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Fuel efficiency for tractor/trailer combinations continues to be a key area of focus for manufacturers and suppliers in the commercial vehicle industry. Improved fuel economy of vehicles in transit can be achieved through reductions in aerodynamic drag, tire rolling resistance, and driveline losses. Fuel economy can also be increased by improving the efficiency of the thermal to mechanical energy conversion of the engine. One specific approach to improving the thermal efficiency of the engine is to implement a waste heat recovery (WHR) system that captures engine exhaust heat and converts this heat into useful mechanical power through use of a power fluid turbine expander. Several heat exchangers are required for this Rankine-based WHR system to collect and reject the waste heat before and after the turbine expander. The WHR condenser, which is the heat rejection component of this system, can be an additional part of the front-end cooling module.

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.

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.

Numerical simulation of aerodynamics for vehicle development is used to meet a wide range of performance targets, including aerodynamic drag for fuel efficiency, cooling flow rates, and aerodynamic lift for vehicle handling. The aerodynamic flow field can also be used to compute the advection of small particles such as water droplets, dust, dirt, sand, etc., released into the flow domain, including the effects of mass, gravity, and the forces acting on the particles by the airflow. Previous efforts in this topic have considered the water sprays ejected by rotating wheels when driving on a wet road. The road spray carries dirt particles and can obscure the side and rear glazing. In this study, road sprays are considered in which the effects of additional water droplets resulting from splashing and dripping of particles from the wheel house and rear under body are added to help understand the patterns of dirt film accumulation on the side glass and rear glass.

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.

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.

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.

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.

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.

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 Tesla Motors Model S has been designed from a clean sheet of paper to prove that no compromises to a desirable aesthetic style and world class driving experience are necessary in order to be energy efficient. Aerodynamic optimization is a major contributor to the overall efficiency of an electric vehicle and the close integration of the Design and Engineering groups at Tesla Motors was specifically arranged to process design iterations quickly and enable the fully informed development of the exterior surfaces at a very rapid pace. Clear communication and a working appreciation of each other's priorities were vital to this collaboration and underpinning this was extensive use of the powerful analysis and visualization capabilities of CFD. CFD was used to identify and effectively communicate the nature of beneficial and detrimental design features and to find ways to enhance or ameliorate them accordingly.

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.

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.

Ground transportation industry contributes to about 14% of the global CO2 emissions. Therefore, any effort in reducing global CO2 needs to include the design of cleaner and more energy efficient vehicles. Their design needs to be optimized for the real-world conditions. Using wind tunnels that can only reproduce idealized conditions quite often does not translate into real-world on-road CO2 reduction and improved energy efficiency. Several recent studies found that very rarely can the real-world environment be represented by turbulence-free conditions simulated in wind tunnels. The real-world conditions consist of both transversal flow velocity component (causing an oncoming yaw flow) as well as large-scale turbulent fluctuations, with length scales of up to many times the size of a vehicle. The study presented in this paper shows how the realistic wind affects the aerodynamics of the vehicle.

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.