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The flows in-cylinder have a profound effect on the mixture preparation and subsequent combustion in all engines. These flows are highly three-dimensional in nature and information from multiple planes is required to characterise the flow dynamics. The flow measurements reported here are from three orthogonal planes in an optical access engine that is based on the Jaguar Land Rover AJ200 Gasoline Direct Injection (GDI) engine. Particle Image Velocimetry (PIV) measurements have been taken every 5°CA from the start of induction to the end of compression. Data have been obtained from 300 cycles for separate experiments measuring flows in the tumble plane, the swirl plane and the cross-tumble plane. Vector comparison metrics are used to quantitatively compare ensemble averaged PIV flow fields to Computational Fluid Dynamics (CFD) simulations across each plane in terms of both the velocity magnitude and direction.

Many modern vehicles have blunt rear end geometries for design aesthetics and practicality; however, such vehicles are potentially high drag. The application of tapering; typically applied to an entire edge of the base of the geometry is widely reported as a means of reducing drag, but in many cases, this is not practical on real vehicles. In this study side tapers are applied to only part of the side edge of a simplified automotive geometry, to show the effects of practical implementations of tapers. The paper reports on a parametric study undertaken in Loughborough University’s Large Wind Tunnel with the ¼ scale Windsor model equipped with wheels. The aerodynamic effect of implementing partial side edge tapers is assessed from a full height taper to a 25% taper in both an upper and lower body configuration. These were investigated using force and moment coefficients, pressure measurements and planar particle image velocimetry (PIV).

The field of vision of the driver during wet road conditions is essential for safety at all times. Additionally, the safe use of the increasing number of sensors integrated in modern cars for autonomous driving and intelligent driver assistant systems has to be ensured even under challenging weather conditions. To fulfil these requirements during the development process of new cars, experimental and numerical investigations of vehicle soiling are performed. This paper presents the surface contamination of self- and foreign-soiling tested in the wind tunnel. For these type of tests, the fluorescence method is state-of-the-art and widely used for visualizing critical areas. In the last years, the importance of parameters like the contact angle have been identified when designing the experimental setup. In addition, new visualization techniques have been introduced.

The management of surface water flows driven from the wind screen by the action of wipers and aerodynamic shear is a growing challenge for automotive manufacturers. Pressure to remove traditional vehicle features, such as A-Pillar steps for aesthetic, aeroacoustic and aerodynamic reasons increases the likelihood that surface water may be convected over the A-Pillar and onto the front side glass where it can compromise drivers’ vision. The ability to predict where and under which conditions the A-Pillar will be breached is important for making correct design decisions. The use of numerical simulation in this context is desirable, as experimental testing relies on the use of aerodynamics test properties which will not be fully representative, or late-stage prototypes, making it difficult and costly to correct issues. This paper provides an update on the ability of simulation to predict A-Pillar overflow, comparing physical and numerical results for a test vehicle.

Physical testing of a vehicle wading through water is performed to gauge its capability to traverse through shallow to deep levels of water, wherein various vehicle performance parameters are observed, recorded and analysed. Jaguar Land Rover (JLR) has instigated and established a comprehensive CAE test procedure for assessing the same, which makes use of overset mesh (in a CFD environment) for a non-traditional approach to vehicle motion. The paper presents investigations made into the established wading physics, in order to optimise the splashing and water jet modelling. Large Scale Interface model was implemented instead of the previously standardised VOF-VOF fluid phase interaction model, and a comparison is made between the two. The implemented wheel rotation approach was scrutinised as well and appropriate inferences are drawn.

In order to specify a brake system that will have robust performance over the entire range of expected vehicle drive cycles it is vital that it has sufficient thermal inertia and dissipation to ensure that component temperatures are kept within acceptable limits. This paper presents a high fidelity CAE (computer aided engineering) technique for predicting the temperature of the front brake and the surrounding suspension components whilst installed on vehicle. To define the boundary conditions the process utilizes a coupled unsteady CFD (computational fluid dynamics) and thermal solver to accurately predict the convective heat transfer coefficients across a range of vehicle speeds. A 1-D model is used to predict the brake energy inputs as well as the vehicle speed-time curves during the drive cycle based on key vehicle parameters including wide-open-throttle performance, drive train losses, rolling resistance, aerodynamic drag etc.

Flash-boiling of sprays may occur when a superheated liquid is discharged into an ambient environment with lower pressure than its saturation pressure. Such conditions normally exist in direct-injection spark-ignition engines operating at low in-cylinder pressures and/or high fuel temperatures. The addition of novel high volatile additives/fuels may also promote flash-boiling. Fuel flashing plays a significant role in mixture formation by promoting faster breakup and higher fuel evaporation rates compared to non-flashing conditions. Therefore, fundamental understanding of the characteristics of flashing sprays is necessary for the development of more efficient mixture formation. The present computational work focuses on modelling flash-boiling of n-Pentane and iso-Octane sprays using a Lagrangian particle tracking technique.

This paper addresses the need for fundamental understanding of the mechanisms of fuel spray formation and mixture preparation in direct injection spark ignition (DISI) engines. Fuel injection systems for DISI engines undergo rapid developments in their design and performance, therefore, their spray breakup mechanisms in the physical conditions encountered in DISI engines over a range of operating conditions and injection strategies require continuous attention. In this context, there are sparse data in the literature on spray formation differences between conventionally drilled injectors by spark erosion and latest Laser-drilled injector nozzles. A comparison was first carried out between the holes of spark-eroded and Laser-drilled injectors of same nominal type by analysing their in-nozzle geometry and surface roughness under an electron microscope.

The object of the validation study presented in this paper is a generic vehicle, the so-called SAE body, developed by a consortium of German car manufacturers (Audi, Daimler, Porsche, Volkswagen). Many experiments have been performed by the abovementioned consortium on this object in the past to investigate its behavior when exposed to fluid flow. Some of these experiments were used to validate the simulation results discussed in the present paper. It is demonstrated that the simulation of the exterior flow is able to represent the transient hydrodynamic structures and at the same time both the generation of the acoustic sources and the propagation of the acoustic waves. Performing wave number filtering allows to identify the acoustic phenomena and separate them from the hydrodynamic effects. In a next step, the noise transferred to the interior of the cabin through the glass panel was calculated, using a Statistical Energy Analysis approach.

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.

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.

This paper presents the development and implementation of an Analytical Target Cascading (ATC) Multi-disciplinary Design Optimisation (MDO) framework for the steady state engine calibration optimisation problem. The case is made that the ATC offers a convenient framework for the engine calibration optimisation problem based on steady state engine test data collected at specified engine speed / load points, which is naturally structured on 2 hierarchical levels: the ‘Global’ level, associated with performance over a drive cycle, and ‘Local’ level, relating to engine operation at each speed / load point. The case study of a diesel engine was considered to study the application of the ATC framework to a calibration optimisation problem. The paper describes the analysis and mathematical formulation of the diesel engine calibration optimisation as an ATC framework, and its Matlab implementation with gradient based and evolutionary optimisation algorithms.

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.

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 modelling.

A computational process for early stage vehicle shape assessment for automotive front window buffeting and greenhouse wind noise is presented. It is a challenging problem in an experimental process as the vehicle geometry is not always finalized. For example, the buffeting behavior typically worsens during the vehicle development process as the vehicle gets tighter, leading to expensive late counter measures. We present a solution using previously validated CFD/CAA software based on the Lattice Boltzmann Method (LBM). A CAD model with realistic automotive geometry was chosen to simultaneously study the potential of different side mirror geometries to influence the front window buffeting and greenhouse wind noise phenomena. A glass mounted mirror and a door mounted mirror were used for this comparative study. Interior noise is investigated for the two phenomena studied. The unsteady flow is visualized and changes in the buffeting and wind noise behavior are explored.

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.

The bio-fuel, 2,5 - dimethylfuran (DMF) is currently regarded as a potential alternative fuel to gasoline due to the development of new production technology. However, little is known about the flame behavior in an optical engine. In this paper, high speed imaging (with intensifier) was used during the combustion of DMF and its blends with gasoline and ethanol (D50, D85, E50D50 and E85D15) in an SI optical engine. The flame images from the combustion of each fuel were analyzed at two engine loads: 3bar and 4bar IMEP. For DMF, D50 and E50D50, two modes were compared: DI and PFI. The average flame shapes (in 2D) and the average flame speeds were calculated and combined with mass fraction burned (MFB) data. The results show that when using DMF, the rate of flame growth development and flame speed is higher than when using gasoline. The differences in flame speed between DMF and gasoline is about 10% to 14% at low IMEP.

Hardware-in-the-loop (HIL) simulations have long been used to test electronic control units (ECUs) and software in car manufacturers. It provides an effective platform to the rapid development process of the ECU control algorithms and accommodates the added complexity of the plant under control. Accurate Model based HIL simulation (AMHIL) is considered as a most efficient and cost effective way for exploration of new designs and development of new products, particularly in calibration and parameterization of vehicle stability controllers. The work presented in the paper is to develop a mathematical model of a windscreen wiper system for the purpose of conducting HIL vehicle test and eventually to replace the real component with the model for cost cutting and improved test efficiency. The model is developed based on the electro-mechanical engineering principles.

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.

Automotive engines are regularly utilized in the material handling market where LPG is often the primary fuel used. When compared to gasoline, the use of gaseous fuels (LPG and CNG) as well as alcohol based fuels, often result in significant increases in valve seat insert (VSI) and valve face wear. This phenomenon is widely recognized and the engine manufacturer is tasked to identify and incorporate appropriate valvetrain material and design features that can meet the ever increasing life expectations of the end-user. Alternate materials are often developed based on laboratory testing – testing that may not represent real world usage. The ultimate goal of the product engineer is to utilize accelerated lab test procedures that can be correlated to field life and field failure mechanisms, and then select appropriate materials/design features that meet the targeted life requirements.