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This paper presents an approach to numerically simulate greenhouse windnoise. The term “greenhouse windnoise” here describes the sound transferred to the interior through the glass panels of a series vehicle. Different panels, e.g. the windshield or sideglass, are contributing to the overall noise level. Attached parts as mirrors or wipers are affecting the flow around the vehicle and thus the pressure fluctuations which are acting as loads onto the panels. Especially the wiper influence and the effect of different wiper positions onto the windshield contribution is examined and set in context with the overall noise levels and other contributors. In addition, the effect of different flow yaw angles on the windnoise level in general and the wiper contributions in particular are demonstrated. As computational aeroacoustics requires accurate, highly resolved simulation of transient and compressible flow, a Lattice-Boltzmann approach is used.

Trucks can carry heavy load and when applying the brakes during for example a mountain downhill or for an abrupt stop, the brake temperatures can rise significantly. Elevated temperatures in the drum brake region can reduce the braking efficiency or can even cause the brake system to fail, catch fire or even break. It therefore needs to be designed such to be able to transfer the heat out of its system by convection, conduction and/or radiation. All three heat transfer modes play an important role since the drum brakes of trucks are not much exposed to external airflow, a significant difference from disk brakes of passenger cars analyzed in previous studies. This makes it a complex heat transfer problem which is not easy to understand. Numerical methods provide insight by visualization of the different heat transfer modes. Presented is a numerical method that simulates the transient heat transfer of a truck drum brake system cooldown at constant driving speed.

Vehicle thermal management (VTM) simulations are becoming increasingly important in the development phase of a vehicle. These simulations help in predicting the thermal profiles of critical components over a drive cycle. They are usually done using two methodologies: (1) Solving every aspect of the heat transfer, i.e., convection, radiation, and conduction, in a single solver (Conjugate Heat Transfer) or (2) Simulating convection using a fluid solver and computing the other two mechanisms using a separate thermal solver (Co-simulation). The first method is usually computationally intensive, while the second one isn’t. This is because Co-simulation reduces the load of simulating all heat transfer mechanisms in a single code. This is one of the reasons why the Co-simulation method is widely used in the automotive industry. Traditionally, the methods developed for Co-simulation processes are load case specific.

Vehicle thermal management (VTM) simulations constitute an important step in the early development phase of a vehicle. They help in predicting the temperature profiles of critical components over a drive cycle and identify components which are exceeding temperature design limits. Parts with the highest temperatures in a vehicle with an internal combustion engine are concentrated in the engine bay area. As packaging constraints grow tighter, the components in the engine bay are packed closer together. This makes the thermal protection in the engine bay even more crucial. The fan influences the airflow into the engine bay and plays an important role in deciding flow distribution in this region. This makes modelling of the fan an important aspect of VTM simulations. The challenge associated with modelling the fan is the accurate simulation of the rotation imparted by the fan to the incoming flow. Currently, two modelling approaches are prevalent in the industry.

The ultimate goal for vehicle aerodynamicists is to develop vehicles that perform well on the road under real-world conditions. One of the most important metrics to evaluate vehicle performance is the drag coefficient. However, vehicle development today is performed mostly under controlled settings using wind tunnels and computational fluid dynamics (CFD) with artificially uniform upstream conditions, neglecting real-world effects due to road turbulence from wind and other vehicles. Thus, the drag coefficients computed with these methods might not be representative of the real performance of the car on the road. This might ultimately lead engineers to develop design solutions and aerodynamic devices which, while performing well in idealized conditions, do not perform well on the road. For this reason, it is important to assess the vehicle’s drag as seen in real-world environments. An effort in this direction is represented by using the wind-averaged drag.

Modern aerodynamic Class 8 freight tractors can improve vehicle freight efficiency and fuel economy versus older traditional style tractors when pulling Canadian style A- or B-Train double trailer long combination vehicles (LCV's) at highway speeds. This paper compares the aerodynamic performance of a current generation aerodynamic tractor with several freight hauling configurations through computational fluid dynamics evaluations using the Lattice-Boltzmann methodology. The configurations investigated include the tractor hauling a standard 53′ trailer, a platooning configuration with a 30′ separation distance, and an A-Train configuration including two 48′ trailers connected with a dolly converter. The study demonstrates CFD's capability of evaluating extremely long vehicle combinations that might be difficult to accomplish in traditional wind tunnels due to size limitations.

Aerodynamic performance assessment of automotive shapes is typically performed in wind tunnels. However, with the rapid progress in computer hardware technology and the maturity and accuracy of Computational Fluid Dynamics (CFD) software packages, evaluation of the production-level automotive shapes using a digital process has become a reality. As the time to market shrinks, automakers are adopting a digital design process for vehicle development. This has elevated the accuracy requirements on the flow simulation software, so that it can be used effectively in the production environment. Evaluation of aerodynamic performance covers prediction of the aerodynamic coefficients such as drag, lift, side force and also lift balance between the front and rear axle. Drag prediction accuracy is important for meeting fuel efficiency targets, prediction of front and rear lifts as well as side force and yawing moment are crucial for high speed handling.

The importance of fuel economy and emission standards has increased rapidly with high fuel costs and new environmental regulations. This requires analysis techniques capable of designing the next generation long-haul truck to improve both fuel efficiency and cooling. In particular, it is important to have a predictive design tool to assess how exterior design changes impact aerodynamic performance. This study evaluates the use of a Lattice Boltzmann based numerical simulation and the National Research Council (NRC) Canada's wind tunnel to assess aerodynamic drag on a production Volvo VNL tractor-trailer combination. Comparisons are made between the wind tunnel and simulation to understand the influence of wind tunnel conditions on truck aerodynamic performance. The production VNL testing includes a full range of yaw angles to demonstrate the influence of cross wind on aerodynamic drag.

The level of infotainment in today's vehicles and the customer expectation of the functionality imply a significant effort is required on thermal management of the systems, to guarantee their full operation under all operating conditions. The worst case thermal conditions the system will get exposed to are caused by solar loading on the cabin or heat up as a result of cabin heating. Simulation of a solar load driven case will be discussed in this paper. The long soak conditions during these tests result in the modelling requirement for long natural convection periods. This is creating a challenge for the conventional CFD simulations in turnaround time. New simulation methodology has resulted in significant speed up enabling these fully transient simulations in a reasonable turnaround time to enable programme support. A two phase approach to simulating this problem is proposed in this paper.

Long haul tractor design in the future will be challenged by freight efficiency standards and emission legislations. Along with any improvements in aerodynamics, this will also require additional cooling capacity to handle the increased heat rejection from next generation engines, waste heat recovery and exhaust gas recirculation systems. Fan engagement will also have to be minimized under highway conditions to maximize fuel economy. These seemingly contradictory requirements will require design optimization via analysis techniques capable of predicting both the aerodynamic drag and engine cooling airflow accurately. This study builds on previous work [1] using a Lattice Boltzmann based computational method on a Volvo VNL tractor trailer combination. Simulation results are compared to tests conducted at National Research Council (NRC) Canada's wind tunnel.

Air flow in the underhood area is the primary source of engine cooling. A quick look at the vehicle underhood reveals exceptionally complex geometry. In addition to the engine, there are fans, radiator, condenser, other heat exchangers and components. The air flow needs to have adequate access to all relevant parts that require cooling. Due to complex geometry, the task to ensure sufficient air cooling is not a simple one. The air flow entering from the front grille is affected by many components on its path through the underhood. Even small geometry details affect the flow direction and can easily cause recirculation regions which reduce the cooling efficiency. Therefore, air cooling flow analysis requires detailed treatment of the underhood geometry and at the same time accurate air flow modeling. Recent advances in the lattice-Boltzmann equation (LBE) modeling are allowing both.

Over the past decades, interior noise from wind noise or engine noise have been significantly reduced by leveraging improvements of both the overall vehicle design and of sound package. Consequently, noise sources originating from HVAC systems (Heat Ventilation and Air Conditioning), fans or exhaust systems are becoming more relevant for perceived quality and passenger comfort. This study focuses on HVAC systems and discusses a Flow-Induced Noise Detection Contributions (FIND Contributions) numerical method enabling the identification of the flow-induced noise sources inside and around HVAC systems. This methodology is based on the post-processing of unsteady flow results obtained using Lattice Boltzmann based Method (LBM) Computational Fluid Dynamics (CFD) simulations combined with LBM-simulated Acoustic Transfer Functions (ATF) between the position of the sources inside the system and the passenger’s ears.

The demand for low noise level in vehicle cabin continues to rise lately. In particular, noise generated by eco-friendly cars such as hybrid and electric ones tends to become lower and lower. In this market environment, the noise contributions caused by HVAC systems are also increasing. Therefore, it becomes increasingly important to accurately predict noise generated by HVAC systems and analyze the noise sources and resolve the noise issue. In this study, direct acoustics prediction approach based on Lattice Boltzmann Method is applied to predict the flow-induced noise from HVAC systems including blower and ducts and find noise sources. In order to validate the simulation result, acoustics measurements are performed on HVAC systems in an anechoic room and the results are compared to each other. A new technique is applied to finding a noise source for a specific frequency and shows improved noise level through modifying the geometry related to noise sources detected by the simulation.

Systematic numerical simulations were performed for the improvement of fuel efficiency and thermal performance of a compact size passenger vehicle. Both aerodynamic and thermal aspects were considered concurrently. For the sake of systematic evaluation, our study was conducted employing various design changes in multiple steps: 1) analysis of the baseline design; 2) elimination of the engine room components; 3) modification of the engine room component layout; 4) modification of the aerodynamic components (such as under body cover and cooling ducts). The vehicle performance characteristics corresponding to different design options were analyzed in terms of aerodynamic coefficient, engine coolant temperature, and surface temperatures of thermally critical components such as battery and exhaust manifold. Finally optimal design modification solutions for better vehicle performance were proposed.

Two models for the forecast of road traffic emissions, independently developed in parallel, are comparatively presented and assessed: EPROG developed by BMW and enlarged by VDA for a national application (Germany) and FOREMOVE, developed for application on European Community scale. The analysis of the methodological character of the two algorithms proves that the models are fundamentally similar with regard to the basic calculation schemes used for the emissions. The same holds true as far as the significant dependencies of the emission factors, and the recognition and incorporation of the fundamental framework referring to traffic important parameters (speeds, mileage and mileage distribution etc) are concerned.

In recent years, vehicle cabin quietness takes a growing importance particularly related to the emergence of hybrid and electric vehicles and “Idle Stop system” vehicles. Demand for quieter car air-conditioner systems is increasingly important also, especially the reduction of the flow-induced noise from the HVAC. In HVAC systems, the rotating blower is one of the main noise sources and the digital solution for predicting and analyzing the blower aeroacoustic noise in the early stage of design is needed for developing a quieter blower. The target of this study is to develop and to validate a flow-induced noise predictive tool for a HVAC blower and to analyze the noise source. In this paper, a low-dissipation, transient, compressible CFD/CAA approach based on the Lattice Boltzmann Method (LBM) is used to predict simultaneously the flow and aeroacoustic radiation of two production blowers.

The specification of automotive ventilation / defrosting systems has often utilized “trial-and-error” and “prior experience” techniques. But design development and production efficiency has generated a strong interest in using more sophisticated design tools such as computational fluid dynamics. For this purpose a joint experimental and numerical study was undertaken. This comprehensive investigation was divided into two parts. First, the three dimensional defroster flow field was measured using LDA in an actual automobile. Second, LDA and infrared thermography was used to map the flow and temperature fields for a two dimensional jet impinging upon a slanted plate -- a simplified representation of a car defroster geometry.

A newly developed simulation methodology for a long term, transient tractor cabin cool-down is presented in this paper. The air flow was simulated using a Lattice-Boltzmann Equation (LBE) based 3-dimensional flow solver. The conduction and radiation effects on the solid parts as well as the average cabin air temperature evolution were solved by the thermal solver, which also includes a human comfort model. The simulation results were compared with the measured experimental test data and good agreement was observed validating the developed simulation approach. The developed methodology can be applied to all other ground vehicles cabin comfort applications.

This paper describes a novel approach for modeling an automotive HVAC unit. The model consists of black-box models trained with experimental data from a self-developed measurement setup. It is capable of predicting the temperature and mass flow of the air entering the vehicle cabin at the various air vents. A combination of temperature and velocity sensors is the basis of the measurement setup. A measurement fault analysis is conducted to validate the accuracy of the measurement system. As the data collection is done under fluctuating ambient conditions, a review of the impact of various ambient conditions on the HVAC unit is performed. Correction models that account for the different ambient conditions incorporate these results. Numerous types of black-box models are compared to identify the best-suited type for this approach. Moreover, the accuracy of the model is validated using test drive data.

During the design process for a vehicle, the CAD surface geometry becomes available at an early stage so that numerical assessment of aerodynamic performance may accompany the design of the vehicle's shape. Accurate prediction requires open grille models with detailed underhood and underbody geometry with a high level of detail on the upper body surface, such as moldings, trim and parting lines. These details are also needed for aeroacoustics simulations to compute wall-pressure fluctuations, and for thermal management simulations to compute underhood cooling, surface temperatures and heat exchanger effectiveness. This paper presents the results of a significant effort to capitalize on the investment required to build a detailed virtual model of a pickup truck in order to simultaneously assess performance factors for aerodynamics, aeroacoustics and thermal management.