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Since transient vehicle HVAC computational fluids (CFD) simulations take too long to solve in a production environment, the goal of this project is to automatically create a lumped-parameter flow network from a steady-state CFD that solves nearly instantaneously. The data mining algorithm k-means is implemented to automatically discover flow features and form the network (a reduced order model). The lumped-parameter network is implemented in the commercial thermal solver MuSES to then run as a fully transient simulation. Using this network a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track localized temperatures near specific objects (such as equipment in vehicles).

Battery temperature variations have a strong effect on both battery aging and battery performance. Significant temperature variations will lead to different battery behaviors. This influences the performance of the Hybrid Electric Vehicle (HEV) energy management strategies. This paper investigates how variations in battery temperature will affect Lithium-ion battery aging and fuel economy of a HEV. The investigated energy management strategy used in this paper is the Equivalent Consumption Minimization Strategy (ECMS) which is a well-known energy management strategy for HEVs. The studied vehicle is a Honda Civic Hybrid and the studied battery, a BLS LiFePO4 3.2Volts 100Ah Electric Vehicle battery cell. Vehicle simulations were done with a validated vehicle model using multiple combinations of highway and city drive cycles. The battery temperature variation is studied with regards to outside air temperature.

Despite numerous research efforts, there is no reliable and widely accepted tool for the prediction of erosion prone material surfaces due to collapse of cavitation bubbles. In the present paper an Erosion Aggressiveness Index (EAI) is proposed, based on the pressure loads which develop on the material surface and the material yield stress. EAI depends on parameters of the liquid quality and includes the fourth power of the maximum bubble radius and the bubble size number density distribution. Both the newly proposed EAI and the Cavitation Aggressiveness Index (CAI), which has been previously proposed by the authors based on the total derivative of pressure at locations of bubble collapse (DP/Dt>0, Dα/Dt<0), are computed for a cavitating flow orifice, for which experimental and numerical results on material erosion have been published. The predicted surface area prone to cavitation damage, as shown by the CAI and EAI indexes, is correlated with the experiments.

To cope with the increasing number of advanced features (e.g., smart-phone integration and side-blind zone alert.) being deployed in vehicles, automotive manufacturers are designing flexible hardware architectures which can accommodate increasing feature content with as fewer as possible hardware changes so as to keep future costs down. In this paper, we propose a formal and quantitative definition of flexibility, a related methodology and a tool flow aimed at maximizing the flexibility of an automotive hardware architecture with respect to the features that are of greater importance to the designer. We define flexibility as the ability of an architecture to accommodate future changes in features with no changes in hardware (no addition/replacement of processors, buses, or memories). We utilize an optimization framework based on mixed integer linear programming (MILP) which computes the flexibility of the architecture while guaranteeing performance and safety requirements.

The Time Variant Discrete Fourier Transform was implemented as a real-time order tracking method using developed software and commercially available hardware. The time variant discrete Fourier transform (TVDFT) with the application of the orthogonality compensation matrix allows multiple tachometers to be tracked with close and/or crossing orders to be separated in real-time. Signal generators were used to create controlled experimental data sets to simulate tachometers and response channels. Computation timing was evaluated for the data collection procedure and each of the data processing steps to determine how each part of the process affects overall performance. Many difficulties are associated with a real-time data collection and analysis tool and it becomes apparent that an understanding of each component in the system is required to determine where time consuming computation is located.

Engineering education at the University level is enhanced by competition-based projects. The SAE Clean Snowmobile Challenge is a prime example of how competition-based engineering education benefits the small engines industry and improves the engineering talent pool of the nation in general. For the past several decades, SAE has encouraged young engineers to compete in designing off road vehicles (Baja SAE ®), small race cars (Formula SAE ®), remote control airplanes (Aero Design ®), high mileage vehicles (Supermileage ®) and robots (Walking Robot ®). Now a new competition, the SAE Clean Snowmobile Challenge ™ (CSC), based on designing a cleaner and quieter snowmobile has led to a new path for young engineers to explore the challenges of designing engines that emit less pollution and noise. The paper will summarize the results of the most recent Clean Snowmobile Challenge 2006 and document the successes of the past seven years of the Challenge.

An interactive tool for predicting the performance of vehicle designs in the pedestrian leg impact test has been developed. This tool allows users to modify the design of a vehicle front structure through the use of a graphical interface, and then evaluates the performance of the design with a response surface. This performance is displayed in the graphical interface, providing the user with nearly instantaneous feedback to his design changes. An example is shown that demonstrates how the tool can be used to help guide the user towards vehicle designs that are likely to improve performance. As part of the development of this tool, a simplified, parametric finite element model of the front structure of the vehicle was created. This vehicle model included eleven parameters that could be adjusted to change the structural dimensions and structural behavior of the model.

Michigan Technological University has established a broad-based university-wide research initiative, termed Wood-to-Wheels (W2W), to develop and evaluate improved technologies for growing, harvesting, converting, and using woody biomass in renewable transportation fuel applications. The W2W program bridges the entire biomass development-production-consumption life cycle with research in areas including forest resources, bioprocessing, engine/vehicle systems, and sustainable decisions. The W2W chain establishes a closed cycle of carbon between the atmosphere, woody biomass, fuels, and vehicular systems that can reduce the accumulation of CO2 in the atmosphere. This paper will summarize the activities associated with the Wood-to-Wheels initiative and describe challenges and the potential benefits that are achievable.

Efficient methods for simulating operators performing part handling tasks in manufacturing plants are needed. The simulation of part handling motions is an important step towards the implementation of virtual manufacturing for the purpose of improving worker productivity and reducing injuries in the workplace. However, industrial assembly tasks are often complex and involve multiple interactions between workers and their environment. The purpose of this paper is to present a series of industrial simulations using the Human Motion Simulation Framework developed at the University of Michigan. Three automotive assembly operations spanning scenarios, such as small and large parts, tool use, walking, re-grasping, reaching inside a vehicle, etc. were selected.

With the current increase in concern and awareness regarding sustainability and energy, a new focus has been placed on the field of engineering. In this realm of focus, how to educate engineers, more specifically how to continually educate engineers to keep up with technology and the changing workforce has become a very important topic of interest. There exists a gap between graduate studies and professional implementation of technology which the Energy Systems Engineering [ESE] program currently in deployment and development between the University of Michigan and General Motors seeks to address. This work outlines current efforts in encouraging new engineers to enter the field, but focuses primarily on continuing and re-educating the workforce to meet the needs of new technologies. Examples of academic-industry cooperation will be discussed, with some focus on the benefit and experience of the student.

Vehicle dynamics simulation with Hardware In the Loop (HIL) has been demonstrated to reduce development and validation time for dynamic control systems. For dynamic control systems such as Anti-lock Braking System (ABS) and Electronic Stability Control (ESC), an accurate vehicle dynamics performance simulation system requires the Electronic Brake Control Module (EBCM) coupled with the vehicles brake system hardware. This kind of HIL simulation-specific software tool can further increase efficiency by means of automation and optimization of the development and validation process. This paper presents a method for HIL vehicle dynamics simulator optimization through Brake Response Time (BRT) correlation. The paper discusses the differences between the physical vehicle and the HIL vehicle dynamics simulator. The differences between the physical and virtual systems are used as factors in the development of a Design Of Experiment (DOE) quantifying HIL simulator performance.

This paper analyzes the control of the series-parallel powersplit used in the 2001 Michigan Tech FutureTruck. An electronic throttle controller is implemented and a new control algorithm is proposed and tested. A vehicle simulation has been created in MATLAB and the control algorithm implemented within the simulation. A program written in C has also been created that implements the control algorithm in the test vehicle. The results from both the simulation and test vehicle are presented and discussed and show a 15% increase in fuel economy. With the increase in fuel economy, and through the use of the original exhaust after treatment, lower emissions are also expected.

Living in the era of rising environmental sensibility and increasing gasoline prices, the development of a new environmentally friendly generation of vehicles becomes a necessity. Hybrid electric vehicles are one means of increasing propulsion system efficiency and decreasing pollutant emissions. In this paper, the series-parallel power-split configuration for Michigan Technological University's FutureTruck is analyzed. Mathematical equations that describe the hybrid power-split transmission are derived. The vehicle's differential equations of motion are developed and the system's need for a controller is shown. The engine's brake power and brake specific fuel consumption, as a function of its speed and throttle position, are experimentally determined. A control strategy is proposed to achieve fuel efficient engine operation. The developed control strategy has been implemented in a vehicle simulation and in the test vehicle.

The induction hardening process involves a complex interaction of electromagnetic heating, rapid cooling, metallurgical phase transformations, and mechanical behavior. Many factors including induction coil design, power, frequency, scanning velocity, workpiece geometry, material chemistry, and quench severity determine a process outcome. This paper demonstrates an effective application of a numerical analysis tool for understanding of induction hardening. First, an overview of the Caterpillar induction simulation tool is briefly discussed. Then, several important features of the model development are examined. Finally, two examples illustrating the use of the computer simulation tool for solving induction-hardening problems related to cracking and distortion are presented. These examples demonstrate the tool's ability to simulate changes in process parameters and latitude of modeling steel or cast iron.

This study investigates a methodology in which the general public's subjective interpretation of vehicle handling and performance can be predicted. Several vehicle handling measurements were acquired, and associated metrics calculated, in a controlled setting. Human evaluators were then asked to drive and evaluate each vehicle in a winter driving school setting. Using the acquired data, multiple linear regression and artificial neural network (ANN) techniques were used to create and refine mathematical models of human subjective responses. It is shown that artificial neural networks, which have been trained with the sets of objective and subjective data, are both more accurate and more robust than multiple linear regression models created from the same data.

The so-called Modified Martempering discussed in this work differs from the standard martempering by that the temperature of the quenching bath is below the Ms point. In spite of the fact the lower temperature increases the severity of quenching, this also usually avoids the bainite formation, and by this reason, it is possible to make a fair comparison between different processes, which result in different microstructures. The present study shows the results in terms of mechanical properties, impact resistance in special of a cold work tool steel class, after being heat treated by the isothermal modified martempering process, as well as a comparison with the conventional quenching and tempering process and the austempering as well.

The innovation term has been so widely misused that the confusion observed among the companies trying to get themselves into the innovation realm is a common and natural consequence. The lack of understanding of the innovation dynamics, flow and metrics generally culminate in a non-well-thought implementation of innovation processes and policies that are usually tragic in the short term. The most common consequences are the loss of credibility of the innovation process in general among leaders and employees, and the loss of credibility of the company as an innovative company among suppliers, partners and customers, causing these companies to abandon this powerful tool and, as consequence, to limit their capabilities to compete in the future. In order to prevent this from happening, companies that were not built upon innovation will need to grow capability and change cultural priorities to match the demands of the innovation process.

In this paper, two correlations, Windowed Selected Moving Autocorrelation (WSMA) and Tri-Correlation (TriC), are introduced and discussed. The WSMA is simpler than the conventional autocorrelation. WSMA uses less data points to obtain useful signal content at desired frequencies. The computational requirement is therefore reduced compared to the conventional autocorrelation. The simplified TriC provides improved signal to noise separation capability than WSMA does while still requiring reduced computational effort compared to the standard autocorrelation. Very often, computation resource limitation exists for real-time applications. Therefore, the WSMA and TriC offer more opportunities for real-time monitor and feedback control applications in the frequency domain due to their high efficiencies. As an example, applications in internal combustion (IC) engine misfire detection are presented. Simulation and vehicle test results are also presented in this paper.

The paper describes an experimental activity on the spatial and temporal liquid- and vapor-phase distributions of diesel fuel at engine-like conditions. The influence of the k-factor (0 and 1.5) of a single-hole axial-disposed injector (0.100 mm diameter and 10 L/d ratio) has been studied by spraying fuel in an optically-accessible constant-volume combustion vessel. A high-speed imaging system, capable of acquiring Mie-scattering and Schlieren images in a near simultaneous fashion mode along the same line of sight, has been developed at the Michigan Technological University using a high-speed camera and a pulsed-wave LED system. The time resolved pair of schlieren and Mie-scattering images identifies the instantaneous position of both the vapor and liquid phases of the fuel spray, respectively. The studies have been performed at three injection pressures (70, 120 and 180 MPa), 23.9 kg/m3 ambient gas density and 900 K gas temperature in the vessel.

Battery State of Charge (SOC) constraints are used to prevent the battery in Hybrid Electric Vehicles (HEVs) from over-charging or over-discharging. These constraints strongly influence the power-split of the HEV. This paper presents results on how Battery State of Charge (SOC) constraints effects Lithium ion battery aging and fuel economy when using the Equivalent Consumption Minimization Strategy (ECMS). The vehicle studied is the Honda Civic Hybrid. The battery used is A123 Systems’ ANR26650 battery cell. Vehicle simulation uses multiple combinations of highway and city drive cycles. For each combination of drive cycles, nine SOC constraints ranges are used. Battery aging is evaluated using a semi-empirical model combined with the accumulated Ah-throughput method which uses, as an input, the battery SOC trajectory from the vehicle simulations. The simulation results provide insight into how SOC constraints effect fuel economy as well as battery aging.