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This paper presents a simulation of the cooling airflow and surface temperatures of a midsize truck. The simulation uses full detailed geometry of the truck. Performance of the under-hood cooling airflow is analyzed and potential design changes leading to better cooling airflow are highlighted. Surface temperature over certain under-hood part is studied. Possible optimizations using various material and configurations are proposed. It is shown that the presented simulation approach provides valuable information to evaluate cooling system and thermal protection performance. Fast design iterations can be achieved using this approach.

For most car manufacturers, wind noise from the greenhouse region has become the dominant high frequency noise contributor at highway speeds. Addressing this wind noise issue using experimental procedures 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. Previously, a computational approach that couples an unsteady computational fluid dynamics solver (based on a Lattice Boltzmann method) to a Statistical Energy Analysis (SEA) solver had been validated for predicting the noise contribution from the side mirrors. This paper presents the use of this computational approach to predict the vehicle interior noise from the windshield wipers, so that different wiper placement options can be evaluated early in the design process before the surface is frozen.

More stringent heavy vehicle emissions legislation demands considerably higher performance for engine cooling systems. This paper presents a study of cooling airflow for a Freightliner Class 8 truck. The predicted radiator coolant inlet and charge-air-cooler outlet temperatures are in very good agreement with the measured data. The under hood flow behavior is described and potential areas of improvement leading to better cooling airflow performance are highlighted. The airflow simulation approach is based on the Lattice-Boltzmann Method (LBM) and is described in detail. It is shown that the presented simulation approach can provide accurate predictions of cooling airflow and coolant temperature across different fan speeds.

A validation study was performed comparing the simulation results of the Lattice-Boltzmann Equation (LBE) based flow solver, PowerFLOW®, to cooling cell measurements conducted at Volvo Trucks North America (VTNA). The experimental conditions were reproduced in the simulations including dynamometer cell geometry, fully detailed under-hood, and external tractor geometry. Interactions between the air flow and heat exchangers were modeled through a coupled simulation with the 1D-tool, PowerCOOL™, to solve for engine coolant and charge air temperatures. Predicted temperatures at the entry and exit plane of the radiator and charge-air-cooler were compared to thermocouple measurements. In addition, a detailed flow analysis was performed to highlight regions of fan shroud loss and cooling airflow recirculation. This information was then used to improve cooling performance in a knowledge-based incremental design process.

Presented are simulations of cooling airflow and external aerodynamics over Land Rover LR3 and Ford Mondeo cars under several driving conditions. The simulations include details of the external flow field together with the flow in the under-hood and underbody areas. Shown is the comparison between the predicted and measured coolant inlet temperature in the radiator, drag and lift coefficients, temperature distribution on the radiator front face, and wake total pressure distribution. Very good agreement is observed. In addition, shown is the complex evolution of the temperature field in the idle case with strong under-hood recirculation. It is shown that the presented Lattice-Boltzmann Method based approach can provide accurate predictions of both cooling airflow and external aerodynamics.

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.

Utilization of direct injection systems is one of the most promising technologies for fuel economy improvement for SI engine powered passenger cars. Engine performance is essentially influenced by the characteristics of the injection equipment. This paper will present CFD analyses of a swirl type GDI injector carried out with the Multiphase Module of AVL's FIRE/SWIFT CFD code. The simulations considered three phases (liquid fuel, fuel vapor, air) and mesh movement. Thus the transient behavior of the injector can be observed. The flow phenomena known from measurement and shown by previous simulation work [2, 7, 10, 11] were reproduced. In particular the simulations shown in this paper could explain the cause for the outstanding atomization characteristics of the swirl type injector, which are caused by cavitation in the nozzle hole.

Many critical thermal issues that occur in vehicles are uncovered only under more “thermally stressed” driving conditions that are transient in nature such as abruptly changing vehicle speed or turning off fan and engine. Therefore, for flow simulations to be useful in the vehicle design process, it is imperative that these simulations have the ability to accurately model long term transient thermal convection on full vehicles. Presented are simulations for a passenger vehicle driving at 60 kilometers per hour followed by a complete stop. The simulations were performed using a coupling between the flow and thermal solver and in the process, taking into account convection, conduction and radiation effects. Temperature predictions were made both under steady state conditions and during the key-off. Good agreement with the measurements was observed.

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.

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.

Cavitation induced cylinder liner erosion can be a significant durability problem in high power density diesel engines. It is typically discovered in the field, thus causing costly redesigns. The application of a predictive simulation to analyze the liner cavitation process upfront could identify the problem early on and enable significant savings. Hence, this work investigates the ability of the computational fluid dynamics (CFD) multiphase flow simulation tool to handle vibration induced cavitation. A flow of liquid through a U-shaped duct is analyzed, where a middle segment of the duct is set to vibrate in a manner resembling vibration of the cooling jacket walls in an internal combustion engine. Velocity, pressure and vapor concentration fields are tracked for two cases, distinguished by different frequencies of duct wall vibration.

In a tiered cooling pack, the airflow through the individual heat exchangers is determined by the package and aperture lay out. Each heat exchanger rejects heat as a function of the internal coolant flows, the cooling airflow and the air temperature. In a typical automotive cooling pack, the cooling airflow will be non-uniform in velocity and temperature due to fans, aperture geometry, exterior flows, heat exchangers and recirculation. In a drive cycle, these boundary conditions will change with vehicle operating conditions like vehicle speed, engine speed, ambient temperature, and altitude. These non-uniform conditions on the cooling pack can lead to significant errors when uniform boundary conditions are assumed in a transient simulation. This error is commonly corrected using vehicle test data. A predictive approach, which eliminates the need for correlation vehicle testing, is presented.

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.