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In this paper the effect of aerodynamic modifications that influence the unsteady aerodynamic properties of a vehicle on the response of the closed loop system driver-vehicle under side wind conditions is investigated. In today's aerodynamic optimization the side wind sensitivity of a vehicle is determined from steady state values measured in the wind tunnel. There, the vehicle is rotated with respect to the wind tunnel flow to create an angle of attack. In this approach however, the gustiness that is inherent in natural wind is not reproduced. Further, unsteady forces and moments acting on the vehicle are not measured due to the limited dynamic response of the commonly used wind tunnel balances. Therefore, a new method is introduced, overcoming the shortcomings of the current steady state approach. The method consists of the reproduction of the properties of natural stochastic crosswind that are essential for the determination of the side wind sensitivity of a vehicle.

The lattice Boltzmann (LB) method has been successfully used in conjunction with a Very Large-Eddy Simulation (VLES) turbulence modeling approach for over a decade for the accurate prediction of automotive fluid dynamics. Its success lies in the unique underlying physics that is significantly different from traditional computational fluid dynamics methods. In this paper, we provide a complete description of the method followed by a set of examples which show its use in the automotive industry. We will first provide a review of the physics and numerical methods. Here the LB method and its relationship to kinetic theory and the Navier-Stokes equations will be briefly discussed. We will summarize the strengths of LB method, especially for the solution of transient flows in extremely complex geometries. The VLES turbulence modeling method will be presented next, as well as how VLES neatly fits into the LB framework.

In automobile development, wind tunnel measurements are used to optimize fuel consumption and the vehicle's road behavior. The classic measuring technique is based on a stationary vehicle set up in the wind tunnel with stationary wheels. Relative movement between vehicle and road surface is therefore ignored. In more recent studies, measurements have been taken with improved ground simulation. For example, a belt is used instead of the stationary wind tunnel floor and the car wheels rotate. Ground simulation using a belt and rotating wheels generally leads to a reduction in flow angularity at the front wheels, in the same way as blocking the cooling air flow, whereby, as a matter of fact, the aerodynamic drag is reduced. Analogous air flow angle correlations can be established for the effect of underfloor panels.

A vehicle on the road encounters an unsteady flow due to turbulence in the natural wind, the unsteady wakes from other vehicles and as a result of traversing through the stationary wakes of road side obstacles. There is increasing concern about potential differences in aerodynamic behaviour measured in steady flow wind tunnel conditions and that which occurs for vehicles on the road. It is possible to introduce turbulence into the wind tunnel environment (e.g. by developing active turbulence generators) but on-road turbulence is wide ranging in terms of both its intensity and frequency and it would be beneficial to better understand what aspects of the turbulence are of greatest importance to the aerodynamic performance of vehicles. There has been significant recent work on the characterisation of turbulent airflow relevant to road vehicles. The simulation of this time-varying airflow is now becoming possible in wind tunnels and in CFD.

Aerodynamic efficiency plays an increasingly important role in the automotive industry, as the push for increased fuel economy becomes a larger factor in the engineering and design process. Longitudinal drag is used as the primary measure of aerodynamic performance, usually cited as the coefficient of drag (CD). This drag is created mostly by the body shape of the vehicle, but the wheel and tire system also contributes a significant portion. In addition to the longitudinal drag created by the body and wheels, rotational drag can add an appreciable amount of aerodynamic resistance to the vehicle as well. Reducing power consumption is an especially vital aspect in electric vehicle (EV) design. As the world's first luxury electric sedan, the Tesla Model S combines a premium driving experience with an electric drivetrain package that allows for unique solutions to many vehicle subsystems.

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.

In addition to the analysis of human driving behavior or the development of new advanced driver assistance systems, the high simulation quality of today’s driving simulators enables investigations of selected topics pertaining to driving dynamics. With high reproducibility and fast generation of vehicle variants the subjective evaluation process leads to a better system understanding in the early development stages. The transfer of the original on-road test run to the virtual reality of the driving simulator includes the full flexibility of the vehicle model, the maneuver and the test track, which allows new possibilities of investigation. With the opportunity of a realistic whole-vehicle simulation provided by the Stuttgart Driving Simulator new analysis of the human’s thresholds of perception are carried out.

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.

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 combination of enhanced powertrains and adapted vehicle concepts can reduce the energy demand of vehicles significantly, especially when energy conversion efficiency rises and at the same time driving resistances decrease. In addition, new powertrain concepts are able to offer extra functionality due to a growing cross-linking with chassis and vehicle body. The design of highly linked vehicles and powertrain systems requires additional new development methods in order to answer interacting questions of driving dynamics and vehicle energy efficiency at an early stage of development. In the paper a database-based simulation platform is presented which was developed at the IVK of the University of Stuttgart in cooperation with the Research Institute of Automotive Engineering and Vehicle Engines Stuttgart (FKFS). The simulation platform is used as an example to discuss mass reducing developments for various powertrain concepts.

The entire automotive industry is moving towards lower CO₂ emissions and higher energy efficiency. Especially for higher driving speeds this can be achieved by minimizing aerodynamic drag. Additionally, aerodynamic downforce is essential to maintain or even improve the handling performance of a vehicle. In order to optimize the vehicle's aerodynamic efficiency in wind tunnel tests, the boundary conditions of a vehicle driving on a road must be simulated properly. Particularly for optimizing the underbody region of a vehicle, ground simulation is an important issue in every wind tunnel. Today rolling road systems featuring one or more moving belts on the wind tunnel floor are a standard tool to simulate the complex boundary condition of a vehicle driving on the road. But generally the technical effort to measure aerodynamic forces accurately increases with improvement of the aerodynamic ground simulation.

In recent years, driving simulators have become a valuable tool in the automotive design and testing process. Yet, in the field of vehicle dynamics, most decisions are still based on test drives in real cars. One reason for this situation can be found in the fact that many driving simulators do not allow the driver to evaluate the handling qualities of a simulated vehicle. In a driving simulator, the motion cueing algorithm tries to represent the vehicle motion within the constrained motion envelope of the motion platform. By nature, this process leads to so called false cues where the motion of the platform is not in phase or moving in a different direction with respect to the vehicle motion. In a driving simulator with classical filter-based motion cueing, false cues make it considerably more difficult for the driver to rate vehicle dynamics.

Water accumulating on a vehicle's wind screen, driven over the A-pillar by a combination of aerodynamic forces and the action of the windscreen wipers, can be a significant impediment to driver vision. Surface water film, or streams, persisting in key vision areas of the side glass can impair the drivers' ability to see clearly through to the door mirror, and laterally onto junctions. Common countermeasures include: water management channels and hydrophobic glass coatings. Water management channels have both design and wind noise implications. Hydrophobic coatings entail significant cost. In order to manage this design optimisation issue a water film and wiper effect model has been developed in collaboration with Jaguar Land Rover, extending the capabilities of the PowerFLOW CFD software. This is complimented by a wind-tunnel based test method for development and validation. The paper presents the progress made to date.

In this paper the influence of different turbulent flow conditions on the aerodynamic drag of a quarter scale model with notchback and estate back rear ends is investigated. FKFS swing® (Side Wind Generator) is used to generate a turbulent flow field in the test section of the IVK model scale wind tunnel. In order to investigate the increase in drag with increasing yaw, a steady state yaw sweep is performed for both vehicle models. The shape of the drag curves vary for each vehicle model. The notchback model shows a more pronounced drag minimum at 0° yaw angle and experiences a more severe increase in drag at increasing yaw when compared to the estate back model. Unsteady time averaged aerodynamic drag values are obtained at two flow situations with different turbulent length scales, turbulence intensities, and yaw angle amplitudes. While the first one is representing light wind, the second one is recreating the presence of strong gusty wind.

This paper presents an integrated numerical and experimental approach to take best possible advantage of the common development tools at hand (1D, CFD and wind tunnel) to determine the cooling air mass flow at the different vehicle development stages. 1D tools can be used early in development when neither 3D data nor wind tunnel models with detailed underhood flow are available. A problem that has to be resolved is the dependency on input data. In particular, the pressure coefficients on the outer surface (i.e. at the air inlet and outlet region) and the pressure loss data of single components are of great importance since the amount of cooling air flow is directly linked to these variables. The pressure coefficients at the air inlet and outlet are not only a function of vehicle configuration but also of driving velocity and fan operation. Both, static and total pressure coefficient, yield different advantages and disadvantages and can therefore both be used as boundary conditions.

Within the scope of a current research project at the Research Institute of Automotive Engineering and Vehicle Engines Stuttgart (FKFS), the potential for an estimation of vehicle side slip angle and yaw rate arising from online measurement of tire forces is evaluated. Investigations focus on how the vehicle state can be determined, if in addition to wheel speeds and steering angle the tire forces currently acting on the vehicle are known. Different estimation procedures based on inverse tire models, direct integration of vehicle accelerations and closed-loop-observer are discussed. The performance is tested with data from vehicle dynamics simulation.

Investigating the crosswind behavior of passenger cars is one main research subject at the Research Institute of Automotive Engineering and Vehicle Engines Stuttgart (FKFS), an institute of the University of Stuttgart. Faced with the vehicle dynamics during stochastic crosswind, this paper is concerned with the evaluation of the crosswind behavior as experienced by the driver. Most of the evaluation criteria of crosswind are currently based on the vehicle reactions only and exclude the driver's actions. A comparison of the crosswind behavior of two vehicles at the FKFS showed a non-uniform - in some cases even contrary - evaluation when applying these criteria. This paper introduces a new approach to considering the vehicle's crosswind behavior which includes the driver's reactions. The fundamental issue of this new approach is to derive the driver's evaluation from their steering inputs when compensating for the crosswind excitation. In other words: The driver is used as a sensor.

One of the remaining challenges in the simulation of the aerodynamics of ground vehicles is the modeling of the airflows around the spinning tires and wheels of the vehicle. As in most advances in the development of simulation capabilities, it is the lack of appropriately detailed and accurate experimental data with which to correlate that holds back the advance of the technology. The flow around the wheels and tires and their interfaces with the vehicle body and the ground is a critical area for the development of automobiles and trucks, not just for aerodynamic forces and moments, and their result on fuel economy and vehicle handling and performance, but also for the airflows and pressures that affect brake cooling, engine cooling airflows, water spray management etc.

This paper presents a methodology for simulating Fluid Structure Interaction (FSI) for a typical vehicle bonnet (hood) under a range of onset flow conditions. The hood was chosen for this study, as it is one of the panels most prone to vibration; particularly given the trend to make vehicle panels lighter. Among the worst-case scenarios for inducing vibration is a panel being subjected to turbulent flow from vehicle wakes, and the sudden peak loads caused by emerging from a vehicle wake. This last case is typical of a passing manoeuvre, with the vehicle suddenly transitioning from being immersed in the wake of the leading vehicle, to being fully exposed to the free-stream flow. The transient flowfield was simulated for a range of onset flow conditions that could potentially be experienced on the open road, which may cause substantial vibration of susceptible vehicle panels.

In the automotive industry, there is a continued need to improve the development process and handle the increasing complexity of the overall vehicle system. One major step in this process is a comprehensive and complementary approach to both simulation and testing. Knowledge of the overall dynamic vehicle behavior is becoming increasingly important for the development of new control concepts such as integrated vehicle dynamics control aiming to improve handling quality and ride comfort. However, with current well-established test systems, only separated and isolated aspects of vehicle dynamics can be evaluated. To address these challenges and further merge the link between simulation and testing, the Institute of Internal Combustion Engines and Automotive Engineering (IVK), University of Stuttgart is introducing a new Handling Roadway (HRW) Test System in cooperation with The Research Institute of Automotive Engineering and Vehicle Engines Stuttgart (FKFS) and MTS Systems Corporation.