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The reduction in wind noise is increasingly important to vehicle designers as overall vehicle refinement increases. Customers often fit accessories such as roof bars to vehicles, with the aerodynamic interaction of these components generating aeroacoustic noise sources. These are often tonal in nature and of particular annoyance to occupants. Sensors for automated driving fitted to future vehicles may also have a similar detrimental effect on vehicle refinement. Therefore, careful design of such components is important to minimise dissatisfaction. This paper presents the combined application of acoustic beamforming in a full-scale aeroacoustic wind tunnel and the use of a Lattice Boltzmann Method CFD code to characterise the aeroacoustic performance of a roof bar design when fitted to a production vehicle.

The in-cabin sound pressure level response of a vehicle in yawed wind conditions can differ significantly between the smooth flow conditions of the aeroacoustic wind tunnel and the higher turbulence, transient flow conditions experienced on the road. Previous research has shown that under low turbulence conditions there is close agreement between the variation with yaw of in-cabin sound pressure level on the road and in the wind tunnel. However, under transient conditions, sound pressure levels on the road were found to show a smaller increase due to yaw than predicted by the wind tunnel, specifically near the leeward sideglass region. The research presented here investigates the links between transient flow and aeroacoustics. The effect of small geometry changes upon the aeroacoustic response of the vehicle has been investigated.

At higher speeds aerodynamic noise tends to dominate the overall noise inside the passenger compartment. Large-scale turbulent conditions experienced on the road can generate different noise characteristics from those under steady-state conditions experienced in an acoustic wind tunnel. The objective of this research is to assess the relationship between on-road flow conditions and the sound pressure level in the cabin. This research, covering links between the unsteady airflow around the vehicle and aeroacoustic effects, is a natural progression from previous aerodynamic studies. On-road testing was undertaken using a current production vehicle equipped with a mobile data logging system. Testing was carried out on major roads at typical highway speeds, where wind noise is very significant. Of particular interest are high-yaw conditions, which can lead to a blustering phenomenon.

A vehicle driving on the road experiences unsteady flow conditions which are not generally reproduced in the development environment. This paper investigates the potential importance of this difference to aeroacoustics and hence to occupant perception and proposes a methodology to enable better ranking of designs by taking account of wind noise modulation. Two approaches of reproducing the effects of unsteady wind on aeroacoustics were investigated: an active wind tunnel Turbulence Generation System (TGS) and a quasi-steady approach based on measurements at a series of fixed yaw angles. A number of tools were used to investigate the onset flow and its impacts, including roof-mounted probe, acoustic heads and surface microphones. External noise measurements help to reveal the response of separate exterior noise sources to yaw.

Vehicle manufacturers demand early design assessment of vehicle wind noise attribute so as to eliminate engineering waste induced by late design changes. Vehicle wind noise attribute can be simulated with a Statistical Energy Analysis (SEA) model using exterior surface turbulence pressure on the vehicle greenhouse panel as the wind noise load. One important application of SEA wind noise model is the wind noise assessment for vehicle form design. Vehicle form optimization for wind noise plays an important role in lightweight vehicle architecture, since that reduction in the wind noise load will compensate the loss of vehicle body acoustic attenuation caused by down-gauge glazing and body panels. In this paper, two SEA wind noise load cases currently used in vehicle SEA wind noise modeling have been analyzed and evaluated against vehicle measurements.

Vehicle wind noise is becoming increasingly important to customer satisfaction. Early wind noise assessment is critical to get things right during the early design phase. In this paper, SEA modeling technique is used to predict vehicle interior noise caused by the exterior turbulence. Measured surface turbulence pressures over vehicle greenhouse panels are applied as wind noise load. SEA representation of wind noise load case is investigated. It has been found that current SEA wind noise load case over-estimates at frequencies below window glass coincident frequency. A new concept of noise source pole index is introduced and a new wind noise load coupling has been developed. Comparison with vehicle wind tunnel measurements shows that the proposed load case significantly improved prediction accuracy.

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.

Statistical Energy Analysis (SEA) is the standard analytical tool for predicting vehicle acoustic and vibration responses at high frequencies. SEA is commonly used to obtain the interior Sound Pressure Level (SPL) due to each individual noise or vibration source and to determine the contribution to the interior noise through each dominant transfer path. This supports cascading vehicle noise and vibration targets and early evaluation of the vehicle design to effectively meet NVH targets with optimized cost and weight. A common misconception is that SEA is only capable of predicting a general average interior SPL for the entire vehicle cabin and that the differences between different locations such as driver's ear, rear passenger's ear, lower interior points, etc., in the vehicle cannot be analytically determined by an SEA model.

The power demand of air conditioning in PHEVs is known to have a significant impact on the vehicle’s fuel economy and performance. Besides the cooling power associated to the passenger cabin, in many PHEVs, the air conditioning system provides power to cool the high voltage battery. Calculating the cooling power demands of the cabin and battery and their impact on the vehicle performance can help with developing optimum system design and energy management strategies. In this paper, a representative vehicle model is used to calculate these cooling requirements over a 24-hour duty cycle. A number of pre-cooling and after-run cooling strategies are studied and effect of each strategy on the performance of the vehicle including, energy efficiency, battery degradation and passenger thermal comfort are calculated. Results show that after-run cooling of the battery should be considered as it can lead to significant reductions in battery degradation.

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.

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.

This study presents a one-dimensional model for the prediction of the pressure loss across a wall-flow gasoline particulate filter (GPF). The model is an extension of the earlier models of Bissett [1] and Konstandopoulos and Johnson [2] to the turbulent flow regime, which may occur at high flow rates and temperatures characteristic of gasoline engine exhaust. A strength of the proposed model is that only one parameter (wall permeability) needs to be calibrated. An experimental study of flow losses for cold and hot flow is presented, and a good agreement is demonstrated. Unlike zero-dimensional models, this model provides information about the flow along the channels and thus can be extended for studies of soot and ash accumulation, heat transfer and reaction kinetics.

Electrical power requirements for vehicles continue to increase. Future vehicle applications require the development of reliable and robust power supply strategies that operate over various ambient temperatures and driving conditions. Insufficient charge balance is one of the major concerns for conventional lead-acid battery systems when operated with limited charging times during short journeys or extreme climate conditions. For vehicle power supply analysis, a detailed understanding of the operational characteristics of the major components and how they interact as a part of the electric power system, including environmental and road conditions, is essential if the analysis is to aid system optimization. This paper presents a model based technique that enhances the process of vehicle electrical power system design. Vehicle system optimization using virtual prototypes has become critically important as more electrical features are added to future vehicles.

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.

Automotive manufactures demand early assessment of vehicle form design against wind noise attribute to eliminate any engineering waste induced by late design changes. To achieve such an assessment, it is necessary to determine a measurable quantity which is able to represent vehicle form changes, and to understand the relationship between the quantity and vehicle interior cabin noise. This paper reports experimental measurements of vehicle exterior surface pressure and the interior cabin noise level in response to the change of exterior rear view mirror shape. Measurements show that exterior surface pressure on vehicle greenhouse panel is a primary factor of wind noise load to the interior cabin noise; they can be used in preliminary wind noise ranking. Care should be taken when using them in ranking vehicle form wind noise performance. It has been observed that a change in surface pressure on the front side window does not necessarily lead to a change in the interior cabin noise.

Simulations are presented which fully couple both the aerodynamics and cooling flow for a model of a fully engineered production saloon car (Jaguar XJ) with a two-tier cooling pack. This allows for the investigation of the overall aerodynamic impact of the under-hood cooling flow, which is difficult to predict experimentally. The simulations use a 100 million-element mesh, surface wrapped and solved to convergence using a commercially available RANS solver (STARCCM+). The methodology employs representative boundary conditions, such as rotating wheels and a moving ground plane. A review is provided of the effect of cooling flows on the vehicle aerodynamics, compared to published data, which suggest cooling flow accounts for 26 drag counts (0.026 Cd). Further, a sensitivity analysis of the pressure drop curves used in the porous media model of the heat exchangers is made, allowing for an initial understanding of the effect on the overall aerodynamics.

A vehicle on the road encounters an unsteady flow due to turbulence in the natural wind, unsteady wakes of other vehicles and as a result of traversing through the stationary wakes of roadside obstacles. Unsteady effects occurring in the sideglass region of a vehicle are particularly relevant to wind noise. This is a region close to the driver and dominated by separated flow structures from the A-pillar and door mirrors, which are sensitive to unsteadiness in the onset flow. Since the sideglass region is of particular aeroacoustic importance, the paper seeks to determine what impact these unsteady effects have on the sources of aeroacoustic noise as measured inside the passenger compartment, in addition to the flow structures in this region. Data presented were obtained during on-road measurement campaigns using two instrumented vehicles, as well as from aeroacoustic wind tunnel tests.

Historically vehicle aerodynamic development has focused on testing under idealised conditions; maintaining measurement repeatability and precision in the assessment of design changes. However, the on-road environment is far from ideal: natural wind is unsteady, roadside obstacles provide additional flow disturbance, as does the presence of other vehicles. On-road measurements indicate that turbulence with amplitudes up to 10% of vehicle speed and dominant length scales spanning typical vehicle sizes (1-10 m) occurs frequently. These non-uniform flow conditions may change vehicle aerodynamic behaviour by interfering with separated turbulent flow structures and increasing local turbulence levels. Incremental improvements made to drag and lift during vehicle development may also be affected by this non-ideal flow environment. On-road measurements show that the shape of the observed turbulence spectrum can be generalised, enabling the definition of representative wind conditions.

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.

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.