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The identification of the dominant noise sources in diesel engines and the assessment of their contribution to far-field noise is a process that can involve both fired and motored testing. In the present work, the cross-spectral densities of signals from cylinder pressure transducers, accelerometers mounted on the engine surface, and microphones (in the near and far fields), were used to identify dominant noise sources and estimate the transfer paths from the various “inputs” (i.e., the cylinder pressures, the accelerometers and the near field microphones) to the far field microphones. The method is based on singular value decomposition of the input cross-spectral matrix to relate the input measurements to independent virtual sources. The frequencies at which a particular input is strongly affected by an independent source are highlighted, and with knowledge of transducer locations, inferences can be drawn as to possible noise source mechanisms.

The structural excitation by turbulent flow pressure fluctuations continues to be an important part of vehicle NVH analysis and design. Much of the analytical work on turbulent flow has been limited to flow over smooth, flat surfaces. Measurements and CFD analyses show a significantly different pressure spectrum for flows over an obstruction. The coupling of the turbulent pressure excitation to the structural vibration and transmitted sound depends on the spatial matching between the source and response fields. This paper develops an analytical model for the spatial correlation of turbulent flow pressure fluctuations downstream of an obstruction. Such a model is useful in the early design stage of a vehicle and is compatible with SEA models of the fluid structure interaction.

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.

This paper is part of a larger body of experimental and computational work devoted to studying the role of close-coupled post injections on soot reduction in a heavy-duty optical engine. It is a continuation of an earlier computational paper. The goals of the current work are to develop new CFD analysis tools and methods and apply them to gain a more in depth understanding of the different in-cylinder environments into which fuel from main- and post-injections are injected and to study how the in-cylinder flow, thermal and chemical fields are transformed between start of injection timings. The engine represented in this computational study is a single-cylinder, direct-injection, heavy-duty, low-swirl engine with optical components. It is based on the Cummins N14, has a cylindrical shaped piston bowl and an eight-hole injector that are both centered on the cylinder axis. The fuel used was n-heptane and the engine operating condition was light load at 1200 RPM.

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.

This paper describes a novel design and verification process for analytical methods used in the development of advanced combustion strategies in internal combustion engines (ICE). The objective was to improve brake thermal efficiency (BTE) as part of the US Department of Energy SuperTruck program. The tools and methods herein discussed consider spray formation and injection schedule along with piston bowl design to optimize combustion efficiency, air utilization, heat transfer, emission, and BTE. The methodology uses a suite of tools to optimize engine performance, including 1D engine simulation, high-fidelity CFD, and lab-scale fluid mechanic experiments. First, a wide range of engine operating conditions are analyzed using 1-D engine simulations in GT Power to thoroughly define a baseline for the chosen advanced engine concept; secondly, an optimization and down-select step is completed where further improvements in engine geometries and spray configurations are considered.

One way to develop an understanding of soot formation and oxidation processes that occur during direct injection and combustion in an internal combustion engine is to image the natural luminosity from soot over time. Imaging is possible when there is optical access to the combustion chamber. After the images are acquired, the next challenge is to properly interpret the luminous distributions that have been captured on the images. A major focus of this paper is to provide guidance on interpretation of experimental images of soot luminosity by explaining how radiation from soot is predicted to change as it is transmitted through the combustion chamber and to the imaging. The interpretations are only limited by the scope of the models that have been developed for this purpose. The end-goal of imaging radiation from soot is to estimate the amount of soot that is present.

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.

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.

A layered approach to the simulation of dynamically interdependent systems is presented. In particular, the approach is applied to the integrated engineering plant of a notional all-electric warship. The models and parameters of the notional ship are presented herein. This approach is used to study disruptions to the integrated engineering plant caused by anti-ship missiles. Example simulation results establish the effectiveness of this approach in examining the propagation of faults and cascading failures throughout a dynamically interdependent system of systems.

The optimal design of hybrid-electric vehicle power systems poses a challenge to the system analyst, who is presented with a host of parameters to fine-tune, along with stringent performance criteria and multiple design objectives to meet. Herein, a methodology is presented to transform such a design task into a constrained multi-objective optimization problem, which is solved using a distributed evolutionary algorithm. A power system model representative of a series hybrid-electric vehicle is considered as a paradigm to support the illustration of the proposed methodology, with particular emphasis on the power system's time-domain performance.

In long-duration, closed human habitats in space that include crop growth, one challenge that is faced while designing a candidate waste processor is the composition of solid-waste loads, which include human waste, packaging and food-processing materials, crop spoilage, and plant residues. In this work, a new modeling tool is developed to characterize crop residues and food wastes based on diet in order to support the design of solid-waste technologies for closed systems. The model predicts amounts of crop residues and food wastes due to food processing, crop harvests, and edible spoilage. To support the design of solid-waste technologies, the generation of crop residues and food wastes was characterized for a 600-day mission to Mars using integrated menu, crop, and waste models. The three sources of plant residues and food waste are identified to be food processors, crop harvests, and edible spoilage.

Dynamics of machine tool components play a critical role in the outcome of machining processes. This paper addresses several important issues on machine tool and machining dynamics. It illustrates the dynamic behavior of structural components under operating conditions and presents an improved technique for modeling structural non-linearity. It also describes spindle modeling capability that has been developed to predict dynamic and thermal characteristics of spindle systems. Finally, the paper discusses the impact of non-linear dynamics on machining stability.

Detailed computer models of system components for More Electric Aircraft have been developed using the Advanced Control System Language (ACSL) and its graphical front-end, Graphic Modeller. Among the devices modeled are a wound-rotor synchronous generator with parallel bridge-rectifier outputs, a switched-reluctance generator, and various loads including a DC-DC converter, an inverter-driven induction motor, and an electro-hydrostatic actuator. Results from the simulations are presented together with corroborating experimental test results.