usefulness of aerodynamics simulations in the early assessment of wind noise depends particularly on the local accuracy obtained in this region. This paper extends work previously published by the author(1) with additional data and analysis. An extended review of the relevant published literature is also provided. Then the degree to which a commercial Lattice-Boltzman solver (Exa PowerFLOW™) is currently able to capture both the local flow structure and surface pressure distribution (both time averaged and unsteady) is evaluated. Influential factors in the simulation are shown to be spatial resolution, turbulence and boundary layer modelling.

Disc brake noise is recognized as a major problem of the automotive industry. Various experimental and numerical techniques have been developed to model the noisy brake and investigate possible solutions. Developing a virtual model of the disc brake which can accurately reproduce the behavior of the brake unit under different conditions is a considerable step forward towards reaching this goal. Among various aspects of the analytical model of a disc brake, application of the correct value of damping based on the material properties and functional frequency range of each component is a significant factor in ensuring correct prediction of the brake system behavior. Complex Eigenvalue Analysis is well established as a tool for predicting brake instabilities which can potentially lead to brake noise. However, it is known to over-predict instabilities i.e. predict instabilities which do not occur in the real brake system.

This paper documents some of the findings from a joint JLR and AVL project which was conducted at the JLR Gaydon test facility in the UK. A testing and development efficiency concept is presented and test data quality is identified as a key factor. In support of this methods are proposed to correctly measure and set targets for data quality with high confidence. An illustrative example is presented involving a Diesel passenger car calibration process which requires response surface models (RSMs) of key engine measured quantities e.g. engine-out emissions and fuel consumption. Methods are proposed that attempt to quantify the relationships between RSM statistical model quality metrics, test data variability measures and design of experiment (DOE) formulation. The methods are tested using simulated and real test data.

Full hybrid electric vehicles are usually defined by their capability to drive in a fully electric mode, offering the advantage that they do not produce any emissions at the point of use. This is particularly important in built up areas, where localized emissions in the form of NOx and particulate matter may worsen health issues such as respiratory disease. However, high degrees of electrification also mean that waste heat from the internal combustion engine is often not available for heating the cabin and for maintaining the temperature of the powertrain and emissions control system. If not managed properly, this can result in increased fuel consumption, exhaust emissions, and reduced electric-only range at moderately high or low ambient temperatures negating many of the benefits of the electrification. This paper describes the development of a holistic, modular vehicle model designed for development of an integrated thermal energy management strategy.

The HyPACE (Hybrid Petrol Advanced Combustion Engine) project is a part UK government funded research project established to develop a high thermal efficiency petrol engine that is optimized for hybrid vehicle applications. The project combines the capabilities of a number of partners (Jaguar Land Rover, BorgWarner, MAHLE Powertrain, Johnson Matthey, Cambustion and Oxford University) with the target of achieving a 10% vehicle fuel consumption reduction, whilst still achieving a 90 to 100 kW/liter power rating through the novel application of a combination of new technologies. The baseline engine for the project was Jaguar Land Rover’s new Ingenium 4-cylinder petrol engine which includes an advanced continuously variable intake valve actuation mechanism. A concept study has been undertaken and detailed combustion Computational Fluid Dynamics (CFD) models have been developed to enable the optimization of the combustion system layout of the engine.

The rotor and stator of electric motors consist of multiple materials, of which steel forms the majority of mass and volume. Steel in electric motors is commonly in the form of thin sheets (laminations), stacked along the axis of the rotor. The structural integrity of such a stack can be ensured using bolting, welding or bonding of the laminations. Predictive mechanical finite element simulations of these laminated stacks can become computationally intense because the steel sheets are thin, and the motor often contains hundreds of them. If the laminations are modelled individually, the size of the elements is very small compared to the overall dimensions and the interface between the laminations need to be modelled as well. In this paper, we present an alternate method of modelling this laminated stack as a single solid body using homogeneous and orthotropic material property, instead of representing each lamination.

A prototype multi-hole diesel injector operating with n-heptane fuel from a high-pressure common rail system is used in a high-pressure and high-temperature test rig capable of reaching 1100 Kelvin and 150 bar under different oxygen concentrations. A novel optical set-up capable of visualizing the soot cloud evolution in the fuel jet from 30 to 85 millimeters from the nozzle exit with the high-speed color diffused back illumination technique is used as a result of the insertion of a high-pressure window in the injector holder opposite to the frontal window of the vessel. The experiments performed in this work used one wavelength provide information about physical of the soot properties, experimental results variating the operational conditions show the reduction of soot formation with an increase in injection pressure, a reduction in ambient temperature, a reduction in oxygen concentration or a reduction in ambient density.

Increasingly stringent regulations and rising fuel costs require that automotive manufacturers reduce their fleet CO2 emissions. Gasoline engine downsizing is one such technology at the forefront of improvements in fuel economy. As engine downsizing becomes more aggressive, normal engine operating points are moving into higher load regions, typically requiring over-fuelling to maintain exhaust gas temperatures within component protection limits and retarded ignition timings in order to mitigate knock and pre-ignition events. These two mechanisms are counterproductive, since the retarded ignition timing delays combustion, in turn raising exhaust gas temperature. A key process being used to inhibit the occurrence of these knock and pre-ignition phenomena is cooled exhaust gas recirculation (EGR). Cooled EGR lowers temperatures during the combustion process, reducing the possibility of knock, and can thus reduce or eliminate the need for over-fuelling.

A novel semi-analytical solution has been developed for the calculation of the static and dynamic response of an off road tire interacting with a deformable terrain, which utilizes soil parameters independent of the size of the contact patch (size-independent). The models involved in the solution presented, can be categorized in rigid and/or pneumatic tires, with or without tread pattern. After a concise literature review of related methods, a detailed presentation of the semi-analytical solution is presented, along with assumptions and limitations. A flowchart is provided, showing the main steps of the numerical implementation, and various test cases have been examined, characterized in terms of vertical load, tire dimensions, soil properties, deformability of the tire, and tread pattern. It has been found that the proposed model can qualitatively capture the response of a rolling wheel on deformable terrain.

Mathematical modelling has become an essential tool in the design of modern catalytic systems. Emissions legislation is becoming increasingly stringent, and so mathematical models of aftertreatment systems must become more accurate in order to provide confidence that a catalyst will convert pollutants over the required range of conditions. Automotive catalytic converter models contain several sub-models that represent processes such as mass and heat transfer, and the rates at which the reactions proceed on the surface of the precious metal. Of these sub-models, the prediction of the surface reaction rates is by far the most challenging due to the complexity of the reaction system and the large number of gas species involved.

Over the past decade there have been significant advances made in the technology used to engineer Powertrain Sound Quality into automobiles. These have included exhaust system technologies incorporating active and semi-active valves, intake system technologies involving passive and direct feedback devices, and technologies aimed at tuning the structure-borne content of vehicle interior sound. All of these technologies have been deployed to complement the traditional control of NVH issues through the enhancement of Powertrain Sound Quality. The aim of this paper is to provide an historical review of the recent industry-wide advances made in these technologies and to provide the author's perspective on what issues have been addressed and what opportunities have been delivered.

Testing real-time vehicular systems challenges the tester to design test cases for concurrent and sequential input events, emulating unexpected user and usage profiles. The vehicle response should be robust to unexpected user actions. Sequence Covering Arrays (SCA) offer an approach which can emulate such unexpected user actions by generating an optimized set of test vectors which cover all possible t-way sequences of events. The objective of this research was to find an efficient nonfunctional sequence testing (NFST) strategy for testing the robustness of real-time automotive embedded systems measured by their ability to recover (prove-out test) after applying sequences of user and usage patterns generated by combinatorial test algorithms, considered as “noisy” inputs. The method was validated with a case study of an automotive embedded system tested at Hardware-In-the-Loop (HIL) level. The random sequences were able to alter the system functionality observed at the prove-out test.

Government regulations and consumer needs are driving automotive manufacturers to reduce vehicle energy consumption. However, this forms part of a complex landscape of regulation and customer needs. For instance, when reducing aerodynamic drag or vehicle weight for efficiency other important factors must be taken into account. This is seen in vehicle bonnet design. The bonnet is a large unsupported structure that is exposed to very high and often fluctuating aerodynamic loads, due to travelling in the wake of other vehicles. When travelling at high speed and in close proximity to other vehicles this unsteady aerodynamic loading can force the bonnet structure to vibrate, so-called “bonnet flutter”. A bonnet which is stiff enough to not flutter may be either too heavy for efficiency or insufficiently compliant to meet pedestrian safety requirements. On the other hand, a bonnet which flutters may be structurally compromised or undermine customer perceptions of vehicle quality.

Vehicle water wading capability refers to vehicle functional part integrity (e.g. engine under-tray, bumper cover, plastic sill cover etc.) when travelling through water. Wade testing involves vehicles being driven through different depths of water at various speeds. The test is repeated and under-body functional parts are inspected afterwards for damage. Lack of CAE capability for wading equates to late detection of failure modes which inevitably leads to expensive design change, and potentially affects program timing. It is thus of paramount importance to have a CAE capability in this area to give design loads to start with. Computational fluid dynamics (CFD) software is used to model a vehicle travelling through water at various speeds. A non-classical CFD approach was deemed necessary to model this. To validate the method, experimental testing with a simplified block was done and then verified with CFD modeling.

The modern luxurious electric vehicle (EV) demands high torque and high-speed requirements with increased range. Fulfilling these requirements gives rise to the need for increased efficiency and power density of the motors in the Electric Drive Unit (EDU). Internal Permanent Magnet (IPM) motor is one of the best suited options in such scenarios because of its primary advantages of higher efficiency and precise control over torque and speed. In the IPM motor, permanent magnets are mounted within the rotor body to produce a resultant rotating magnetic field with the 3-phase AC current supply in the stator. IPM configuration provides structural integrity and high dynamic performance as the magnets are inserted within the rotor body. Adhesive glue is used to install the magnets within the laminated stack of rotor.