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In this paper we are presenting the concept of automated park and charge functions in different use scenarios. The main scenario is automated park and charge in production and the other use scenario is within automated valet parking in parking garages. The automated park and charge in production is developed within the scope of the publicly funded project E-Self. The central aim of the project is the development and integration of automated driving at the end-of-line in the production at Ford Motor Company's manufacturing plant in Cologne. The driving function thereby is mostly based upon automated valet driving with an infrastructure based perception and action planning. Especially for electric vehicles the state of charge of the battery is critical, since energy is needed for all testing and driving operations at end-of-line.

Homologation is an important process in vehicle development and aerodynamics a main data contributor. The process is heavily interconnected: Production planning defines the available assemblies. Construction defines their parts and features. Sales defines the assemblies offered in different markets, where Legislation defines the rules applicable to homologation. Control engineers define the behavior of active, aerodynamically relevant components. Wind tunnels are the main test tool for the homologation, accompanied by surface-area measurement systems. Mechanics support these test operations. The prototype management provides test vehicles, while parts come from various production and prototyping sources and are stored and commissioned by logistics. Several phases of this complex process share the same context: Production timelines for assemblies and parts for each chassis-engine package define which drag coefficients or drag coefficient contributions shall be determined.

The issue of greenhouse gas (GHG) emissions from the transportation sector is widely acknowledged. Recent years have witnessed a push towards the electrification of cars, with many considering it the optimal solution to address this problem. However, the substantial battery packs utilized in electric vehicles contribute to a considerable embedded ecological footprint. Research has highlighted that, depending on the vehicle's size, tens or even hundreds of thousands of kilometers are required to offset this environmental burden. Human-powered vehicles (HPVs), thanks to their smaller size, are inherently much cleaner means of transportation, yet their limited speed impedes widespread adoption for mid-range and long-range trips, favoring cars, especially in rural areas. This paper addresses the challenge of HPV speed, limited by their low input power and non-optimal distribution of the resistive forces.

As vibration and noise regulations become more stringent, numerical models need to incorporate more detailed damping treatments. Commercial frameworks, such as Nastran and Actran, allow the representation of trim components as frequency-dependent reduced impedance matrices (RIM) in frequency response analysis of fully trimmed models. The RIM is versatile enough to couple the trims to modal-based or physical components. If physical, the trim components are reduced on the physical coupling degrees of freedom (DOFs) for each connected interface. If modal, the RIMs are projected on the eigenmodes of the connected component. While a model size reduction is achieved compared to the original model, most numerical models possess an extensive number of interfaces DOFs, either modal or physical, leading to large dense RIM which triggers substantial memory and disk storage.

When travelling in an open-jet wind tunnel, the path of an acoustic wave is affected by the flow causing a shift of source positions in acoustical maps of phased arrays outside the flow. The well-known approach of Amiet attempts to correct for this effect by computing travel times between microphones and map points based on the assumption that the boundary layer of the flow, the so-called shear-layer, is infinitely thin and refracts the acoustical ray in a conceptually analogy to optics. However, in reality, the turbulent nature of both the not-so thin shear-layer and the acoustic emission process itself causes an additional smearing of sources in acoustic maps, which in turn causes deconvolution methods based on these maps - the most prominent example being CLEAN-SC - to produce certain ring effects, so-called halos, around sources.

In response to global climate change, there is a widespread push to reduce carbon emissions in the transportation sector. For the difficult to decarbonize heavy-duty (HD) vehicle sector, lower carbon intensity fuels can offer a low-cost, near-term solution for CO2 reduction. The use of natural gas can provide such an alternative for HD vehicles while the increasing availability of renewable natural gas affords the opportunity for much deeper reductions in net-CO2 emissions. With this in consideration, the US National Renewable Energy Laboratory launched the Natural Gas Vehicle Research and Development Project to stimulate advancements in technology and availability of natural gas vehicles. As part of this program, Southwest Research Institute developed a hybrid-electric medium-HD vehicle (class 6) to demonstrate a substantial CO2 reduction over the baseline diesel vehicle and ultra-low NOx emissions.

It is important to accurately predict the aerodynamic properties for designing applications which involves fluid flows, particularly in the aerospace industry. Traditionally, this is done through complex numerical simulations, which are computationally expensive, resource-intensive and time-consuming, making them less than ideal for iterative design processes and rapid prototyping. Machine learning, powered by vast datasets and advanced algorithms, offers an innovative approach to predict airfoil characteristics with remarkable accuracy, speed, and cost-effectiveness. Machine learning techniques have been applied to fluid dynamics and have shown promising results. In this study, machine learning model called the back-propagation neural network (BPNN) is used to predict key aerodynamic coefficients of lift and drag for airfoils.

Launch vehicle structures in course of its flight will be subjected to dynamic forces over a range of frequencies up to 2000 Hz. These loads can be steady, transient or random in nature. The dynamic excitations like aerodynamic gust, motor oscillations and transients, sudden application of control force are capable of exciting the low frequency structural modes and cause significant responses at the interface of launch vehicle and satellite. The satellite interface responses to these low frequency excitations are estimated through Coupled Load Analysis (CLA). The analysis plays a crucial role in mission as the satellite design loads and Sine vibration test levels are defined based on this. The perquisite of CLA is to predict the responses with considerable accuracy so that the design loads are not exceeded in the flight. CLA validation is possible by simulating the flight experienced responses through the analysis.

Launch vehicles are vulnerable to aeroelastic effects due to their lightweight, flexible, and higher aerodynamic loads. Aeroelasticity research has therefore become an inevitable concern in the development of the Reusable Launch Vehicle (RLV). RLV is the space analogy of an aircraft, a unanimous solution to achieve more affordable access to space. The lightweight control surface of the RLV signifies the relevance of the study on control effectiveness. It is the capability of a control surface such as an elevon or rudder to produce aerodynamic forces and moments to change the launch vehicle's orientation and maneuver it along the intended flight path. The static aeroelastic problem determines the efficiency of control, aircraft trim behaviour, static stability, and maneuvering quality in steady flight conditions. In this study, static aeroelastic analysis was performed on a typical RLV using MSC/NASTRAN inbuilt aerodynamics.

Abstract : In any human space flight program, safety of the crew is of utmost priority. In case of exigency during atmospheric flight, the crew is safely and quickly rescued from the launch vehicle using Crew escape system. Crew escape system is a crucial part of the Human Space flight vehicle which carries the crew module away from the ascending launch vehicle by firing its rocket motors (Pitch Motor (PM), Low altitude Escape Motor (LEM) and High altitude Escape Motor (HEM)). The structural loads experienced by the crew escape system during the mission abort are severe as the propulsive forces, aerodynamic forces and inertial forces on the vehicle are significantly high. Since the mission abort can occur at anytime during the ascent phase of the launch vehicle, trajectory profiles are generated for abort at every one second interval of ascent flight time considering several combinations of dispersions on various propulsive parameters of abort motors and aero parameters.

A structural load estimating methodology was developed for the RLV-TD HEX-01 mission, the maiden winged body technology demonstrator vehicle of ISRO. The technique characterizes atmospheric regime of flight from vehicle loads perspective and ensures adequate structural margin considering atmospheric variations and system level perturbations. Primarily the method evaluates time history of station loads considering effects of vehicle dynamics and structural flexibility. Station loads in the primary structure are determined by superposition of quasi-static aerodynamic loads, dynamic inertia loads, control surface loads and propulsion system loads based on actual physics of the system. Spatial aerodynamic distributions at various Mach numbers along the trajectory have been used in the study. Argumentation in aerodynamic loads due to vehicle flexibility is assessed through the use of spatial aerodynamic distributions.

Severe problem of aerodynamic heating and drag force are inherent with any hypersonic space vehicle like space shuttle, missiles etc. For proper design of vehicle, the drag force measurement become very crucial. Ground based test facilities are employed for these estimates along with any suitable force balance as well as sensors. There are many sensors (Accelerometer, Strain gauge and Piezofilm) reported in the literature that is used for evaluating the actual aerodynamic forces over test model in high speed flow. As per previous study, the piezofilm also become an alternative sensor over the strain gauges due to its simple instrumentation. For current investigation, the piezofilm and strain gauge sensors have mounted on same stress force balance to evaluate the response time as well as accuracy of predicted force at the same instant. However, these force balance need to be calibrated for inverse prediction of the force from recorded responses.

Dimensional optimization has always been a time consuming process, especially for aerodynamic bodies, requiring much tuning of dimensions and testing for each sample. Aerodynamic auxiliaries, especially wings, are design dependent on the primary model attached, as they influence the amount of lift or reduction in drag which is beneficial to the model. In this study CFD analysis is performed to obtain pressure counter of wings. For a wing, the angle of attack is essential in creating proper splits to incoming winds, even under high velocities with larger distances from the separation point. In the case of a group of wings, each wing is then mentioned as a wing element, and each wing is strategically positioned behind the previous wing in terms of its vertical height and its self-angle of attack to create maximum lift. At the same time, its drag remains variable to its shape ultimately maximizing the C L /C D ratio.

The study of aerodynamic forces in hypersonic environments is important to ensure the safety and proper functioning of aerospace vehicles. These forces vary with the angle of attack (AOA) and there exists an optimum angle of attack where the ratio of the lift to drag force is maximum. In this paper, computational analysis has been performed on a blunt cone model to study the aerodynamic characteristics when hypersonic flow is allowed to pass through the model. The flow has a Mach number of 8.44 and the angle of attack is varied from 0º to 20º. The commercial CFD solver ANSYS FLUENT is used for the computational analysis and the mesh is generated using the ICEM CFD module of ANSYS. Air is selected as the working fluid. The simulation is carried out for a time duration of 1.2 ms where it reaches a steady state and the lift and drag forces and coefficients are estimated. The pressure, temperature, and velocity contours at different angles of attack are also observed.

Unmanned Aerial Vehicles (UAVs), or drones, are aerial platforms with diverse applications. Their design is shaped by specific constraints, driving a multidisciplinary, iterative process encompassing aerodynamics, structures, flight mechanics and other domains. This paper describes the design of a fixed-wing UAV tailored to competition requirements. The payload comprises golf balls with specific weight and dimensions. The requirements included maintaining a thrust-to-empty weight ratio below 1 and achieving a high payload fraction, calculated as the ratio of payload weight to total UAV weight. An optimization approach was introduced, altering the conventional UAV sizing process to enhance the payload fraction. This was achieved by adjusting the design points within the solution space derived from constraint analysis.