Search Results

Abstract A Direct Yaw-Moment Control (DYC) logic for a rear-wheel-drive electric-powered vehicle is proposed. The vehicle is a Formula SAE (FSAE) type race car, with two electric motors powering each rear wheel. Vehicle baseline balance is neutral at low speeds, for increased maneuverability, and increases understeering at high speeds (due to the aerodynamic configuration) for stability. A controller that can deal with these yaw response variations, modelling uncertainties, and vehicle nonlinear behavior at limit handling is proposed. A two-level control strategy is considered. For the upper level, yaw rate and sideslip angle are considered as feedback control variables and a cubic-error Proportional Derivative (PD) controller is proposed for the feedback control. For the lower level, a traction control algorithm is used, together with the yaw moment requirement, for torque allocation.

Abstract A major contributor to fatal vehicle crashes is hydroplaning, which has traditionally been reported at a specific vehicle speed for a given operating condition. However, hydroplaning is a complex phenomenon requiring a holistic, probabilistic, and multidisciplinary approach. The objective of this article is to develop a probabilistic approach to predict Hydroplaning Potential and Risk that integrates fundamental understanding of the interdependent factors: hydrology, fluid-solid interactions, tire mechanics, and vehicle dynamics. A novel theoretical treatment of Hydroplaning Potential and Risk is developed, and simulation results for the prediction of water film thickness and Hydroplaning Potential are presented. The results show the advantages of the current approach which could enable the improvement of road, vehicle, and tire design, resulting in greater safety of the traveling public.

Abstract In this work, the refinement of a phenomenological turbulence model developed in recent years by the authors is presented in detail. As known, reliable information about the underlying turbulence intensity is a mandatory prerequisite to predict the burning rate in phenomenological combustion models. The model is embedded under the form of “user routine” in the GT-Power™ software. The main advance of the proposed approach is the potential to describe the effects on the in-cylinder turbulence of some geometrical parameters, such as the intake runner orientation, the compression ratio, the bore-to-stroke ratio, and the valve number. The model is based on three balance equations, referring to the mean flow kinetic energy, the tumble vortex momentum, and the turbulent kinetic energy (3-eq. concept). An extended formulation is also proposed, which includes a fourth equation for the dissipation rate, allowing to forecast also the integral length scale (4-eq. concept).

Abstract A wind-tunnel study was undertaken to investigate the drag reduction potential of two-truck platooning, in the context of understanding some of the factors that may influence the potential fuel savings and greenhouse-gas reductions. Testing was undertaken in the National Research Council Canada 2 m × 3 m Wind Tunnel with two 1/15-scale models of modern aerodynamic tractors paired with dry-van trailers configured with and without combinations of side-skirts and boat-tails. Separation distances of 0.14, 0.28, 0.49, 0.70 and 1.04 vehicle lengths were tested (3 m, 6 m, 10.5 m, 15 m, and 22.5 m full scale). Additionally, within-lane lateral offsets up to 0.31 vehicle widths (0.8 m full scale) were evaluated, along with a full-lane offset of 1.42 vehicle widths (3.7 m full scale). This study has made use of a wind-averaged-drag coefficient as the primary metric for evaluating the effect of vehicle platooning.

Abstract The transient surface pressure over a full-scale, operational compact automotive vehicle—a Volkswagen Golf 7—exposed to transient crosswinds with relative yaw angles of β = 22-45° has been characterized. Experiments were performed at the BMW side-wind facility in Aschheim, Germany. Measurements of the incoming flow in front of the car were taken with eleven five-hole dynamic pressure probes, and separately, time-resolved surface pressure measurements at 188 locations were performed. Unsteady characteristics (not able to be identified in quasi-steady modelling) have been identified: the flow in separated regions on the vehicle’s leeward side takes longer to develop than at the windward side, and spatially, the vehicle experiences local crosswind as it gradually enters the crosswind.

Abstract In this article, a methodology is presented to assess the influence of time-averaged deformations on a production car of the 2018 A-class due to wind load. Exemplary, the deformations of the front and rear bumper are investigated. The aerodynamic development of vehicles at Mercedes-Benz is divided into several phases. When comparing, force coefficients differences can be observed between these distinct hardware stages as well as when comparing steady-state simulations to wind tunnel measurements. In early phases when prototype vehicles are not yet available, so-called aero foam models are used. These are well-defined full-sized vehicle models as the outer skin is milled from Polyurethane. Important aerodynamic characteristics such as an engine compartment with a cooling module, deflecting axles with rotatable wheels, and underbody covers are represented.

Abstract Vehicle tire performance is an important consideration for vehicle handling, stability, mobility, and ride comfort, as well as durability. All forces exerted on the vehicle, except aerodynamic forces, are transferred to the contact regions between the road and tires. As one of the most famous empirical tire models, the Magic Formula (MF) model is widely used in vehicle ride comfort and handling stability simulations because of its ability to characterize the dynamic characteristics of tires. However, it is difficult to quickly and accurately identify the MF model that contains many parameters and highly nonlinear characteristics. This article introduces a homotopy optimization methodology to identify the MF tire model parameters based on weighted orthogonal residuals, with a morphing parameter used to lead the algorithm to the optimal global solution and avoids local convergence.

Abstract In this article, the method based on the combination of the acoustic perturbation equations and the statistical energy analysis has been used to simulate and optimize the interior aerodynamic noise of a large sport utility vehicle model. The reliability of the method was verified by comparing the analysis results with the wind tunnel test. Influenced by the main noise sources such as A-pillar, exterior rearview mirror, and front sidewindow, the wind noise of the model was significantly greater than that of the same class. To improve the wind noise performance, the side mirror was optimized with the method, including the minimum distance between the rearview mirror and the triangle trim cover, the angle between the rearview mirror and the front sidewindow, and the shell groove of the rearview mirror. The simulation results show that the overall sound pressure level in the car decreases by 2.12 dBA and the articulation index increases by 4.04% after optimization.

Abstract The appearance of an automobile is anything but unimportant for the owner. This applies to the acquisition as well as the keeping. In this context, the avoidance of corrosion is a fundamental part of the user’s satisfaction of a company. The body design can be modified to optimize drainage and reduce the risk of corrosion, improving the owner’s satisfaction with the purchase of the automobile. During the proof of concept of water management, as part of the process of development, physical prototypes are state of the art. At this point in the development process, every necessary change is expensive and time consuming. Virtual methods are able to support the development in earlier steps and thus reduce costs. The conventional Computational Fluid Dynamics (CFD) methods could not handle the simulation of a full car in the rain or water passage properly due to much higher computation efforts and deviations from the experiments.

Abstract Autonomous Vehicle (AV) technology has the potential to fundamentally transform the automotive industry, reorient transportation infrastructure, and significantly impact the energy sector. Rapid progress is being made in the core artificial intelligence engines that form the basis of AV technology. However, without a quantum leap in testing and verification, the full capabilities of AV technology will not be realized. Critical issues include finding and testing complex functional scenarios, verifying that sensor and object recognition systems accurately detect the external environment independent of weather conditions, and building a regulatory regime that enables accumulative learning. The significant contribution of this article is to outline a novel methodology for solving these issues by using the Florida Poly AV Verification Framework (FLPolyVF).

Abstract A computational fluid dynamics (CFD) and wind tunnel investigation of a human powered vehicle (HPV), designed by the Velo Racing Team at Ostfalia University, is undertaken to analyse the Eco-body’s drag efficiency. Aimed at competing in a high profile HPV speed record competition, the vehicle’s aerodynamic efficiency is shown to compare well with successful recent eco-body designs. Despite several limitations, newly obtained wind tunnel data shows that the corresponding CFD simulations offer an effective tool for analysing and refining the HPV design. It is shown that, in particular, the design of the rear wheel fairings, as well as the ride height of the vehicle, may be optimised further. In addition, refinements to the CFD and wind tunnel methodologies are recommended to help correlation.

Abstract The turboshaft engine performance is closely related to the helicopter’s design, and because of its location beneath the helicopter’s main rotor, it has unique features that distinguish it from other families of gas turbine engines. The impact of the engine suction and main rotor’s blow in different flight regimes and climatic conditions lead to variations in speed, pressure, and temperature at the inlet of the turboshaft engines, which, in turn, will affect the design of the engine cycle. Therefore, in this article, the equations governing the airflow for turboshaft engines are enhanced to incorporate these effects. The equations in this article are derived using aerodynamics, flight dynamics, helicopter, and turboshaft design to lend the inlet velocity of the engine. In order to validate the analytical outcomes of these equations, a computational fluid dynamics (CFD) analysis is carried out to evaluate the turbulent flow at the T700-GE turboshaft inlet.

Abstract Emissions development work for gasoline aftertreatment systems is often conducted in a laboratory on a chassis dynamometer. In this situation, extractive sample lines are frequently connected to the aftertreatment system before and after various components, such as a three-way catalyst, selective catalytic reduction substrate, and the like. This is done to measure the conversion efficiency of the aftertreatment system components as a function of time. The time series exhaust component concentration data, also referred to as continuous data, are combined with a measure of exhaust volumetric flowrate and used to calculate mass-based emissions. As gasoline powertrains become cleaner and produce lower levels of criteria emissions, the proximity (i.e., colocated or not colocated) of the volumetric flowrate and concentration measurements may affect the accuracy of the overall mass emission calculation.

Abstract In this study, two types of drag reduction devices (a horizontal plate, and a vertical plate) are used to weaken the downwash of the upper flow and c-pillar vortex of the DrivAer notchback model driving at high speed (140 km/h). By analyzing and comparing 15 cases in total, the aerodynamic drag reduction mechanism can be used in the development of vehicles. First, various CFD simulation conditions of a baseline model were compared to determine the analysis condition that efficiently calculates the correct aerodynamic drag. The vertical plate and horizontal plate applied in the path of the c-pillar vortex and downwash suppressed vortex development and induced rapid dissipation. As a result, the application of a 50-mm wedge-shaped vertical plate to the trunk weakened the vortex and reduced the drag by 3.3% by preventing the side flow from entering the trunk top.

Abstract The computational analysis and design of an aerodynamics system for a Formula SAE vehicle is presented. The work utilizes a stochastic-approximation optimization (SAO) process coupled with a computational fluid dynamics (CFD) solver. The methodology is presented in a general manner, and is applicable to other complex parametrizable systems. A mix of discrete and continuous variables is established to define the airfoil profile, location, sizing and angle of all wing elements. Objectives are established to maximize downforce, minimize drag and maintain a target vehicle aerodynamic balance. A combination of successive 2D and 3D CFD evaluations have achieved vehicle aerodynamic performance targets at a minimal computational cost.

Abstract Fuel consumption is at an all-time high, with crude oil set to get depleted in the next two decades. Drag force is one of the major components responsible for decreasing mileage and thus increasing fuel consumption in vehicles. Using passive modifications such as spherical depressions on the body surface, aerodynamic drag experienced by passenger vehicles can be significantly reduced. Spherical depressions are designed to delay flow separation, following which the wake size is reduced, resulting in a decrease in drag force. In this study, computer-aided design (CAD) models of generalized lightweight vehicles are made with dimples at the sides of the car, having a diameter of 60 mm and a center-to-center distance of 90 mm. Several models are created having depression aspect ratios (ARs) of 2, 4, 6, and 8, and each model is simulated to velocities of 22 m/s, 24 m/s, 26 m/s, 28 m/s, and 30 m/s.

Abstract The aerodynamic optimization process of cars requires multiple iterations between aerodynamicists and stylists. Response surface modeling and reduced-order modeling (ROM) are commonly used to eliminate the overhead due to computational fluid dynamics (CFD), leading to faster iterations. However, a primary drawback of these models is that they can work only on the parameterized geometric features they were trained with. This study evaluates if deep learning models can predict the drag coefficient (cd ) for an arbitrary input geometry without explicit parameterization. We use two similar data sets (total of 1000 simulations) based on the publicly available DrivAer geometry for training. We use a modified U-Net architecture that uses signed distance fields (SDF) to represent the input geometries. Our models outperform the existing models by at least 11% in prediction accuracy for the drag coefficient.

Abstract A two-dimensional model of three elements, high-lift airfoil, was designed at a Reynolds number of ?????? using computational fluid dynamics (CFD) to generate downforce with good lift-to-drag efficiency for a formula student open-wheel race car basing on the nominal track speeds. The numerical solver uses the Reynolds-averaged Navier-Stokes (RANS) equation model coupled with the Langtry-Menter four-equation transition shear stress transport (SST) turbulence model. Such model adds two further equations to the ?? − ?? SST model resulting in an accurate prediction for the amount of flow separation due to adverse pressure gradient in low Reynolds number flow. The ?? − ?? SST model includes the transport effects into the eddy-viscosity formulation, whereas the two equations of transition momentum thickness Reynolds number and intermittency should further consider transition effects at low Reynolds number.

Abstract The water injection is one of the technologies assessed in the development of new internal combustion engines fulfilling new emission regulation and policy on Auxiliary Emission Strategy assessment. Besides all the positive aspects about the reduction of mixture temperature at top dead center and exhaust gases temperature at turbine inlet, it is well known that the water vapor acts as a mixture diluter, thus diminishing the reactants burning rate. A common methodology employed for the Reynolds-Averaged Navier-Stokes Computational Fluid Dynamics (RANS CFD) simulation of the reciprocating internal combustion engines’ turbulent combustion relies on the flamelet approach, which requires knowledge of the Laminar Flame Speed (LFS) and thickness. Typically, these properties are calculated by means of correlation laws, but they do not keep into account the presence of water mass fraction. A more precise methodology for the definition of both the LFS and thickness is thus required.

Abstract This study investigates the use of a road weather model (RWM) as a virtual sensing technique to assist autonomous vehicles (AVs) in driving safely, even in challenging winter weather conditions. In particular, we investigate how the AVs can remain within their operational design domain (ODD) for a greater duration and minimize unnecessary exits. As the road surface temperature (RST) is one of the most critical variables for driving safety in winter weather, we explore the use of the vehicle’s air temperature (AT) sensor as an indicator of RST. Data from both Road Weather Information System (RWIS) stations and vehicles measuring AT and road conditions were used. Results showed that using only the AT sensor as an indicator of RST could result in a high number of false warnings, but the accuracy improved significantly with the use of an RWM to model the RST.