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In the dense fabric of urban areas, electric scooters have rapidly become a preferred mode of transportation. As they cater to modern mobility demands, they present significant safety challenges, especially when interacting with pedestrians. In general, e-scooters are suggested to be ridden in bike lanes/sidewalks or share the road with cars at the maximum speed of about 15-20 mph, which is more flexible and much faster than pedestrians and bicyclists. Accurate prediction of pedestrian movement, coupled with assistant motion control of scooters, is essential in minimizing collision risks and seamlessly integrating scooters in areas dense with pedestrians. Addressing these safety concerns, our research introduces a novel e-Scooter collision avoidance system (eCAS) with a method for predicting pedestrian trajectories, employing an advanced Long short-term memory (LSTM) network integrated with a state refinement module.

In the past decades, automotive structure design has sought to minimize its mass while maintaining or improving structural performance. As such, topology optimization (TO) has become an increasingly popular tool during the conceptual design stage. While the designs produced by TO methods provide significant performance-to-mass ratio improvements, they require considerable computational resources when solving large-scale problems. An alternative for large-scale problems is to decompose the design domain into multiple scales that are coupled with homogenization. The problem can then be solved with hierarchical multiscale topology optimization (MSTO). The resulting optimal, homogenized macroscales are de-homogenized to obtain a high-fidelity, physically-realizable design. Even so MSTO methods are still computationally expensive due to the combined costs of solving nested optimization problems and performing de-homogenization.

A common scenario in engineering design is the evaluation of expensive black-box functions: simulation codes or physical experiments that require long evaluation times and/or significant resources, which results in lengthy and costly design cycles. In the last years, Bayesian optimization has emerged as an efficient alternative to solve expensive black-box function design problems. Bayesian optimization has two main components: a probabilistic surrogate model of the black-box function and an acquisition functions that drives the design process. Successful Bayesian optimization strategies are characterized by accurate surrogate models and well-balanced acquisition functions. The Gaussian process (GP) regression model is arguably the most popular surrogate model in Bayesian optimization due to its flexibility and mathematical tractability. GP regression models are defined by two elements: the mean and covariance functions.

Nested planetary gear trains, which consist of two integrated co-axial single-stage planetary gearsets, have recently been widely implemented in automobile transmissions and various other applications. In the current study, a non-destructive vibrational and acoustical monitoring technique is developed to detect a common type of gear grinding defect for a complex nested gear train structure. A nested gear train which has an unground pinion with unpolished teeth profile is used to exemplify the developed methodology. An experimental test stand with an open and vertical mounting configuration has been designed to acquire both vibrational and acoustical data. The measured data are investigated using several signal processing techniques to identify unground pinions in the gear system. A general frequency spectrum analysis is performed initially, which is then followed by a peak finding algorithm to identify the peaks in the spectrum.

Tire/road noise has become a significant issue in the automotive industry, especially for electric vehicles. Among the various tire/road noise sources, the air-cavity mode can amplify the forces transmitted from the tire to the suspension system causing noticeable cabin noise near 200 Hz. Furthermore, when the tire is deformed by loading, the fundamental air-cavity mode separates into two acoustic modes, a fore-aft mode and vertical mode due to the break in geometrical symmetry. This is important because the two components of the split mode can increase force levels at the hub by interacting with neighboring structural modes, thus resulting in increased interior noise levels. In this research, finite element simulations of five commercial tires at rated load were performed with a view to identifying the frequency split and its interaction with structural resonances. These results have been compared with previously obtained empirical results.

This paper explains the basic principles behind two platform technologies that my research team has developed in the field of optical metrology and optical information processing: 1) high-speed 3D optical sensing; and 2) real-time 3D video compression and streaming. This paper will discuss how such platform technologies could benefit the automotive industry including in-situ quality control for additive manufacturing and autonomous vehicle systems. We will also discuss some of other applications that we have been working on such as crime scene capture in forensics.

The formation of ice on aircraft is a highly dynamic process during which ice will expand and contract upon freezing and undergoing changes in temperature. Finite element analysis (FEA) simulations were performed investigating the stress/strain response of an idealized ice sample bonded to an acrylic substrate subjected to a uniform temperature change. The FEA predictions were used to guide the placement of strain gages on custom-built acrylic and aluminum specimens. Tee rosettes were placed in two configurations adjacent to thermocouple sensors. The specimens were then placed in icing conditions such that ice was grown on top of the specimen. It was hypothesized that the ice would expand on freezing and contract as the temperature of the interface returned to the equilibrium conditions.

Near-Field Acoustical Holography (NAH) is an inverse process in which sound pressure measurements made in the near-field of an unknown sound source are used to reconstruct the sound field so that source distributions can be clearly identified. NAH was originally based on performing spatial transforms of arrays of measured pressures and then processing the data in the wavenumber domain, a procedure that entailed the use of very large microphone arrays to avoid spatial truncation effects. Over the last twenty years, a number of different NAH methods have been proposed that can reduce or avoid spatial truncation issues: for example, Statistically Optimized Near-Field Acoustical Holography (SONAH), various Equivalent Source Methods (ESM), etc.

The design optimization of thin-walled tubular structures is of relevance in the automotive industry due to their low cost, ease of manufacturing and installation, and high-energy absorption efficiency. This study presents a methodology to design thin-walled tubular structures for crashworthiness applications. During an impact, thin-walled tubular structures may exhibit progressive collapse/buckling, global collapse/buckling, or mixed collapse/buckling. From a crashworthiness standpoint, the most desirable collapse mode is progressive collapse due to its high-energy absorption efficiency, stable deformation, and low peak crush force (PCF). In the automotive industry, thin-walled components have complex structural geometries. These complexities and the several loading conditions present in a crash reduce the possibility of progressive collapse. The Hybrid Cellular Automata (HCA) method has shown to be an efficient continuum-based approach in crashworthiness design.

Structures with multiple materials have now become one of the perceived necessities for automotive industry to address vehicle design requirements such as light-weight, safety, and cost. The objective of this study is to develop a design methodology for multi-material structures accountable for vehicle crash durability. The heuristic topology synthesis approach of Hybrid Cellular Automaton (HCA) framework is implemented to generate multi-material structures with the constraint on the volume fraction of the final design. The HCA framework is integrated with ordered-SIMP (solid isotropic material with penalization) interpolation, artificial material library, as well as statistical analysis of material distribution data to ensure a smooth transition between multiple practical materials during the topology synthesis.

This paper introduces a design methodology to tailor the acceleration and displacement responses of a vehicle structure subjected to a dynamic crushing load. The proposed approach is an extension of the hybrid cellular automaton (HCA) method, through which the internal energy density is uniformly distributed within the structure. The proposed approach, referred here to as an extended HCA (xHCA) method, receives the suitable combinations of volume fraction and a finite element meta-parameter for which the algorithm synthesizes the load paths that allow the desired crash response. Lower meta-parameter values lead designs obtained by traditional optimizers, while larger values lead to designs obtained by the HCA method. Simultaneous implementation of multiple values of meta-parameters is presented here as a further development of xHCA method.

This paper describes a simulation approach for the modeling of tandem external gear pumps. A tandem gear pump is the combination of two pumps with a common drive shaft. Such design architecture finds application in certain automotive transmission systems. The model presented in this work is applicable for pumps with both helical and spur gears. The simulation model is built on the HYGESim (HYdraulic GEars machines Simulator) previously developed by the authors for external spur gear units. In this work, the model formulation is properly extended to the capabilities of simulating helical gears. Starting directly from the CAD drawings of the unit, the fluid-dynamic model solves the internal instantaneous tooth space volume pressures and the internal flows following a lumped parameter approach. The simulation tool considers also the radial micro-motion of the gears, which influences the internal leakages and the features of the meshing process.

An increase in the number of vehicles per capita coupled with stricter emission regulations have made the development of newer and better hybrid vehicle architectures indispensable. Although electric hybrids have more visibility and are now commercially available, hydraulic hybrids, with their higher power densities and cheaper components, have been rigorously explored as the alternative. Several architectures have been proposed and implemented for both on and off highway applications. The most commonly used architecture is the series hybrid, which requires an energy conversion from the primary source (engine) to the secondary domain. From he re, the power flows either into the secondary source (high-pressure accumulator) or to the wheels depending upon the state of charge of the accumulator. A mode-switching hydraulic hybrid, which is a combination of a hydrostatic transmission and a series hybrid, was recently developed in the author’s research group.

The basic idea behind large-eddy simulation (LES) is to accurately resolve the large energy-containing scales and to use subgrid-scale (SGS) models for the smaller scales. The accuracy of LES can be significantly impacted by the numerical discretization schemes and the choice of the SGS model. This work investigates the accuracy of low-order LES codes in the simulation of a turbulent round jet which is representative of fuel jets in engines. The turbulent jet studied is isothermal with a Reynolds number of 6800. It is simulated using Converge, which is second-order accurate in space and first-order in time, and FLEDS, developed at Purdue University, which is sixth-order accurate in space and fourth-order in time. The high-order code requires the resolution of acoustic time-scales and hence is approximately 10 times more expensive than the low-order code.

Mobile Earth Moving Machinery like Skid-steer loaders have tight turning radius in limited spaces due to a short wheelbase which prevents the use of suspensions in these vehicles. The absence of a suspension system exposes the vehicle to ground vibrations of high magnitude and low frequency. Vibrations reduce operator comfort, productivity and life of components. Along with vibrations, the machine productivity is also hampered by material spillage which is caused by the tilting of the bucket due to the extension of the boom. The first part of the paper focuses on vibration damping. The chassis’ vibrations are reduced by the use of an active suspension element which is the hydraulic boom cylinder which is equivalent to a spring-damper. With this objective, a linear model for the skid steer loader is developed and a state feedback control law is implemented.

Typically, earthmoving machines do not have wheel suspensions. This lack of components often causes uncomfortable driving, and in some cases reduces machine productivity and safety. Several solutions to this problem have been proposed in the last decades, and particularly successful is the passive solution based on the introduction of accumulators in the hydraulic circuit connecting the machine boom. The extra capacitance effect created by the accumulator causes a magnification of the boom oscillations, in such a way that these oscillations counter-react the machine oscillation caused by the driving on uneven ground. This principle of counter-reacting machine oscillations through the boom motion can be achieved also with electro-hydraulic solutions, properly actuating the flow supply to the boom actuators on the basis of a feedback sensors and a proper control strategy.

This work proposes a new method to design crashworthiness structures that made of functionally graded cellular (porous) material. The proposed method consists of three stages: The first stage is to generate a conceptual design using a topology optimization algorithm so that a variable density is distributed within the structure minimizing its compliance. The second stage is to cluster the variable density using a machine-learning algorithm to reduce the dimension of the design space. The third stage is to maximize structural crashworthiness indicators (e.g., internal energy absorption) and minimize mass using a metamodel-based multi-objective genetic algorithm. The final structure is synthesized by optimally selecting cellular material phases from a predefined material library. In this work, the Hashin-Shtrikman bounds are derived for the two-phase cellular material, and the structure performances are compared to the optimized structures derived by our proposed framework.

The vertical force generated from terrain-tire interaction has long been of interest for vehicle dynamic simulations and chassis development. To improve simulation efficiency while still providing reliable load prediction, a terrain pre-filtering technique using a constraint mode tire model is developed. The wheel is assumed to convey one quarter of the vehicle load constantly. At each location along the tire's path, the wheel center height is adjusted until the spindle load reaches the pre-designated load. The resultant vertical trajectory of the wheel center can be used as an equivalent terrain profile input to a simplified tire model. During iterative simulations, the filtered terrain profile, coupled with a simple point follower tire model is used to predict the spindle force. The same vehicle dynamic simulation system coupled with constraint mode tire model is built to generate reference forces.

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.

A novel Blended Hydraulic Hybrid transmission architecture is presented in this paper with benefits over conventional designs. This novel configuration combines elements of a hydrostatic transmission, a parallel hybrid, and a selectively connectable high pressure accumulator using passive and actively controlled logic elements. Losses are reduced compared to existing series hybrid transmissions by enabling the units to operate efficiently at pressures below the current high pressure accumulator's pressure. A selective connection to the high pressure accumulator also allows for higher system precharge which increases regenerative braking torque and energy capture with little determent to system efficiency. Finally operating as a hydrostatic transmission increases transmission stiffness (i.e. driver response) and may improve driver feel in certain situations when compared to a conventional series hybrid transmission.