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Optimizing the trade-off between reliability and cost of operating a microgrid, including vehicles as both loads and sources, can be a challenge. Optimal energy management is crucial to develop strategies to improve the efficiency and reliability of microgrids, as well as new communication networks to support optimal and reliable operation. Prior approaches modeled the grid using MATLAB, but did not include the detailed physics of loads and sources, and therefore missed the transient effects that are present in real-time operation of a microgrid. This article discusses the implementation of a physics-based detailed microgrid model including a diesel generator, wind turbine, photovoltaic array, and utility. All elements are modeled as sources in Simulink. Various loads are also implemented including an asynchronous motor. We show how a central control algorithm optimizes the microgrid by trying to maximize reliability while reducing operational cost.

Weight reduction is very important in automotive design because of stringent demand on fuel economy. Structural optimization of dynamic systems using finite element (FE) analysis plays an important role in reducing weight while simultaneously delivering a product that meets all functional requirements for durability, crash and NVH. With advancing computer technology, the demand for solving large FE models has grown. Optimization is however costly due to repeated full-order analyses. Reanalysis methods can be used in structural vibrations to reduce the analysis cost from repeated eigenvalue analyses for both deterministic and probabilistic problems. Several reanalysis techniques have been introduced over the years including Parametric Reduced Order Modeling (PROM), Combined Approximations (CA) and the Epsilon algorithm, among others.

It is challenging to perform probabilistic analysis and design of large-scale structures because probabilistic analysis requires repeated finite element analyses of large models and each analysis is expensive. This paper presents a methodology for probabilistic analysis and reliability based design optimization of large scale structures that consists of two re-analysis methods; one for estimating the deterministic vibratory response and another for estimating the probability of the response exceeding a certain level. The deterministic re-analysis method can analyze efficiently large-scale finite element models consisting of tens or hundreds of thousand degrees of freedom and large numbers of design variables that vary in a wide range. The probabilistic re-analysis method calculates very efficiently the system reliability for many probability distributions of the design variables by performing a single Monte Carlo simulation.

High-fidelity finite element (FE) tire-snow interaction models have the advantage of better understanding the physics of the tire-snow system. They can be used to develop semi-analytical models for vehicle design as well as to design and interpret field test results. For off-terrain conditions, there is a high level of uncertainties inherent in the system. The FE models are computationally intensive even when uncertainties of the system are not taken into account. On the other hand, field tests of tire-snow interaction are very costly. In this paper, dynamic metamodels are established to interpret interaction forces from FE simulation and to predict those forces by using part of the FE data as training data and part as validation data. Two metamodels are built based upon the Krieging principle: one has principal component analysis (PCA) taken into account and the other does not.

Vehicle handling and stability performances are greatly determined by non-steady state (NSS) tire cornering properties. Analytical derivation of NSS tire cornering models are presented in this paper based on Pacejka's string-concept assumption, in which carcass is assumed to be a stretched string with lateral deformation and lateral relaxation. The lateral inputs of the models are either displacement-based (lateral displacement and yaw angle) or slip-based (slip angle and turn slip). The transient deformations in spatial domain in both longitudinal and lateral directions are obtained directly from geometric relationship of contact patch. The additional self-aligning moment due to longitudinal deformation of contact patch after effect of tire width is considered is also achieved according to geometric relationship of contact patch in longitudinal direction and two transient geometric conditions of contact point.

In this research, off-road vehicle simulation is performed with tire-soil interaction model. The predictive semi-analytical model, which is originally developed for tire-snow interaction model by Lee [4], is applied as a tire-soil interaction model and is implemented to MSC/ADAMS, commercial multi-body dynamic software. It is applied to simulate the handling maneuver of military vehicle HMMWV. Two cases are simulated with Michigan sandy loam soil property. Each case has two maneuvers, straight-line brake and step steer (J-turn). First, tire-soil interaction model and conventional on-road tire model are simulated on the flat road of the same frictional coefficient. The proposed tire-soil interaction model provided larger force under the same slip. Second, the same maneuvers are performed with real off-road frictional coefficient. The proposed tire-soil model can be validated and the behavior of the off-road vehicle can be identified through two simulation cases.

With increasing demand for cost-effective fuel cells, it is essential to investigate alternative materials for components of the fuel cells. The objective of this paper is to implement elastomeric materials (silicon rubber) for the use of bipolar plates in a polymer electrolyte membrane fuel cell. Two different types of conductive fillers, a graphite fiber and flake, were added at different concentrations to a two-component silicone rubber slurry. Electrical, thermal and mechanical properties of the composite material were investigated. Comparable electrical and thermal conductivities were achieved to that of commercially available plates. The silicone rubber based composite material maintained elastomeric properties for improved sealing of cell fluid reactants and products.

An application of variation simulation for predicting vehicle interior driveline vibration is presented. The model, based on a “Monte Carlo”-style approach, predicts the noise, vibration and harshness (NVH) response of the vehicle driveline based on distributions of imbalance and runout derived from manufacturing production variation (the forcing function) and the vehicle's sensitivity to the forcing function. The model is used to illustrate the change in vehicle interior vibration that results when changes are made to production variation for runout and imbalance of driveline components, and how those same changes result in different responses based on vehicle sensitivity.

Selecting the right transportation platform is challenging, whether it is at a personal level or at an organizational level. In settings where predominantly the functional aspects rule the decision making process, defining the mobility of a vehicle is critical for comparing different offerings and making acquisition decisions. With the advent of intelligent vehicles, exhibiting partial to full autonomy, this challenge is exacerbated. The same vehicle may traverse independently and with greater tolerance for acceleration than human occupied vehicles, while, at the same time struggle with obstacle avoidance. The problem presents itself at the individual vehicle sensing level and also at the vehicle/fleet level. At the sensing and information level, one can be looking at issues of latency, bandwidth and optimal information fusion from multiple sources including privileged sensing. At the overall vehicle level, one focuses more on the ability to complete missions.

Durability of automotive structures is a primary engineering consideration that is evaluated during a vehicle's design and development. In addition, it is a basic expectation of consumers, who demand ever-increasing levels of quality and dependability. Automakers have developed corporate requirements for vehicle system durability which must be met before a products is delivered to the customer. To provide early predictions of vehicle durability, prior to the construction and testing of prototypes, it is necessary to predict the forces generated in the vehicle structure due to road inputs. This paper describes an application of the “virtual proving ground” approach for vehicle durability load prediction for a vehicle on proving ground road surfaces. Correlation of the results of such a series of simulations will be described, and the modeling and simulation requirements to provide accurate simulations will be presented.

Factorial analyses of stress concentrations at the bolt thread root based on finite element models are presented in this paper. A full bolted joint including a bolt, a nut, and fastened members were modeled using solid elements. Bolt and bolt threads were meshed in detail in 3-dimensional mode, with their interaction being only the direct load transfer between the bolt and nut. Statistical design of experiments was conducted to identify the factors and two-factor interactions, which may have impact on the stress concentration at the bolt thread root.

All the frictional forces developed from tire-snow interfaces are closely associated with snow depth and snow sinkage. One of the important differences between tire-soil interaction and tire-snow interaction is that the latter is explicitly snow depth dependent. Based on our established depth-dependent upper bound indentation model, the effects of snow depth on tire-snow interaction are presented in this paper. Snow is considered as a pressure-sensitive Drucker-Prager material. The required snow material parameters of the model are Drucker-Prager material constants only. Snow sinkages, for longitudinal slip close to zero, under different snow depths are numerically solved through the sinkage solver. The comparison between sinkage obtained analytically and the sinkage computed from finite element simulation is very good.

Snow-covered ground severely affects vehicle mobility in cold regions due to low friction coefficients and snow sinkage. Simulation and evaluation of vehicle mobility in cold regions require real-time friendly tire-snow interaction models that are applicable for quasi-real driving conditions. Recently, we have developed tire-snow dynamics models that are snow depth dependent, sinkage dependent and normal load dependent. The number of model parameters is reduced through theoretical analysis of normal indentation, contact pressure and shear stress within the tire-snow interface. In-plane and out-of-plan motion resistances and traction forces (gross traction and net traction) are analytically calculated for combined slip conditions.

There is a scarcity of comprehensive tire-snow interaction models for combined (longitudinal and lateral) slips. Current tire-snow interaction empirical and finite element models mostly focus on force-slip relationships in the longitudinal direction only, following the approach used for tire-soil interaction models. One of the major differences between tire-snow and tire-soil interactions is that the former is typically depth-dependent, especially for shallow snow. Our approach in the modeling of tire-snow interaction is to rely on the underlying physics of the phenomena, wherever we could, and use test data (or finite element simulation results in the absence of test data) to calibrate the required model parameters. We also make contact with on-road models and extend them for off-road applications.

Countless articles and publications3,4,5 have documented and proven the efficacy, benefits and value of operating within a lean system. Furthermore, there exists common agreement amongst leading organizations successfully implementing a lean system that in order to do so it must take into consideration the entire enterprise, that is, from supplier to customer and everything in between6. One of the core issues this paper addresses is when the optimal time is to train and educate the people who currently have, or will have, influence over the ‘enterprise’.

Motivated by experiences in the Formula SAE® competition, an engine control unit (ECU) was designed, developed and tested at Oakland University. A systems approach was taken in which the designs of the electronic architecture and software were driven by the mechanical requirements and operational needs of the engine, and by the need for dynamometer testing and tuning functions. An ECU, powered by a 68HC12 microcontroller was developed, including a four-layer circuit board designed for EMC. A GUI was written with Visual C++® for communication with a personal computer (PC). The ECU was systematically tested with an engine simulator, a 2L Ford engine and a 600cc Honda engine, and finally in Oakland's 2004 FSAE vehicle.

The coefficient of friction between surfaces is an important criterion for predicting metal behavior during sheet metal stamping processes. This research introduces an innovative technique to find the coefficient of friction on a lubricated aluminum sheet metal surface by simulating the industrial manufacturing stamping process while using 3D digital image correlation (3D-DIC) to track the deformation. During testing, a 5000 series aluminum specimen is placed inside a Stretch-Bend-Draw Simulator (SBDS), which operates with a tensile machine to create a stretch and bend effect. The friction coefficient at the contact point between an alloy sheet metal and a punch tool is calculated using an empirical equation previously developed. In order to solve for the unknown friction coefficient, the load force and the drawback force are both required. The tensile machine software only provides the load force applied on the specimen by the load cell.

Unexpected severe failures occur during the warm forming procedure of carbon fiber material due to the existence of extremely large deformation/strain. To evaluate this failure, a good understanding the accurate material property under certain loading is important to evaluate the forming feasibility of carbon fiber material. Also, a clear connection between the fiber orientation and the material property helps to increase the accuracy of the forming prediction. Therefore, an experimental test is needed to evaluate the material property as well as the fiber orientation. In this paper, a uniaxial tension test for the prepreg carbon fiber under the warm forming condition is performed. A halogen lamp is used to heat the specimen to reach the warm forming condition. A 3D Digital Image Correlation (3D-DIC) is utilized to measure the material property and the fiber orientation in this test, along with a DIP system.

The need for transient thermal simulations in vehicle packaging studies has grown rapidly in recent years. To date, the computational costs associated with the transient simulation of 3D conjugate heat transfer phenomena has prohibited the widespread use of full vehicle transient simulations. This paper presents results from a recent study that explored a method to circumvent the computational costs associated with long transient conjugate heat transfer simulations. The proposed method first segregates the thermal structural and fluid physics domains to take advantage of time scale differences. The two domains are then re-coupled to calculate a series of steady state conjugate heat transfer simulations at various vehicle speeds. The local convection terms are then used to construct a set of surrogate models dependent on vehicle speed, that predict the local heat transfer coefficients and the local near wall fluid temperatures.

Springback is a common phenomenon in automotive manufacturing processes, caused by the elastic recovery of the internal stresses during unloading. A thorough understanding of springback is essential for the design of tools used in sheet metal forming operations. A DBS (Draw-bead Simulator) has been used to simulate the forming process for two different sheet metals: aluminum and steel. Two levels of pulling force and two die radii have been enforced to the experimental process to get different springback. Also, the Digital Image Correlation (DIC) system has been adopted to capture the sheet contour and measure the amount of side-wall-curl (sheet springback) after deformation. This paper presents the influence of the material properties, force, and die radius on the deformation and springback after forming. A thorough understanding of this phenomenon is essential, seeing that any curvature in the part wall can affect quality and sustainability.