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Abstract Autonomous vehicles (AVs) rely heavily upon their perception subsystems to “see” the environment in which they operate. Unfortunately, the effect of variable weather conditions presents a significant challenge to object detection algorithms, and thus, it is imperative to test the vehicle extensively in all conditions which it may experience. However, the development of robust AV subsystems requires repeatable, controlled testing—while real weather is unpredictable and cannot be scheduled. Real-world testing in adverse conditions is an expensive and time-consuming task, often requiring access to specialist facilities. Simulation is commonly relied upon as a substitute, with increasingly visually realistic representations of the real world being developed.

Abstract This article presents a workflow for aerodynamic optimization of vehicles that for the first time combines the adjoint method and the efficient global optimization (EGO) algorithm in order to take advantage of both the gradient-based and gradient-free methods for aerodynamic optimization problems. In the workflow, the adjoint method is first applied to locate the sensitive surface regions of the baseline vehicle with respect to the objective functions and define a proper design space with reasonable design variables. Then the EGO algorithm is applied to search for the optimal site in the design space based on the expected improvement (EI) function. Such workflow has been applied to minimize the aerodynamic drag for a mass-produced electric vehicle. With the help of STAR-CCM+ and its adjoint solver, sensitive surface regions with respect to the aerodynamic drag are first located on the vehicle.

Abstract This article introduces a finite element (FE) approach to determine tire deformation and its effect on open-wheel race car aerodynamics at high vehicle velocities. In recent literature tire deformation was measured optically. Combined loads like accelerating at a corner exit are difficult to reproduce in wind tunnels and require several optical devices to measure the tire deformation. In contrast, an FE approach is capable of determining the tire deformation in combined load states accurately. Additionally, the temperature influence on tire deformation is investigated. The FE tire model was validated using three-dimensional (3D) scan measurements; stiffness measurements in the vertical, lateral, and longitudinal direction; and the change of loaded radius with speed at different loads, respectively. The deformed shape of the tire of the FE model was used in a computational fluid dynamics (CFD) simulation.

Abstract Multi-agent autonomous racing still remains a largely unsolved research challenge. The high-speed and close proximity situations that arise in multi-agent autonomous racing present an ideal condition to design algorithms which trade off aggressive overtaking maneuvers and minimize the risk of collision with the opponent. In this article we study a two-vehicle autonomous racing setup and present AutoPass—a novel framework for overtaking in a multi-agent setting. AutoPass uses the structure of an automaton to break down the complex task of overtaking into sub-maneuvers that balance overtaking likelihood and risk with safety of the ego vehicle. We present real-world implementation of 1/10-scale autonomous racing cars to demonstrate the effectiveness of AutoPass for the overtaking task.

Abstract Formula Student Driverless (FSD) challenges engineering students to develop autonomous single-seater race cars in a quest to bring about more graduates who are well prepared to solve the real-world problems associated with autonomous driving. In this article, we present the software stack of KA-RaceIng’s entry to the 2019 competitions. We cover the essential modules of the system, including perception, localization, mapping, motion planning, and control. Furthermore, development methods are outlined, and an overview of the system architecture is given. We conclude by presenting selected runtime measurements, data logs, and competition results to provide an insight into the performance of the final prototype.

Abstract TOC

Abstract When commercial vehicles drive in a mountainous area, the complex road condition and long slopes cause frequent acceleration and braking, which will use 25% more fuel. And the brake temperature rises rapidly due to continuous braking on the long-distance downslopes, which will make the brake drum fail with the brake temperature exceeding 308°C [1]. Meanwhile, the kinetic energy is wasted during the driving progress on the slopes when the vehicle rolls up and down. Our laboratory built a model that could calculate the distance from the top of the slope, where the driver could release the accelerator pedal. Thus, on the slope, the vehicle uses less fuel when it rolls up and less brakes when down. What we do in this article is use this model in a real vehicle and measure how well it works.

Abstract The airline industry faces a crisis in the future as consumer demand is increasing, but the environmental effects and depleting resources of kerosene mean that growth is unsustainable. Hydrogen is touted as the leading candidate to replace kerosene, but it needs significant technological and economical endeavors. In such a scenario, cryogenic liquid hydrogen (LH2) is predicted to be the most feasible method of using hydrogen. The major challenge of LH2 as an aircraft fuel is that it requires approximately four times the storage volume of kerosene—due to its lower density. Thus the design of cryogenic storage tanks to handle larger quantities of fuel is becoming increasingly important. But the increase in drag associated with larger storage tanks causes an increase in fuel consumption. Hence, this paper aims to evaluate the aerodynamic performance of different storage configurations and aid in the selection of an economic and efficient storage system.

Abstract The future of heavy trucking will require greater aerodynamic improvements and will involve active and automated systems that tailor varied parameters to optimize energy efficiency over a broad operational range. Continuous advancement of accuracy and precision is needed to realize these ever-smaller aerodynamic gains and to generate more detailed aerodynamic characterizations to feed these system-wide optimizations. To accomplish this, a comprehensive aerodynamic development approach is needed and should include computational fluid dynamics, operational testing, and wind tunnel testing. In 2016, a high-fidelity 1/3 scale wind tunnel model of a tractor-trailer heavy truck was developed for Reynolds equivalent wind tunnel testing with full coverage rolling road ground simulation. The model and support system were designed and built for use in the Windshear rolling road wind tunnel.

Abstract Aerodynamic drag for road vehicles is most often assessed based on zero yaw conditions. The rise of electric vehicles in recent years put greater demand on how the vehicles perform in real-world conditions. Specifically, the aerodynamic drag performance at non-zero yaw angles has received increased attention. Various methods to calculate wind-averaged drag have been proposed. However, there have not been any studies done for the yaw distribution in China; this is important, given its diverse geographic and climatic conditions and growing number of vehicles. This study presents a methodology using probes integrated with a production vehicle to collect representative on-road data. A survey of on-road conditions in China is presented including coastal and inland provinces, different road types, and a range of traffic conditions. Using high temporal and special resolution meteorological data, the correlation between yaw angle distribution and natural wind is derived.

Abstract Aerodynamic optimization of the exterior vehicle shape is a highly multidisciplinary task involving, among others, styling and aerodynamics. The often differing priorities of these two disciplines give rise to iterative loops between stylists and aerodynamicists. Reduced-order modeling (ROM) has the potential to shortcut these loops by enabling aerodynamic evaluations in real time. In this study, we aim to assess the performance of ROM via proper orthogonal decomposition (POD) for a real-life industrial test case, with focus on the achievable accuracy for the prediction of fields and aerodynamic coefficients. To that end, we create a training data set based on a six-dimensional parameterization of a Volkswagen passenger production car by computing 100 variants with Detached-Eddy simulations (DES).

Abstract Turboprop aircraft have the capability of reversing thrust to provide extra stopping power during landing. Reverse thrust helps save the wear and tear on the brakes and reduces the landing distance under various conditions. The article explains a methodology to predict the disking drag (reverse thrust) from the Computational Fluid Dynamics (CFD) technique using Blade Element Momentum (BEM) theory and estimation of the same from high-speed taxiing trial (HSTT) and ground roll data for a turboprop aircraft using system identification techniques. One-dimensional kinematic equation was used for modeling the aircraft dynamics, and the error between measured and estimated responses was optimized using the Output Error Optimization Method (OEOM). The estimated propeller drag was matched with CFD predictions to arrive at a relation between the propeller blade pitch angle and throttle position.

Abstract Sports Utility Vehicles (SUVs) often have blunt rear end geometries for design and practicality, which is not typically aerodynamic. Drag can be reduced with a number of passive and active methods, which are generally prioritised at zero yaw, which is not entirely representative of the “on road” environment. As such, to combine a visually square geometry (at rest) with optimal drag reductions at non-zero yaw, an adaptive system that applies vertical side edge tapers independently is tested statically. A parametric study has been undertaken in Loughborough University’s Large Wind Tunnel with the ¼ scale Windsor Model. The aerodynamic effect of implementing asymmetric side tapering has been assessed for a range of yaw angles (0°, ±2.5°, ±5° and ±10°) on the force and moment coefficients.

Abstract From the fact that a propulsor consumes less power for a given thrust if the inlet air is slower, simulations are conducted for a propulsor imposed behind an airfoil as ideal boundary layer ingestion (BLI) propulsor to stand on the benefits of this configuration from the point of view of power and efficiency and to get a closer look on the mutual interaction between them. This interaction is quantified by the impact on three main sets of parameters, namely, power consumption, boundary layer properties, and airfoil performance. The position and size of the propulsor have great influence on the flow around the airfoil. Parametric studies are carried out to understand their influence. BLI propulsor directly affects the power saving and all of the pressure-dependent parameters, including lift and drag. For the present case, power saving reached 14.4% compared to the propeller working in freestream.

Abstract The First Automotive CFD Prediction Workshop was held in December 2019 at St Anne’s College at the University of Oxford with the aim to assess the ability of a broad range of computational fluid dynamics (CFD) methods to predict the flow over realistic automotive geometries. Here, results from 53 simulation data sets from 9 separate groups are analyzed for the open-source automotive DrivAer model (in the fastback and estate variants). The represented CFD approaches include Reynolds-averaged Navier-Stokes (RANS) approaches with a broad range of turbulence models, as well as scale-resolving approaches such as wall-modelled large-eddy simulation (WMLES) and hybrid RANS-LES methods (HRLM). A range of CFD codes was used, including commercial, academic, and open source. Compared to the two experimental data points, there was a large spread of CFD results. The difference between drag predictions among HRLM and RANS methods is significant, with an even larger mismatch for lift.

Abstract Solving a Minimum Lap Time Problem (MLTP), under the constraints stemming from a race car’s driving dynamics, can be considered to be state of the art. Nevertheless, when dealing with electric race vehicles as in Formula E or the Roborace competition, solving an MLTP is not enough to form an appropriate competition strategy: Maximum performance over the entire race can only be achieved by an optimization horizon spanning all the subsequent laps of a race. This results in a Minimum Race Time Problem (MRTP). To solve this, the thermodynamic and energetic limitations of the electric powertrain components must be taken into account, as exceeding them leads to safety shutdowns. Therefore, we present an Optimal Control Problem (OCP) to calculate an Energy Strategy (ES) for electric race cars, which contain physically detailed descriptions of its powertrain components. Leveraging a Sequential Quadratic Programming (SQP) solver, the OCP can be solved numerically in real time.

Abstract The traditional side mirrors on an automobile could create a substantial part of drag in the total car aerodynamic design consideration. On some concept cars, digital side mirrors (DSM) have been installed with the aim to reduce the total drag; thus the optimization study of DSM configuration becomes an important task. In this study the benchmark DrivAer fastback model is employed for optimization work of DSM via computational fluid dynamics (CFD) software and simulated with a realistic moving ground and rotating wheel conditions. In order to validate the lift and drag coefficients with existing experimental data, the wheel rotation is implemented through three different kinds of rotating methods: Moving Wall (MW), Multiple Reference Frame (MRF), and Sliding Mesh (SM), while the SM method provides the most accurate results.

Abstract The development of the technology of automated highways promises the opportunity for the vehicles to travel safely at a closer distance concerning each other. As such, vehicles moving in the wake of others experience a reduction in fuel consumption. This article investigates the effect of longitudinal distance between two passenger cars on drag coefficients numerically and experimentally. For the numerical analysis, the fluid flow at car speeds of 70, 90 and 110 km/h were examined. The Artificial Intelligence coding was applied to train an Artificial Neural Network to extend the calculated data. The optimum values for the inter-vehicle distance and the vehicle speed to assure the least drag coefficient are obtained. To support the numerical results an instrument designed and built particularly to accurately measure the fuel consumption was installed on a midsize sedan car and some field tests were carried out.

Abstract SAE guidelines for computational fluid dynamics (CFD) and wind-tunnel tests on semi-trailer trucks were complied with to investigate the influence of adding a lateral skirts device—in the lower trailer part—on the improvement of the total drag force and the airflow structure around the truck. A reduced-scale (1:28) semi-trailer truck moving at three various speeds (i.e., 50 km/h, 75 km/h, and 100 km/h) is considered in this study. A reasonable agreement between experimental and numerical results was achieved in terms of the drag force parameter with a highest relative error of about 13% obtained in the case of the lowest speed (i.e., 50 km/h) of a truck without skirts. The numerical results yielded an average drag coefficient value of 0.48, which is reduced to 0.45 when the skirt device is added to the vehicle model.

Abstract This study consists of a novel approach based on Classical Mechanics to explain the aerodynamic forces on a body in motion relating to a fluid. This new approach does not require the presence of viscosity to generate the forces and is compatible with the Kutta condition. The physical reasoning of the approach is outlined with the introduction of the aerodynamic suction effect of the body. Next, the mathematical expressions and a code that models the physical phenomena are developed. These are applied for the case of a sphere immersed in a moving fluid and then an airfoil. An initial validation of this new approach is performed by a comparison of the theoretical results and the available results of the National Advisory Committee for Aeronautics (NACA) airfoils. This new mathematical approach is especially valid for high Reynolds numbers where viscosity can be neglected.