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This research focused on developing a methodology for a vehicle dynamics model of a passenger vehicle outfitted with an aftermarket Automated Driving System software package using only literature and track based results. This package consisted of Autoware.AI (Autoware ®) operating on Robot Operating System 1 (ROS™) with C++ and Python ®. Initial focus was understanding the basics of ROS and how to implement test scenarios in Python to characterize the control systems and dynamics of the vehicle. As understanding of the system continued to develop, test scenarios were adapted to better fit system characterization goals with identification of system configuration limits. Trends from on-track testing were identified and paired with first-order linear systems to simulate physical vehicle responses to given command inputs. Sub-models were developed and simulated in MATLAB ® with command inputs from on-track testing.

Deployment of autonomous vehicles requires an extensive evaluation of developed control, perception, and localization algorithms. Therefore, increasing the implemented SAE level of autonomy in road vehicles requires extensive simulations and verifications in a realistic simulation environment before proving ground and public road testing. The level of detail in the simulation environment helps ensure the safety of a real-world implementation and reduces algorithm development cost by allowing developers to complete most of the validation in the simulation environment. Considering sensors like camera, LiDAR, radar, and V2X used in autonomous vehicles, it is essential to create a simulation environment that can provide these sensor simulations as realistically as possible.

Having connectivity among ground vehicles brings about benefits in fuel economy improvement, traffic mobility enhancement and undesired emission reductions. On the other hand, Unmanned Aerial Vehicles (UAV) have proven to help in getting aerial data to end users in an affordable manner. When UAVs are equipped with cameras, they can get information about the terrain they are flying over. Moreover, using Vehicle-to-Everything (V2X) communication technologies, it is possible to form a communication link between UAVs and the connected ground vehicle networks comprising of Connected and Autonomous vehicles (CAVs). To investigate and exploit the potential benefits and use cases of a broad vehicle network, a microscopic traffic simulator modified previously by our group with the addition of nearby UAVs is used to integrate simulated Connected UAVs flying above a realistic simulation of heterogeneous traffic flow containing both CAVs and non-CAVs.

This paper describes a joint SAE automotive and aerospace Recommended Practice SAE J3168 now in development to standardize a process for Reliability Physics Analysis. This is a science-based approach to implement Physics-of-Failure research in conducting durability simulations in a Computer Aided Engineering Environment. It is used to calculate failure mechanism susceptibilities and estimate the likelihood of failure and the expected durability life of Electrical, Electronic and Electromechanical components and equipment, due to stresses such as mechanical shock, vibration, temperature cycling, etc. Reliability Physics Analysis is based on the material science principle of stress driven damage accumulation in materials. The process enables the identification of potential failure risks early in the design phase so that such risks can be designed out in order to efficiently design high reliable and robustness into electronic products.

The advent of turbochargers and the Eco-Boost technology at Ford in gasoline engines creates new challenges that need to be addressed with innovative designs. One of them is flow induced noise caused by airflow entering the turbocharger during off design operation. At certain vehicle operation conditions, the mass flow rate and pressure ratio are such that compressor wheel can generate a wide range of acoustic frequencies. Characterization of ‘whistles’ or pure tonal noises, ‘whoosh’ or broad band frequency noise caused by flow separation from the blade surfaces, and chirps, where the frequency increases or decreases with time are a few of the common error states. Understanding the fundamental mechanisms of such noise generation is necessary for developing effective countermeasures for the noise source generation. Computational Aero-Acoustic (CAA) analyses are performed to study the effects of inlet and outlet conditions to find the source of the noise.

Cooling drag is a metric that measures the influence of air flow travelling through the open grille of a ground vehicle on overall vehicle drag, both internally (engine air flow) and externally (interference air flow). With the interference effects considered, a vehicles cooling drag can be influenced by various air flow fields around the vehicle, not just the air flow directly entering or leaving the engine bay. For this reason, computational fluid dynamics (CFD) simulations are particularly difficult. With insights gained from a previously conducted set of experimental studies, a CFD validation effort was undergone to understand which air flow field characteristics contribute to CFD/test discrepancies. A Lattice-Boltzmann Large Eddy Simulation (LES) method was used to validate several test points. Comparison using integral force values, surface pressures, and cooling pack air mass flows was presented.

Air rush noise is exhaust gas driven flow-induced noise in the frequency range of 500-6500 Hz. It is essential to understand the flow physics of exhaust gases within the mufflers in order to identify any counter measures that can attenuate this error state. This study is aimed at predicting the flow physics and air rush noise of exhaust mufflers in the aforementioned frequency range at a typical exhaust flow rate and temperature. The study is performed on two different muffler designs which show a significant air rush noise level difference when tested on the vehicle. The transient computational study was performed using DES with 2nd order spatial discretization and 2nd order implicit scheme for temporal discretization in StarCCM+. To compare with test data, a special flow test stand is designed so that all high and low frequency contents emanating from the engine are attenuated before the flow enters the test part.

For many years, the use of in-mold fasteners has been avoided for various reasons including: not fully understanding the load cases in the part, the fear of quality issues occurring, the need for servicing, or the lack of understanding the complexity of all failure modes. The most common solution has been the use of secondary operations to provide attachments, such as, screws, metal clips, heat staking, sonic welding or other methods which are ultimately a waste in the process and an increase in manufacturing costs. The purpose of this paper is to take the reader through the design process followed to design an in-molded attachment clip on plastic parts. The paper explores the design process for in-molded attachment clips beginning with a design concept idea, followed by basic concept testing using a desktop 3D printer, optimizing the design with physical tests and CAE analysis, and finally producing high resolution 3D prototypes for validation and tuning.

Computer Aided Engineering (CAE) has become a vital tool for product development in automotive industry. Increasing computer models are developed to simulate vehicle crashworthiness, dynamic, and fuel efficiency. Before applying these models for product development, model validation needs to be conducted to assess the validity of the models. However, one of the key difficulties for model validation of dynamic systems is that most of the responses are functional responses, such as time history curves. This calls for the development of an objective metric which can evaluate the differences of both the time history and the key features, such as phase shift, magnitude, and slope between test and CAE curves. One of the promising metrics is Error Assessment of Response Time Histories (EARTH), which was recently developed. Three independent error measures that associated with physically meaningful characteristics (phase, magnitude, and slope) were proposed.

High concentrations of diesel fuel can accumulate in the engine oil, especially in vehicles equipped with diesel particle filters. Fuel dilution can decrease the viscosity of engine oil, reducing its film thickness. Higher concentrations of fuel are believed to accumulate in oil with biodiesel than with diesel fuel because biodiesel has a higher boiling temperature range, allowing it to persist in the sump. Numerous countries are taking actions to promote the use of biodiesel. The growing interest for biodiesel has been driven by a desire for energy independence (domestically produced), the increasing cost of petroleum-derived fuels, and an interest in reducing greenhouse gas emissions. Biodiesel can affect engine lubrication (through fuel dilution), as its physical and chemical properties are significantly different from those of petrodiesel. Many risks associated with excessive biodiesel dilution have been identified, yet its actual impact has not been well quantified.

Statistical Energy Analysis (SEA) is an established high-frequency analysis technique for generating acoustic and vibration response predictions in the automotive, aerospace, machinery, and ship industries. SEA offers unique NVH prediction and target-setting capabilities as a design tool at early stages of vehicle design where geometry is still undefined and evolving and no prototype hardware is available yet for testing. The exact frequencies at which SEA can be used effectively vary according to the size and the amount of damping in the vehicle subsystems; however, for automotive design the ability to predict acoustic and vibration responses due to both airborne and structure-borne sources has been established to frequencies of 500 Hz and above. This paper presents the background, historical use, and current industrial applications of structure-borne SEA. The history and motivation for the development of structure-borne SEA are discussed.

Gliders can climb to substantial altitudes without employing any on-board energy resources but using proper piloting skills to utilize rising air currents called thermals. Recent experiments on small Unmanned Aerial Vehicles (UAVs) indicate a significant potential to increase both the flight velocity and the range of gliders by means of such maneuvers. In these experiments the velocity to approach a thermal has been recognized as a critical performance factor, and is chosen as the controlled variable. Accurate longitudinal controllers are required to track the optimal flight trajectories generated using path planning algorithms. These controllers are challenged by the presence of uncertain and time-varying aircraft dynamics, gust disturbances, and control actuator limitations.

Long-duration space missions require high-quality, nutritious foods, which will need reheating to serving temperature, or sterilization on an evolved planetary base. The package is generally considered to pose a disposal problem after use. We are in the process of development of a dual-use package wherein the food may be rapidly reheated in situ using the technology of ohmic heating. We plan to make the container reusable, so that after food consumption, the package is reused to contain and sterilize waste. This approach will reduce Equivalent System Mass (ESM) by using a compact heating technology, and reducing mass requirements for waste storage. Preliminary tests of the package within a specially-designed ohmic heating enclosure show that ISS menu item could easily be heated using ohmic heating technology. Mathematical models for heat transfer were used to optimize the layout of electrodes to ensure uniform heating of the material within the package.

The current Si/polymeric medical diagnostic sensors that are on the market only feature a one-point calibration system [1]. Such a measurement results in less accurate sensing and more in-factory sensor rejection. The two-point calibration fluidic method introduced here will alleviate some of the shortcomings of such current miniature analytical systems. Our fluidic platform is a disposable, multi-purpose micro analytical laboratory on a compact disc (CD) [2, 3]. This system is based on the centrifugal force, in which fluidic flow can be controlled by the spinning rate of the CD and thus a whole range of fluidic functions including valving, mixing, metering, splitting, and separation can be implemented. Furthermore, optical detection such as absorption and fluorescence can be incorporated into the CD control unit to obtain signals from pre-specified positions on the disc.