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Today there are a large variety of drag-reducing devices for heavy trucks that are commonly used, for example, roof deflectors, cab side extenders and chassis fairings. These devices are often proven to be efficient, reducing the total aerodynamic resistance for the vehicle. However, the drag-reducing devices are usually identical for a specific pulling vehicle, independent of the layout of the vehicle combination. In this study, three vehicle combinations were analyzed. The total length of the vehicles varied between 10.10 m and 25.25 m. The combinations consisted of a rigid truck in combination with one or two cargo units. The size of the gap between the cargo units differed between the vehicle combinations. There were also three configurations of each vehicle combination with different combinations of roof deflector and cab side extenders, yielding a total number of nine configurations.

This paper presents results and a Computational Fluid Dynamics (CFD) method for simulation of a detailed louvered fin for a multi-louvered compact heat-exchanger. The airflow was angled at 90°, +30° and −30° relative to the heat-exchanger to evaluate changes in static pressure drop and airflow characteristics. The investigation was based on three heat-exchangers with thicknesses of 52mm and two of 19mm. One period of a detailed louvered fin was simulated for two airflows for each heat-exchanger. The pressure drop data was thereafter compared to experimental data from a full-size heat-exchanger. From the pressure drop and the airflow characteristic results recommendations were made that those kinds of simulations could be defined as steady state, and with the kω-SST turbulence model. For the same heat-exchanger angle the airflow within the core was similar, with a turbulent characteristic behind it.

Nowadays, much focus for vehicle manufacturers is directed towards improving the energy efficiency of their products. The aerodynamic drag constitutes one major part of the total driving resistance for a vehicle travelling at higher speeds. In fact, above approximately 80km/h the aerodynamic drag is the dominating resistance acting on a truck. Hence the importance of reducing this resistance is apparent. Cooling drag is one part of the total aerodynamic drag, which arises from air flowing through the heat exchangers, and the irregular under-hood area. When using Computational Fluid Dynamics (CFD) in the development process it is of great importance to ensure that the methods used are accurately capturing the physics of the flow. This paper deals with comparative studies between CFD and wind-tunnel tests. In this paper, two comparative studies are presented.

This investigation is a continuing analysis of the cooling performance and aerodynamic properties of a rear-mounted cooling module on a semi-generic commercial vehicle, which was carried out by Larsson, Löfdahl and Wiklund. In the previous study two designs of the cooling package installation were positioned behind the rear wheelhouse and the results were compared to a front-mounted cooling module. The investigation was mainly focused on a critical cooling situation occurring at lower vehicle speeds for a local distribution vehicle. The conclusion from the study was that the cooling performance for one of the rear-mounted installation was favorable compared to the front-mounted cooling package. This was mainly due to the low vehicle speed, the high fan speed and to fewer obstacles around the cooling module resulting in a lower system restriction within the installation.

The aim of the study was to investigate the cooling performance of two cooling package positions for distribution vehicles by using Computational Fluid Dynamics. The first cooling package was positioned in the front of the vehicle, behind the grill and the second position was at the rear of the vehicle. Each case was evaluated by its cooling performance for a critical driving situation and its aerodynamic drag at 90 km/h, where the largest challenge of an alternative position is the cooling air availability. The geometry used was a semi-generic commercial vehicle, based on a medium size distribution truck with a heat rejection value set to a fixed typical level at maximum power for a 13 litre Euro 6 diesel engine. The heat exchangers included in the study were the air conditioning condenser, the charge air cooler and the radiator. It was found that the main problem with the rear mounted cooling installation was the combination of the fan and the geometry after the fan.

Owing to increased interest in blended fuels for automotive applications, a great deal of understanding is sought for the behavior of multicomponent fuel sprays. This sets a new requirement on spray model since the volatility of the fuel components in a blend can vary substantially. It calls for careful solution to implement the differential evaporation process concerning thermodynamic equilibrium while maintaining a robust solution. This work presents the Volvo Stochastic Blob and Bubble (VSB2) spray model for multicomponent fuels. A direct numerical method is used to calculate the evaporation of multicomponent fuel droplets. The multicomponent fuel model is implemented into OpenFoam CFD code and the case simulated is a constant volume combustion vessel. The CFD code is used to calculate liquid penetration length for surrogate diesel (n-dodecane)-gasoline (iso-octane) blend and the result is compared with experimental data.

This paper presents pressure drops and heat transfer rates for compact heat exchangers, where the heat exchangers are angled 90°, 60°, 30° and 10° relative to the incoming airflow. The investigation is based on three heat exchangers with thicknesses of 19mm and 52mm. Each heat exchanger was mounted in a duct, where it was tested for thermal and isothermal conditions. The inlet temperature of the coolant was defined to two temperatures; ambient temperature and 90°C. For the ambient cases the coolant had the same temperature as the surrounding air, these tests were performed for five airflow rates. When the coolant had a temperature of 90°C a combination of five coolant flow rates and five airflow rates were tested. The test set-up was defined as having a constant cross-section area for 90°, 60° and 30° angles, resulting in a larger core area and a lower airspeed through the core, for a more inclined heat exchanger.

Wheel and underbody aerodynamics have become important topics in the search to reduce the aerodynamic drag of the heavy trucks. This study aims to investigate, experimentally as well as numerically, the local flow field around the wheels and in the wheel housing on a heavy truck; and how different approaches to modelling the wheel rotation in CFD influences the results. Emphasis is on effects due to ground simulation, and both moving ground and wheel rotation were requirements for this study. A 1:4-scale model of part of a heavy truck geometry has been developed. During the model design numerical simulations were used to optimise the shape, in order to replicate the flow field near the wheel of a complete truck. This was done by changing the flow angles of the incoming and exiting flows, and by keeping the mass flow rates in to, and out of, the wheel housing at the same ratios as in a reference full size vehicle.

The aim with this investigation was to study the aerodynamic properties of truck-trailer combinations of varying lengths. The aerodynamic properties of the combinations were evaluated in order to study similarities and differences in the flow field between different configurations. By the use of Computational Fluid Dynamics (CFD) six different types of truck-trailer combinations used for long hauling have been evaluated. The combinations have a total length varying between 10.10 m and 25.25 m and consist of either a tractor or rigid truck in combination with one or two cargo units. All of the combinations are commonly found on roads in Sweden and several other countries in Europe. The results from the simulations show that the aerodynamic properties differ significantly for the truck-trailer combinations. It was found that the longer vehicle combinations are much more sensitive to yaw conditions than the shorter combinations.