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In computational fluid dynamic (CFD) and computational aeroacoustics (CAA) simulations, the wall surface is normally treated as a purely reflective wall. However, some surface treatments are usually applied in experiments. Thus, the acoustic simulations cannot be validated by experimental results. One of the major challenges is how to define acoustically boundary conditions in a well-posed way. In aeroacoustics analysis, impedance is a quantity to characterize reflectivity and absorption of an acoustically treated surface, which may be introduced into the numerical models as a frequency-domain boundary condition. However, CFD and CAA simulations are time-domain computations, meaning the frequency-domain impedance boundary condition cannot be adopted directly. Several methods, including the three-parameter model, the z-transform method and the reflection coefficient model, were developed.

Experimental measurements of tire tread band vibration have provided direct evidence that higher order structural-acoustic modes exist in tires, not just the well-known fundamental acoustical mode. These modes display both circumferential and radial pressure variations within the tire's air cavity. The theory governing these modes has thus been investigated. A brief recapitulation of the previously-presented coupled structural-acoustical model based on a tensioned string approach will be given, and then an improved tire-acoustical model with a ring-like shape will be introduced. In the latter model, the effects of flexural and circumferential stiffness are considered. This improved model accounts for propagating in-plane vibration in addition to the essentially structure-borne flexural wave and the essentially airborne longitudinal wave accounted for in the previous model. The longitudinal structure-borne wave “cuts on” at the tire's circumferential ring frequency.

Over the last decade, a number of hybrid architectures have been proposed with the main goal of minimizing energy consumption of off-highway vehicles. One of the architecture subsets which has progressively gained attention is hydraulic hybrids for earth-moving equipment. Among these architectures, hydraulic hybrids with secondary-controlled drives have proven to be a reliable, implementable, and highly efficient alternative with the potential for up to 50% engine downsizing when applied to excavator truck-loading cycles. Multi-input multi-output (MIMO) robust linear control strategies have been developed by the authors' group with notable improvements on the control of the state of charge of the high pressure accumulator. Nonetheless, the challenge remains to improve the actuator position and velocity tracking.

The most common and lethal weapons against military vehicles are the improvised explosive devices (IEDs). In an explosion, critical cabin’s penetrations and high accelerations can cause serious injuries and death of military personnel. This investigation uses single and multi-fidelity Bayesian optimization (BO) to design sandwich composite armors for blast mitigation. BO is an efficient methodology to solve optimization problems that involve black-box functions. The black-box function of this work is the finite element (FE) simulation of the armor subjected to blast. The main two components of BO are the surrogate model of the black-box function and the acquisition function that guides the optimization. In this investigation, the surrogate models are Gaussian Process (GP) regression models and the acquisition function is the multi-objective expected improvement (MEI) function. Information from low and high fidelity FE models is used to train the GP surrogates.

The transportation sector is facing three revolutions: shared mobility, electrification, and autonomous driving. To inform decision making and guide smart transportation system development at the city-level, it is critical to model and evaluate how travelers will behave in these systems. Two key components in such models are (1) individual travel demands with high spatial and temporal resolutions, and (2) travelers’ sociodemographic information and trip purposes. These components impact one’s acceptance of autonomous vehicles, adoption of electric vehicles, and participation in shared mobility. Existing methods of travel demand generation either lack travelers’ demographics and trip purposes, or only generate trips at a zonal level. Higher resolution demand and sociodemographic data can enable analysis of trips’ shareability for car sharing and ride pooling and evaluation of electric vehicles’ charging needs.

Considerable improvements can be obtained in battery performance for hybrid electric vehicles (HEVs) by employing an electrochemistry-transport model based on a multi-physics modeling framework and ultrafast numerical algorithms. One important advantage of this approach over the lumped equivalent circuit (or look-up table) approach is the ability of the former to adapt to changes in design and control. In this work, we present mathematical and numerical details of our approach, and demonstrate the robustness of this battery model in simulation of short-pulse charge/discharge characteristic of HEV driving cycles under room and low temperatures.

A simulation tool has been developed for predicting steering effort of a vehicle during steering power-assist system failure. The vehicle system is modeled with the inclusion of a system-level vehicle model and a steering system model that are linked together through the steering moment at the kingpin and front road wheel angle. A driver model has also been designed to provide closed-loop steering angular input to make the car follow a certain target path. The simulation model is correlated well with actual vehicle tests under various steering input and lateral acceleration conditions. Also illustrated are some examples of comparison between measured and simulated sensitivity study for selected factors.

The following computational study examines the structure of sonic hydrogen jets using inlet conditions similar to those encountered in direct-injection hydrogen engines. Cases utilizing the same mass and momentum flux while varying exit-to-chamber pressure ratios have been investigated in a constant-volume computational domain. Furthermore, subsonic versus sonic structures have been compared using both hydrogen and ethylene fuel jets. Finally, the accuracy of scaling arguments to characterize an underexpanded jet by a subsonic “equivalent jet” has been assessed. It is shown that far downstream of the expansion region, the overall jet structure conforms to expectations for self-similarity in the far-field of subsonic jets. In the near-field, variations in fuel inlet-to-chamber pressure ratios are shown to influence the mixing properties of sonic hydrogen jets. In general, higher pressure ratios result in longer shock barrel length, though numerical resolution requirements increase.

Three-dimensional conjugate heat transfer models are built to predict the steady-state performance of microscale pin-fin and cross-flow heat exchangers with hydraulic diameters on the order of 100 μm. Modeling, meshing, and segmentation techniques are presented to allow for macroscale simulation of the microstructured devices. The effect of variation in geometric and flow parameters is investigated. Hydraulic and thermal predictions are compared to published experimental and extended beyond the limited range of test data to provide performance within a wide parametric range. A discussion of the dominating and relevant thermal transport mechanisms in both fluids and solid clarifies the routes to optimizing heat transfer in these small scale heat exchangers.

Driveline torque distribution has long been a research topic, and in the last several decades research has been directed towards enhancing on-road vehicle stability and agility through application of controllable driveline systems. This paper discusses the impact of Direct Yaw Control AWD systems (DYC AWD Systems) on the combined acceleration and turning performance as it pertains to maneuverability and stability on all road surfaces. To achieve higher levels of both safety and performance, the application of a controllable DYC AWD system capable of applying direct yaw moment to the vehicle chassis serves as a key goal to achieve the optimal result. A classification of existing driveline systems is discussed and compared to these optimal requirements. Representative on-vehicle scenarios are discussed to illustrate the impact of AWD control on the vehicle stability and maneuverability and to highlight the effects to the vehicle operator.

Vehicle-to-Vehicle (V2V) safety application research based on short range real-time communication has been researched for over a decade. Examples of V2V applications include Electronic Emergency Brake Light, Do Not Pass Warning, Lane Departure Warning, and Intersection Movement Assist. It is hoped that these applications, whether present as warning or intervention, will help reduce the incidence of traffic collisions, fatalities, injuries, and property damage. The safety benefits of these applications will likely depend on many factors, such as usability, market penetration, driver acceptance, and reliability. Some applications, such as DNPW and IMA, require a longer communication range to be effective. In addition, Dedicated Short Range Communications (DSRC) may be required to communicate without direct line of sight. The signal needs to overcome shadowing effects of other vehicles and buildings that are in the way.

Conventional hydraulic steering systems keep improving performance and driving comfort by introducing advanced features via mechanical design. The ever increasing mechanical complexity requires the advanced modeling and simulation technology to mitigate the risks in the early stage of the development process. In this paper, we focus on advanced modeling tools environment with an example of a load sensing hydraulic steering system. The complete system architecture is presented. Analytical equations are developed for a priority valve and a steering control unit as the foundation of modeling. The full version of hydraulic steering system model is developed in Dymola platform. In order to capture interaction between steering and vehicle, the co-simulation platform between the hydraulic steering system and vehicle dynamics is established by integrating Dymola, Carsim and Simulink.

This paper presents a simulation model for the analysis of internal gear ring pumps. The model follows a multi domain simulation approach comprising sub-models for parametric geometry generation, fluid dynamic simulation, numerical calculation of characteristic geometry data and CAD/FEM integration. The sub-models are interacting in different domains and relevant design and simulation parameters are accessible in a central, easy to handle graphical user interface. The potentials of the described tool are represented by simulation results for both steady state and transient pump operating conditions and by their correlation with measured data. Although the presented approach is suitable to all applications of gear ring pumps, a particular focus is given to hydraulic actuation systems used in automotive drivetrain applications.

Excessive vibration and poor controllability occur in many mobile fluid power applications, with negative consequences as concerns operators' health and comfort as well as machine safety and productivity. This paper addresses the problem of reducing oscillations in fluid power machines presenting a novel control technique of general applicability. Strong nonlinearities of hydraulic systems and the unpredictable operating conditions of the specific application (e.g. uneven ground, varying loads, etc.) are the main challenges to the development of satisfactory general vibration damping methods. The state of the art methods are typically designed as a function of the specific application, and in many cases they introduce energy dissipation and/or system slowdown. This paper contributes to this research by introducing an energy efficient active damping method based on feedback signals from pressure sensors mounted on the flow control valve block.

Notched spoilers may be used to suppress flow-induced cavity resonance in vehicles with open sunroofs or side windows. The notches are believed to generate streamwise vortices that break down the structure of the leading edge cross-stream vortices predominantly responsible for the cavity excitation. The objectives of the present study were to gain a better understanding of the buffeting suppression mechanisms associated with notched spoilers, and to gather data for computational model verification. To this end, experiments were performed to characterize the surface pressure field downstream of straight and notched spoilers mounted on a rigid wall to observe the effects of the notches on the static and dynamic wall pressure. Detailed flow velocity measurements were made using hot-wire anemometry. The results indicated that the presence of notches on the spoiler reduces drag, and thus tends to move the flow reattachment location closer to the spoiler.

This paper presents a method for indirect measurement of tire slip angles from chassis acceleration, yaw rate, and steer angle measurements. The chassis is assumed to be rigid so that acceleration data can be integrated to estimate velocities of the front and rear of the vehicle, from which slip angles can be predicted. The difference in front and rear slip angles is indicative of vehicle oversteer/understeer. Understeer data can then be correlated with position on the track to better understand vehicle handling behavior, aiding the tuning process. The technique is presented, and shown to work well with simulated data, even when the data is corrupted with up to 20% noise. Therefore, the inversion process presented here is theoretically sound. However, when the technique is applied to measured data from race cars, it is shown to be inaccurate. One suspected problem is the difficulty of getting accurate yaw rate data.

A temperature estimation algorithm (thermal observer) that provides accurate estimates of the thermal states of an electric machine in real time is presented. The thermal observer is designed to be a Kalman filter that combines thermal state predictions from a lumped-parameter thermal model of the electric machine with temperature measurements from a single external temperature sensor. An analysis based on the error covariance matrix of the Kalman filter is presented to guide the selection of the best sensor location. The thermal observer performance is demonstrated using a 3.8 kW permanent-magnet machine. Comparison of the thermal observer estimates and the actual temperatures demonstrate that this approach can provide accurate knowledge of the machine's thermal states despite modeling uncertainty and unknown initial machine thermal states.

To support research and analysis requirements in the development of future hybrid-electric drive systems, a flexible and efficient means of predicting the dynamic performance of large-scale multi-disciplinary systems prior to hardware trials is crucial. With the development of Distributed Heterogeneous Simulation (DHS), the technology now exists to enable this type of investigation. Previously, DHS was shown to allow the interconnection of component simulations running on a single computer or networked computers and developed using any combination of a variety of commercial-off-the-shelf software packages. The US Army is interested in using the Simplorer software product from Ansoft Corporation to model various subsystems that are incorporated with such vehicle system simulations. In this paper, the DHS technique is expanded to support the Simplorer software package; thus, allowing subsystem models developed using this tool to be interconnected to form a dynamic system simulation.

The interdependency between propulsion, power, and thermal subsystems on military aircraft such as the F-35 Joint Strike Fighter (JSF) and F-22 Raptor continues to increase as advanced war-fighting capabilities including solid-state radars, electronic attack, electric actuation, and Directed Energy Weaponry (DEW) expand to meet Air Force needs. Novel analysis and testing methodologies are required to predict these interdependencies and address adverse interactions prior to costly hardware prototyping. As a result, the Air Force Research Laboratory (AFRL) has established a dynamic hardware-in-the-loop (HIL) test-bed wherein transient simulations can be integrated through advanced real-time simulation with prototype hardware for integrated system studies and analysis. This paper details a test-bed configuration where a dynamic simulation of an aircraft turbine engine is utilized to control a dual-head electric drive stand.

This paper describes a coupled-circuit physical-variable modeling of multiphase induction motors. The presented modeling interface makes it straightforward to implement an induction machine with arbitrary number of phases and/or phase groups on the stator and the rotor. The 3-, 6-, and 9-phase motors are simulated and compared. It is shown that machines with higher number of phases have less severe torque pulsation and the stator current increase following a loss of one phase. For the 9-phase machine, several studies involving loss of multiple phases are also presented, wherein the relative location of the faulted phases is shown to have a significant impact on redistribution of currents and resulting electromagnetic torque. The proposed models can be used to represent induction motors and generators for transient studies involving multiple faults, system-level reconfiguration, and survivability.