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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.

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.

Currently in the automotive industry, most software source code is manually generated (i.e., hand written). This manually generated code is written to satisfy requirements that are generally specified or captured in an algorithm document. However, this process can be very error prone since errors can be introduced during the manual translation of the algorithm document to code. A better method would be to automatically generate code directly from the algorithm document. Therefore, the automotive industry is striving to model new and existing algorithms in an executable-modeling paradigm where code can be automatically generated. The advent of executable models together with automatic code generation should allow the translation of model to code to be error free, and this error-free status can be confirmed through testing. A three-stage process is presented to functionally verify the model, functionally verify the automatically-generated code, and structurally verify the code.

Robust autonomous navigation in unstructured environments is an unsolved problem and critical to the operation of autonomous military and rescue ground vehicles. Two-dimensional path planners operating on occupancy grids or costs maps can produce infeasible paths when the operational area includes complex terrain. Recently, sample-based path planners that plan on LiDAR-acquired point-cloud maps have been proposed. These approaches require no discretization of the operational area and provide direct pose estimation by modeling vehicle and terrain interaction. In this paper, we show that direct sample-based path planning on point clouds is effective and robust in unstructured environments. Robustness is demonstrated by completing a system parameter sensitivity analysis of the system in an Unreal simulation environment and partnered with field validation.

The concept of product or system function is considered as described in the Taguchi System of Quality Engineering. The importance of transfer functions is also discussed and a review of conventional value analysis techniques is given. This paper proposes a combination of the principles of robust design and value methodology to enable on-target functionality and direct cost allocation early in the product development process. The discussion on integration of value analysis principles in robust design methodology is provided considering the six sigma environment.

The Kalman and Vold-Kalman order tracking filters have been implemented in commercial software since the early 90's. There are several mathematical formulations of filters that have been implemented by different software vendors. However, there have not been any papers that have been published which sufficiently explain the math behind these filters and discuss the actual implementations of the filters in software. In addition, upon generating the equations represented by these filters, solving the equations for datasets in excess of several hundred thousand datapoints is not trivial and has not been discussed in the literature. The papers which have attempted to cover these topics are generally vague and overly mathematically eloquent but not easily understandable by a practicing engineer.

Since 1985, the Body Division of the Automotive Corrosion and Prevention Committee of SAE (ACAP) has conducted biannual surveys of automotive body corrosion in the Detroit area. The purpose of these surveys is to track industry wide corrosion protection improvements and to make this information available for public consumption. The survey consists of a closed car parking lot survey checking for perforations, blisters, and surface rust. This paper reports the results of the five surveys conducted to date.

Future automobiles are required to support an increasing number of complex, distributed functions such as active safety and X-by-wire. Because of safety concerns and the need to deliver correct designs in a short time, system properties should be verified in advance on function models, by simulation or model checking. To ensure that the properties still hold for the final deployed system, the implementation of the models into tasks and communication messages should preserve properties of the model, or in general, its semantics. FlexRay offers the possibility of deterministic communication and can be used to define distributed implementations that are provably equivalent to synchronous reactive models like those created from Simulink. However, the low level communication layers and the FlexRay schedule must be carefully designed to ensure the preservation of communication flows and functional outputs.

For the assessment of vehicle acoustics in the early design stages of a vehicle program, the use of full vehicle SEA models is becoming the standard analysis method in the US automotive industry. One benefit is that OEM's and Tier 1 suppliers are able to cascade lower level acoustic performance targets for NVH systems and components. Detailed SEA system level models can be used to assess the performance of systems such as dash panels, floors and doors, however, the results will be questionable until test data Is available. Correlation can be accomplished with buck testing, which is a common practice in the automotive industry for assessing the STL (sound transmission loss) of vehicle level components. The opportunity to conduct buck testing can be limited by the availability of representative bodies to be cut into bucks and the availability of a transmission loss suite with a suitably large opening.

The traditional method of dynamic characterization of elastomers used in industry has largely been based on sinusoidal input excitation. Discrete frequency sine wave signals at specified amplitudes are used to excite the elastomer in a step-sine sweep fashion. This paper will examine new methods of characterization using various broadband input excitations. These different inputs include continuous sine sweep (chirp), shaped random, and acquired road profile data. Use of these broadband data types is expected to provide a more accurate representation of conditions seen in the field, while helping to eliminate much of the interpolation that is inherent with the classic discrete step-sine technique. Results of the various input types are compared in this paper with those found using the classic discrete step-sine input.

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.

It has the aim to discuss the evolution of electronics components, integrated circuits, new transistors concepts and associate its importance in the automotive modules. Today, the challenge is to have devices which consume less power, suitable for high-energy radiation environment, less parasitic capacitances, high speed, easier device isolation, high gain, easier scale-down of threshold voltage, no latch-up and higher integration density. The improvement of those characteristics mentioned and others in the electronic devices enable the automotive industry to have a more robust product and give the possibility to integrate new features in comfort, safety, infotainment and telematics modules. Finally, the intention is to discuss advanced structures, such as the silicon-on-insulator (SOI) and show how it affects the electronics modules applied for the automotive area.

Because of the wide array of commercial or market fuels in use today, all components, engines, and vehicles must be vigorously tested to confirm emissions performance, driveability and material compatibility. To support the requirements of the modern global vehicle engineer, various testing and validation fuels are used to represent quality that ranges from good to poor for fuel that are currently in the market or that will be introduced into the market in the future. Testing and validation fuels have been developed specifically for emissions compliance testing to meet new environmental regulations in different parts of the world, vehicle performance and reliability needs. Demand for new testing and validation fuels will continue to grow.

Currently, OEMs worldwide are emphasizing more upon development and implementation of new electrical features on existing vehicles [3]. However, development and implementation of new electrical features on existing vehicle platforms create architectural as well as packaging challenges. These challenges are augmented due to following: the need to implement such features across different body styles of vehicles that are based on same or different architectures different requirement for a feature based upon market requirement This paper analyzes these challenges to help in providing design solutions for successful implementation of new features as per following requirements: 1 Provide optimum design to have low cost and high quality for existing vehicle platforms 2 Provide spare capacity while designing new vehicles or architectures

Off road navigation demands ground robots to traverse complex and often changing terrain. Classification and assessment of terrain can improve path planning strategies by reducing travel time and energy consumption. In this paper we introduce a terrain classification and assessment framework that relies on both exteroceptive and proprioceptive sensor modalities. The robot captures an image of the terrain it is about to traverse and records corresponding vibration data during traversal. These images are manually labelled and used to train a support vector machine (SVM) in an offline training phase. Images have been captured under different lighting conditions and across multiple locations to achieve diversity and robustness to the model. Acceleration data is used to calculate statistical features that capture the roughness of the terrain whereas angular velocities are used to calculate roll and pitch angles experienced by the robot.

Several very different order tracking and analysis techniques for rotating equipment have been developed recently that are available in commercial noise and vibrations software packages. Each of these order tracking methods has distinct trade-offs for many common applications and very specific advantages for special applications in sound quality or noise and vibrations troubleshooting. The Kalman, Vold-Kalman, Computed Order Tracking, and the Time Variant Discrete Fourier Transform as well as common FFT based order analysis methods will all be presented. The strengths and weaknesses of each of the methods will be presented as well as the highlights of their mathematical properties. This paper is intended to be an overview of currently available technology with all methods presented in a common format that allows easy comparison of their properties. Several analytical examples will be presented to thoroughly document each methods' behavior with different types of data.

The advancement in embedded systems and positional accuracy with base station GPS modules created opportunity to develop high performance autonomous ground vehicles. However, the development of vehicle model and making accurate state estimations play vital role in reducing the cross track error. The present research focus on developing Linear Quadratic Gaussian (LQG) with Kalman estimator for autonomous ground vehicle to track various routes, that are made with the series of waypoints. The model developed in the LQG controller is a kinematic bicycle model, which mimics 1/5th scale truck. Further, the cubic spline fit has been used to connect the waypoints and generate the continuous desired/target path. The testing and implementation has been done at APS labs, MTU on the mentioned vehicle to study the performance of controller. Python has been used for simulations, controller coding and interfacing the sensors with controller.

This paper aims to provide the experimental and numerical investigation of a single fuel droplet impingement on the different wall conditions to understand the detailed impinging dynamic process. The experimental work was carried out at the room temperature and pressure except for the variation of the impinged wall temperature. A high-speed camera was employed to capture the silhouette of the droplet impinging on wall process against a collimated light. Water, diesel, n-dodecane, and n-heptane were considered as four different droplets and injected from a precision syringe pump with the volume flow rate of 0.2 mL/min at various impact Weber numbers. The impingement outcomes after droplet impacting on the wall include stick, spread, rebound and splash, which depend on the controlling parameters of Weber number, Reynolds number, liquid and surface properties, etc.

Multiple automotive applications exist for small electric motors that are activated by vehicle occupants for various functions such as window lifts and seat adjusters. For such a motor to be described as high quality, not only should the sound it produces be low in amplitude, but it also needs to be free from pulsations and variations that might occur during its (otherwise) steady-state operation. If a motor’s sound contains pulsations or variations between 2 and 8 cycles per second, the variation is described as warble. To establish performance targets for warble noise at both the vehicle and component level a way to measure and quantify the warble noise must be established. Building on existing sound quality metrics such as loudness and pitch variation, a method is established by which processed sound data is put through a secondary operation of Fourier analysis.

The Society of Automotive Engineers' (SAE) Clean Snowmobile Challenge 2004 (CSC 2004) was held at Michigan Technological University in Houghton, Michigan, from March 15 - 20, 2004. The Clean Snowmobile Challenge has been a competition in the SAE Collegiate Design Series since 2000, and began in Jackson Hole, Wyoming, as a response to rising concerns about snowmobiling in environmentally-sensitive areas. Teams from fifteen universities competed in CSC 2004. The winning snowmobile (sled) was developed by the University of Wisconsin, Madison, and featured a four-stroke engine with electronic fuel injection (EFI), a two-stage tuned muffler, and catalytic exhaust aftertreatment. A hybrid-electric design was used to increase the snowmobile's powertrain output and improve acceleration. [8] Teams should be competitive in all events to gain enough points to win the competition.