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To advance vehicle lightweighting, chopped carbon fiber sheet molding compound (SMC) is identified as a promising material to replace metals. However, there are no effective tools and methods to predict the mechanical property of the chopped carbon fiber SMC due to the high complexity in microstructure features and the anisotropic properties. In this paper, a Representative Volume Element (RVE) approach is used to model the SMC microstructure. Two modeling methods, the Voronoi diagram-based method and the chip packing method, are developed to populate the RVE. The elastic moduli of the RVE are calculated and the two methods are compared with experimental tensile test conduct using Digital Image Correlation (DIC). Furthermore, the advantages and shortcomings of these two methods are discussed in terms of the required input information and the convenience of use in the integrated processing-microstructure-property analysis.

The components in a hybrid electric vehicle (HEV) powertrain include the battery pack, an internal combustion engine, and the electric machines such as motors and possibly a generator. These components generate a considerable amount of heat during driving cycles. A robust thermal management system with advanced controller, designed for temperature tracking, is required for vehicle safety and energy efficiency. In this study, a hybridized mid-size truck for military application is investigated. The paper examines the integration of advanced control algorithms to the cooling system featuring an electric-mechanical compressor, coolant pump and radiator fans. Mathematical models are developed to numerically describe the thermal behavior of these powertrain elements. A series of controllers are designed to effectively manage the battery pack, electric motors, and the internal combustion engine temperatures.

The reach capability of drivers is currently represented in vehicle design practice in two ways. The SAE Recommended Practice J287 presents maximum reach capability surfaces for selected percentiles of a generic driving population. Driver reach is also simulated using digital human figure models. In typical applications, a family of figure models that span a large range of the target driver population with respect to body dimensions is positioned within a digital mockup of the driver's workstation. The articulated segments of the figure model are exercised to simulate reaching motions and driver capabilities are calculated from the constraints of the kinematic model. Both of these current methods for representing driver reach are substantially limited. The J287 surfaces are not configurable for population characteristics, do not provide the user with the ability to adjust accommodation percentiles, and do not provide any guidance on the difficulty of reaches that are attainable.

A special spot weld element (SWE) is presented for simplified representation of spot joints in complex structures for structural durability evaluation using the mesh-insensitive structural stress method. The SWE is formulated using rigorous linear four-node Mindlin shell elements with consideration of weld region kinematic constraints and force/moments equilibrium conditions. The SWEs are capable of capturing all major deformation modes around weld region such that rather coarse finite element mesh can be used in durability modeling of complex vehicle structures without losing any accuracy. With the SWEs, all relevant traction structural stress components around a spot weld nugget can be fully captured in a mesh-insensitive manner for evaluation of multiaxial fatigue failure.

In applications of the Energy Finite Element Analysis (EFEA) there is an increasing need for developing comprehensive models with a large number of elements which include both structural and interior fluid elements, while certain parts of the structure are considered to be exposed to an external fluid loading. In order to accommodate efficient computations when using simulation models with a large number of elements, joints, and domains, a substructuring computational capability has been developed. The new algorithm is based on dividing the EFEA model into substructures with internal and interface degrees of freedom. The system of equations for each substructure is assembled and solved separately and the information is condensed to the interface degrees of freedom. The condensed systems of equations from each substructure are assembled in a reduced global system of equations. Once the global system of equations has been solved the solution for each substructure is pursued.

Engineering components and systems are usually subjected to mixed-mode and multiaxial fatigue loadings, and these conditions should be considered in product durability and reliability design and the maintenance of aging equipment, especially mission-critical components and systems. However, modeling the damage and degradation processes under these complex loading conditions is difficult and challenging task because not only the concepts, such as range, mean, peak, valley etc., developed for uniaxial loading usually cannot be directly transferred to mixed-mode and multiaxial loadings, but also some very unique phenomena related to these complex loading conditions. One such a phenomenon is the loading path effect that can be simply described as: out-of-phase loading is more damaging than in-phase loading for some ductile materials.

ADAS features development involves multidisciplinary technical fields, as well as extensive variety of different sensors and actuators, therefore the early design process requires much more resources and time to collaborate and implement. This paper will demonstrate an alternative way of developing prototype ADAS concept features by using remote control car with low cost hobby type of controllers, such as Arduino Due and Raspberry Pi. Camera and a one-beam type Lidar are implemented together with Raspberry Pi. OpenCV free open source software is also used for developing lane detection and object recognition. In this paper, we demonstrate that low cost frame work can be used for the high level concept algorithm architecture, development, and potential operation, as well as high level base testing of various features and functionalities. The developed RC vehicle can be used as a prototype of the early design phase as well as a functional safety testing bench.

The purpose of this paper is to demonstrate the impact of low- floor bus seating configuration, passenger load factor (PLF) and passenger characteristics on individual boarding and disembarking (B-D) times -a key component of vehicle dwell time and overall transit system performance. A laboratory study was conducted using a static full-scale mock-up of a low-floor bus. Users of wheeled mobility devices (n=48) and walking aids (n=22), and visually impaired (n=17) and able-bodied (n=17) users evaluated three bus layout configurations at two PLF levels yielding information on B-D performance. Statistical regression models of B-D times helped quantify relative contributions of layout, PLF, and user characteristics viz., impairment type, power grip strength, and speed of ambulation or wheelchair propulsion. Wheeled mobility device users, and individuals with lower grip strength and slower speed were impacted greater by vehicle design resulting in increased dwell time.

This paper directs attention to a specific region of the air-bag deployment process. Both experimental and analytical results are presented. Experimental procedures and their results are presented along with a two dimensional unsteady isentropic CFD model and a empirical gas-jet model.

Simultaneous measurements of the radial and the tangential components of velocity are obtained in a high-speed, direct-injection diesel engine typical of automotive applications. Results are presented for engine operation with fuel injection, but without combustion, for three different swirl ratios and four injection pressures. With the mean and fluctuating velocities, the r-θ plane shear stress and the mean flow gradients are obtained. Longitudinal and transverse length scales are also estimated via Taylor's hypothesis. The flow is shown to be sufficiently homogeneous and stationary to obtain meaningful length scale estimates. Concurrently, the flow and injection processes are simulated with KIVA-3V employing a RNG k-ε turbulence model. The measured turbulent kinetic energy k, r-θ plane mean strain rates ( 〈Srθ〉, 〈Srr〉, and 〈Sθθ〉 ), deviatoric turbulent stresses , and the r-θ plane turbulence production terms are compared directly to the simulated results.

An experimental heat release rate analysis was conducted on a six cylinder, 12.7 liter Detroit Diesel Series 60 turbocharged engine operating under steady state conditions. The overall chemical, or gross, rate of heat release and the net apparent rate of heat release were determined from experimental measurements. The gross, time averaged, heat release rate was determined by two separate concepts/methods using exhaust gas concentration measurements from the Nicolet Rega 7000 Real Time Exhaust Gas Analyzer and the measured exhaust gas flow rate. The net apparent rate of heat release was determined from the in-cylinder pressure measurements for each of the six cylinders, averaged over 80 cycles. These pressure measurements were obtained using a VXI based Tektronix data acquisition system and LabVIEW software. A computer algorithm then computed the net apparent rate of heat release from the averaged in-cylinder pressure measurements.

A new approach to driver seat-position modeling is presented. The equations of the Seating Accommodation Model (SAM) separately predict parameters of the distributions of male and female fore/aft seat position in a given vehicle. These distributions are used together to predict specific percentiles of the combined male-and-female seat-position distribution. The effects of vehicle parameters-seat height, steering-wheel-to-accelerator pedal distance, seat-cushion angle, and transmission type-are reflected in the prediction of mean seat position. The mean and standard deviation of driver population stature are included in the prediction for the mean and standard deviation of the seat-position distribution, respectively. SAM represents a new, more flexible approach to predicting fore/aft seat-position distributions for any driver population in passenger vehicles. Model performance is good, even at percentiles in the tails of the distribution.

Industrial tasks performed by standing workers are among those most commonly simulated using digital human models. Workers often walk, turn, and take acyclic steps as they perform these tasks. Current h uman modeling tools lack the capability to simulate these whole body motions accurately. Most models simulate walking by replaying joint angle trajectories corresponding to a general gait pattern. Turning is simulated poorly if at all, and violations of kinematic constraints between the feet and ground are common. Moreover, current models do not accurately predict foot placement with respect to loads and other hand targets, diminishing the utility of the associated ergonomic analyses. A new approach to simulating stepping and walking in task-oriented activities is proposed. Foot placements and motions are predicted from operator and task characteristics using empirical models derived from laboratory data and validated using field data from an auto assembly plant.

This paper investigates the effects of manufacturing variations in fuel injectors on the engine performance with emphasis on emissions. The variations are taken into consideration within a Reliability-Based Design Optimization (RBDO) framework. A reduced version of Multi-Zone Diesel engine Simulation (MZDS), MZDS-lite, is used to enable the optimization study. The numerical noise of MZDS-lite prohibits the use of gradient-based optimization methods. Therefore, surrogate models are developed to filter out the noise and to reduce computational cost. Three multi-objective optimization problems are formulated, solved and compared: deterministic optimization using MZDS-lite, deterministic optimization using surrogate models and RBDO using surrogate models. The obtained results confirm that manufacturing variation effects must be taken into account in the early product development stages.

Connected autonomy brings with it the means of significantly increasing vehicle Energy Economy (EE) through optimal Eco-Driving control. Much research has been conducted in the area of autonomous Eco-Driving control via various methods. Generally, proposed algorithms fall into the broad categories of rules-based controls, optimal controls, and meta-heuristics. Proposed algorithms also vary in cost function type with the 2-norm of acceleration being common. In a previous study the authors classified and implemented commonly represented methods from the literature using real-world data. Results from the study showed a tradeoff between EE improvement and run-time and that the best overall performers were meta-heuristics. Results also showed that cost functions sensitive to the 1-norm of acceleration led to better performance than those which directly minimize the 2-norm.

Exhaust gas rebreathing is considered to be a practical enabler that could be used in HCCI production engines. Recent experimental work at the University of Michigan demonstrates that the combustion characteristics of an HCCI engine using large amounts of hot residual gas by rebreathing are very sensitive to engine thermal conditions. This computational study addresses HCCI engine operation with rebreathing, with emphasis on the effects of engine thermal conditions during transient periods. A 1-D cycle simulation with thermal networks is carried out under load and speed transitions. A knock integral auto-ignition model, a modified Woschni heat transfer model for HCCI engines and empirical correlations to define burn rate and combustion efficiency are incorporated into the engine cycle simulation model. The simulation results show very different engine behavior during the thermal transient periods compared with steady state.

Wet clutches are complex hydrodynamic devices used in both conventional and electrified drivetrain systems. They couple or de-couple powertrain components for applications such as automatic shifting, engine disconnect and torque vectoring. Clutch engagement behaviors vary greatly, depending on design parameters and operating conditions. Because of their direct impact on vehicle drivability and fuel economy, a predictive CAE model is desired for enabling analytical design verification processes. During engagement, a wet clutch transmits torque through viscous shear and asperity contact. A conventional Coulomb’s model, which is routinely utilized in shift simulations, is inadequate to capture non-linear hydrodynamic effects for higher fidelity analysis. Extensive research has been conducted over the years to derive hydrodynamic torque transfer models based on 1D squeeze film or 3D CFD. They are typically coupled with an elastic asperity contact model for mechanical torque transfer.

Most current applications of digital human figure models for ergonomic assessments of manual tasks focus on the analysis of a static posture. Tools available for static analysis include joint-specific strength, calculation of joint moments, balance maintenance capability, and low-back compression or shear force estimates. Yet, for many tasks, the inertial loads due to acceleration of body segments or external objects may contribute significantly to internal body forces and tissue stresses. Due to the complexity of incorporating the dynamics of motion into analysis, most commercial software packages used for ergonomic assessment do not have the capacity to include dynamic effects. Thus, commercial human modeling packages rarely provide an opportunity for the user to determine if a static analysis is sufficient.

Assessments of reach capability using human figure models are commonly performed by exercising each joint of a kinematic chain, terminating in the hand, through the associated ranges of motion. The result is a reach envelope determined entirely by the segment lengths, joint degrees of freedom, and joint ranges of motion. In this paper, the validity of this approach is assessed by comparing the reach envelopes obtained by this method to those obtained in a laboratory study of men and women. Figures were created in the Jack human modeling software to represent the kinematic linkages of participants in the laboratory study. Maximum reach was predicted using the software's kinematic reach-envelope generation methods and by interactive manipulation. Predictions were compared to maximum reach envelopes obtained experimentally. The findings indicate that several changes to the normal procedures for obtaining maximum reach envelopes for seated tasks are needed.