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This article begins by describing the need for a new method and tool for performing a sustainability assessment for manufacturing processes and systems. A brief literature survey is done to highlight the major existing methods and tools, their function, and their shortcomings. The article goes on to describe the general approach of the method before describing a computer aided tool that has been developed to implement the method. The article concludes with a walk through of a generic use case that describes where such a method would be useful and how such a tool would be implemented.

Recently Michelin has been developing a new airless, integrated tire and wheel combination called the Tweel® tire. The Tweel tire aims at performance levels beyond those possible with conventional pneumatic technology because of its shear band design, added suspension, and potentially decreased rolling resistance. In this paper, we will focus on the environmental impact of the Tweel tire during its life-cycle from manufacturing, through use and disposal. Since the Tweel tire is currently still in the research phase and is not manufactured and used on a large scale, there are uncertainties with respect to end-of-life scenarios and rolling resistance estimates that will affect the LCA. Nevertheless, some preliminary conclusions of the Tweel tire's environmental performance in comparison to a conventional radial tire can be drawn.

Although the design phase can account for a sizable amount of the resources consumed during the product realization process, the time and costs associated with the design process are often neglected when making design decisions. To investigate this issue, we define a process-centric decision model in which the design-phase consumption of resources, such as time and money, is explicitly modeled. While it is clear that the utility of a design is almost always directly impacted by the monetary costs of the design process, our decision model also accounts for the fact that the profit earned by a product depends strongly on its launch date. The decision model allows us thus to consider the trade-off between the time necessary for analysis and the improvement in product quality that results from the analysis. The decision model is sufficiently generic that almost any set of beliefs about the alternatives or analyses, as well as any utility-based preference structure can be modeled.

This paper employs the motion-mode energy method (MEM) to investigate the effects of a roll-plane hydraulically interconnected suspension (HIS) system on vehicle body-wheel motion-mode energy distribution. A roll-plane HIS system can directly provide stiffness and damping to vehicle roll motion-mode, in addition to spring and shock absorbers in each wheel station. A four degree-of-freedom (DOF) roll-plane half-car model is employed for this study, which contains four body-wheel motion-modes, including body bounce mode, body roll mode, wheel bounce mode and wheel roll mode. For a half-car model, its dynamic energy contained in the relative motions between its body and wheels is a sum of the energy of these four motion-modes. Numerical examples and full-car experiments are used to illustrate the concept of the effects of HIS on motion-mode energy distribution.

The public Hybrid III family finite element models have been used in simulation of automotive safety research widely. The validity of an ATD finite element model is largely dependent on the accuracy of model structure and accurate material property parameters especially for the soft material. For Hybrid III 50th percentile male dummy model, the femur load is a vital parameter for evaluating the injury risks of lower limbs, so the importance of accuracy of knee subcomponent model is obvious. The objective of this work was to evaluate the accuracy of knee subcomponent model and improve the validity of it. Comparisons between knee physical model and knee finite element model were conducted for both structure and property of material. The inaccuracy of structure and the material model of the published model were observed.

We analyze the frequency response of structural dynamic systems with uncertainties in load and material properties. We introduce uncertainties in the system as interval numbers, and use Interval Finite Element Method (IFEM). Overestimation due to dependency is reduced using a new decomposition for the stiffness and mass matrices, as well as for the nodal equivalent load. In addition, primary and derived quantities are simultaneously obtained by means of Lagrangian multipliers that are introduced in the total energy of the system. The obtained interval equations are solved by means of a new variant of the iterative enclosure method resulting in guaranteed enclosures of relevant quantities. Several numerical examples show the accuracy and efficiency of the new formulation.

We present a new interval-based formulation for the static analysis of plane stress/strain problems with uncertain parameters in load, material and geometry. We exploit the Interval Finite Element Method (IFEM) to model uncertainties in the system. Overestimation due to dependency among interval variables is reduced using a new decomposition strategy for the structural stiffness matrix and the nodal equivalent load vector. Primary and derived quantities follow from minimization of the total energy and they are solved simultaneously and with the same accuracy by means of Lagrangian multipliers. Two different element assembly strategies are introduced in the formulation: one is Element-by-Element, and the other resembles conventional assembly. In addition, we implement a new variant of the interval iterative enclosure method to obtain outer and inner solutions. Numerical examples show that the proposed interval approach guarantees to enclose the exact system response.

Effectively obtaining physical parameters for vehicle dynamic model is the key to successfully performing any computer-based dynamic analysis, control strategy development or optimization. For a spring and lump mass vehicle model, which is a type of vehicle model widely used, its physical parameters include sprung mass, unsprung mass, inertial properties of the sprung mass, stiffness and damping coefficient of suspension and tire, etc. To minimize error, the paper proposes a method to estimate these parameters from vehicle modal parameters which are in turn obtained through full-car dynamic testing. To verify its effectiveness, a visual vehicle with a set of given parameters, build in the Adams(Automatic Dynamic Analysis of Mechanical Systems)/Car environment, is used to perform the dynamic testing and provide the testing data for the parameter estimation.

This work contributes to the understanding of physical mechanisms that control flashback, or more appropriately combustion recession, in diesel sprays. A large dataset, comprising many fuels, injection pressures, ambient temperatures, ambient oxygen concentrations, ambient densities, and nozzle diameters is used to explore experimental trends for the behavior of combustion recession. Then, a reduced-order model, capable of modeling non-reacting and reacting conditions, is used to help interpret the experimental trends. Finally, the reduced-order model is used to predict how a controlled ramp-down rate-of-injection can enhance the likelihood of combustion recession for conditions that would not normally exhibit combustion recession. In general, fuel, ambient conditions, and the end-of-injection transient determine the success or failure of combustion recession.

With the development of advanced ABE fermentation technology, the volumetric percentage of acetone, butanol and ethanol in the bio-solvents can be precisely controlled. To seek for an optimized volumetric ratio for ABE-diesel blends, the previous work in our team has experimentally investigated and analyzed the combustion features of ABE-diesel blends with different volumetric ratio (A: B: E: 6:3:1; 3:6:1; 0:10:0, vol. %) in a constant volume chamber. It was found that an increased amount of acetone would lead to a significant advancement of combustion phasing whereas butanol would compensate the advancing effect. Both spray dynamic and chemistry reaction dynamic are of great importance in explaining the unique combustion characteristic of ABE-diesel blend. In this study, a semi-detailed chemical mechanism is constructed and used to model ABE-diesel spray combustion in a constant volume chamber.

End-of-injection transients have recently been shown to be important for combustion and emissions outcomes in diesel engines. The objective of this work is to develop an understanding of the coupling between end-of-injection transients and the propensity for second-stage ignition in mixtures upstream of the lifted diesel flame, or combustion recession. An injection system capable of varying the end-of-injection transient was developed to study single fuel sprays in a newly commissioned optically-accessible spray chamber under a range of ambient conditions. Simultaneous high-speed optical diagnostics, namely schlieren, OH* chemiluminescence, and broadband luminosity, were used to characterize the spatial and temporal development of combustion recession after the end of injection.

In early phases of conceptual design stages for developing a new car in the modern automobile industry, the lack of systematic methodology to efficiently converge to an agreement between the aesthetics and aerodynamic performance tremendously increases budget and time. During these procedures, one of the most important tasks is to create geometric information which is versatilely morphable upon the demands of both of stylists and engineers. In this perspective, this paper proposes a Spline-based Modeling Algorithm (SMA) to implement into performing aerodynamic design optimization research based on CFD analysis. Once a 3-perspective schematic of a car is given, SMA regresses the backbone boundary lines by using optimum polynomial interpolation methods with the best goodness of fit, eventually reconstructing the 3D shape by linearly interpolating from the extracted boundaries minimizing loss of important geometric features.

Since, ice accretion can significantly degrade the performance and the stability of an airborne vehicle, it is imperative to be able to model it accurately. While ice accretion studies have been performed on airplane wings and helicopter blades in abundance, there are few that attempt to model the process on more complex geometries such as fuselages. This paper proposes a methodology that extends an existing in-house Extended Messinger solver to complex geometries by introducing the capability to work with unstructured grids and carry out spatial surface streamwise marching. For the work presented here commercial solvers such as STAR-CCM+ and ANSYS Fluent are used for the flow field and droplet dispersed phase computations. The ice accretion is carried out using an in-house icing solver called GT-ICE. The predictions by GT-ICE are compared to available experimental data, or to predictions by other solvers such as LEWICE and STAR-CCM+.

The around view monitor (AVM) system for vehicles usually suffers from the distortion of surrounding objects caused by incomplete rectification and stitching, which seriously affects the driver's judgment of the surrounding environment during the reversing process. In response to solve this problem, an augmented around view monitor (AAVM) system fusing image and depth information is proposed, which highlights the point clouds of persons or vehicles at the rear of the vehicle. First, an around view image is generated from four fisheye cameras. Then, the calibration of multi TOF cameras is conducted to improve their accuracy of depth estimation and obtain extrinsic camera positions. Next, the 2D-driven object point cloud detection method is proposed to localize and segment object point clouds like vehicles or persons.

Two-scale command shaping is a recently proposed feedforward control method aimed at mitigating undesirable vibrations in nonlinear systems. The TSCS strategy uses a scale separation to cancel oscillations arising from nonlinear behavior of the system, and command shaping of the remaining linear problem. One promising application of TSCS is in reducing engine restart and shutdown vibrations found in conventional and in hybrid electric vehicle powertrains equipped with start-stop features. The efficacy of the TSCS during internal combustion engine restart has been demonstrated theoretically and experimentally in the authors’ prior works. The present article presents simulation results and describes the verified experimental apparatus used to study TSCS as applied to the ICE shutdown case. The apparatus represents a typical HEV powertrain and consists of a 1.03 L three-cylinder diesel ICE coupled to a permanent magnet alternating current electric machine through a spur gear coupling.

This paper intends to present a novel optimal trajectory planning method for obstacle avoidance on highways. Firstly, a mapping from the road Cartesian coordinate system to the road Frenet-based coordinate system is built, and the path lateral offset in the road Frenet-based coordinate system is represented by a function of quintic polynomial respecting the traveled distance along the road centerline. With different terminal conditions regarding its position, heading and curvature of the endpoint, and together with initial conditions of the starting point, the path planner generates a bunch of candidate paths via solving nonlinear equation sets numerically. A path selecting mechanism is further built which considers a normalized weighted sum of the path length, curvature, consistency with the previous path, as well as the road hazard risk.

The driver's face detection and tracking method important for Advanced Driver Assistance Systems (ADAS) and autonomous driving in various situations. The deep SORT algorithm has integrated appearance information, the motion model and the intersection-over-union (IOU) distance methods, and has been applied to face tracking, but it depends on detection information in every frame. Once the detection information lacks, the deep SORT algorithm will wait until the target detects bounding boxes appear again, even if the target didn’t disappear or shield. Hence, we propose to use a new tracker that not completely depend on the detection algorithm to cascade with the deep SORT algorithm to realize stable driver's face tracking. At first, the driver's face detection and tracking will be accomplished by the MTCNN-deep-SORT algorithm.

Aerodynamic noise generated in a miniature car had been evaluated using numerical simulation. Large Eddy Simulation (LES) was applied to analyze the transient flow field and the Ffowcs Williams-Hawkings (FW-H) acoustic analogy was employed to conduct acoustic analysis. The time accurate flow data was obtained using a finite volume flow solver on an unstructured grid. The flow field around the rear view mirror was obtained by numerical for two cases with different side view mirrors. Moreover, the distribution of acoustic source was predicted on side windows, and the aerodynamic noise was lowed through optimizing the shape of the rear view mirror and some experiments were done to validate the effect. Present study ascertained the feasibility and applicability of finite volume method (FVM) with SGS model towards prediction of aerodynamic noise generated in production vehicle.

Modeling and simulation are commonly used in all stages of the design process. This is particularly vital to the success of systems engineering projects where the system under consideration is complex and involves interactions between many interdisciplinary subsystems. In the refining stages of the design process (after concept selection), models and simulations can be used to refine and optimize a system with respect to the decision maker’s objectives. In this paper, a dynamic model of a hydraulic backhoe serves as a test-bed for a large-scale sensitivity analysis and subsequent optimization of the most significant design parameters. The model is optimized under uncertainty with respect to a multi-attribute utility function that includes fuel consumption, cost of the key components, and machine performance.

Suspension system dynamics can be obtained by various methods and vehicle design has gained great advantages over the dynamics analysis. By employing the new Udwadia-Kalaba equation, we endeavor some attempts on its application to dynamic modeling of vehicle suspension systems. The modeling approach first segments the suspension system into several component subsystems with kinematic constraints at the segment points released. The equations of motion of the unconstrained subsystems are thus easily obtained. Then by applying the second order constraints, the suspension system dynamics is then obtained. The equations are of closed-form. Having the equations obtained, we then show its application on dynamical load analysis. The solutions for the dynamical loads at interested hard points are obtained. We use the double wishbone suspension to show the systematic approach is easy handling.