Search Results

As part of the United States Department of Energy's SuperTruck program, Volvo Trucks and its partners were tasked with demonstrating 50% improvement in overall freight efficiency for a tractor-trailer, relative to a best in class 2009 model year truck. This necessitated that significant gains be made in reducing aerodynamic drag of the tractor-trailer system, so trailer side-skirts and a trailer boat-tail were employed. A Lattice-Boltzmann based simulation method was used in conjunction with a Kriging Response Surface optimization process in order to efficiently describe a design space of seven independent parameters relating to boat-tail and side-skirt dimensions, and to find an optimal configuration. Part 1 concerns a fully-skirted tractor-trailer system, and consists of an initial phase of optimization, followed by a mid-project re-evaluation of constraints, and an additional period of optimization.

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 development of a new Dongfeng Heavy truck had very strict targets for fuel consumption. As the aerodynamic drag plays a crucial role for the fuel consumption, a low drag value had to be achieved. It was therefore essential to include evaluation and optimization of the aerodynamics in the development process. Because wind tunnel facilities were not available, the complete aerodynamics development was based on digital simulation. The major portion of the aerodynamic optimization was carried out during the styling phase where mirrors, sun visor, front bumper and aero devices were optimized for drag reduction. For optimizing corner vanes and mud guards, self-soiling from the wheel spray was included in the analysis. The aero results did also show that cooling air flow rates are sufficiently high to ensure proper cooling. During the detailed engineering phase an increase of the drag above the target required further optimization work to finally reach the target.

Design and evaluation of construction equipments and vehicles in the construction industry constitute a very important but expensive and time consuming part of the engineering process on account of large number of variants of prototypes and low production volumes associated with each variant. In this article, we investigate an alternative approach to the hardware testing based design process by implementing a Computational Fluid Dynamics (CFD) simulation based methodology that has the potential to reduce the cost and time of the entire design process. The simulation results were compared with test data and good agreement was observed between test data and simulation.

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.