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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).

In order to extend the operability limit of the gasoline compression ignition (GCI) engine, as an avenue for low temperature combustion (LTC) regime, the effects of parametric variations of engine operating conditions on the performance of six-stroke GCI (6S-GCI) engine cycle are numerically investigated, using an in-house 3D CFD code coupled with high-fidelity physical sub-models along with the Chemkin library. The combustion and emissions were calculated using a skeletal chemical kinetics mechanism for a 14-component gasoline surrogate fuel. Authors’ previous study highlighted the effects of the variation of injection timing and split ratio on the overall performance of 6S-GCI engine and the unique mixing-controlled burning mode of the charge mixtures during the two additional strokes. As a continuing effort, the present study details the parametric studies of initial gas temperature, boost pressure, fuel injection pressure, compression ratio, and EGR ratio.

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.

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.

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.

The piezoelectric cylinder pressure transducer is one of the most critical tools for internal combustion (IC) engine research and development. However, not all cylinder pressure transducers perform equally in every application, and the fidelity of transducers can vary across different models and manufacturers. Even slightly dissimilar models from the same manufacturer can have significantly different performance in areas such as sensitivity and resistance to intra-cycle thermal shock. These performance differences can lead to errors and inconsistencies in the calculation of combustion metrics like mean effective pressure (MEP), the polytropic compression and expansion exponents (PolyC and PolyE), and mass fraction burn (MFB) calculations. The variations can lead to suboptimal hardware and calibration choices during the engine development phase.

The paper reviews the role of drawbeads in sheet metal stamping. The design of drawbeads is discussed in depth, with treatment of different bead cross sections, bead end shapes, and bead materials. International standards and practices are included. This is followed by the historical development of the modeling of the drawbead restraining force, starting with basic equilibrium approaches, and leading to the use of the finite element method which permits the study of drawbead effects on sheet metal flow in three dimensions. Finally, the potential of active drawbeads is described based upon ongoing research which is directed toward closed-loop computer control of the stamping process through adjustment of the drawbead penetration.

Recent trends in signal processing have led to the discovery and implementation of wavelets as tools of many different applications. This paper focuses on their use as a tool for transient extraction. From the Discrete Wavelet Transform (DWT), specific coefficients are picked using a coherence-based criterion. These coefficients are then taken back to the time domain as the extracted transient. If the extracted transient is a response from a measured input, then a frequency response function can be formulated.

A practical approach for evaluating and validating global system designs for Squeak and Rattle performance is proposed. Using simple slip and rattle models, actual sound and vibration data, and the fundamentals of audiological perception, analysis tools adapted from Chaos Theory are used to establish threshold levels of performance and identify system characteristics which are significant contributors to Squeak and Rattle. Focus on system design is maintained by using a simple rattle noise indicator and relating rattle events to levels of dynamic motion (acceleration, velocity, etc.). The threshold level is defined as the level of acceleration at which the system moves from a non-rattling state to a rattling state. The approach is demonstrated with a simple analytical model applied to an experimental structure under dynamic load.

Noise Path Analysis techniques (NPA) have been developed and refined by the automotive industry for structure-borne noise and vibration evaluation of their products. Off-highway vehicles, particularly those with enclosed cabs, are excellent candidates for the application of these techniques. Like automobiles, many off-highway machines are typically driven by a rotating power source, have a well-defined acoustic receiver space, and use some form of isolation between source and receiver sub-systems. These structural characteristics make NPA a useful tool for identifying dominant sources and energy transfer paths. The objectives of this paper are to revisit the fundamental theory of matrix inversion as it applies to NPA techniques, and to address the common setup and measurement issues encountered when acquiring noise path data on off-highway machines. A general overview of the procedures involved in applying NPA to an off-highway machine will be presented.

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.

To address the need of increasing fuel economy requirements, automotive Original Equipment Manufacturers (OEMs) are increasing the number of turbocharged engines in their powertrain line-ups. The turbine-driven technology uses a forced induction device, which increases engine performance by increasing the density of the air charge being drawn into the cylinder. Denser air allows more fuel to be introduced into the combustion chamber, thus increasing engine performance. During the inlet air compression process, the air is heated to temperatures that can result in pre-ignition resulting and reduced engine functionality. The introduction of the charge air cooler (CAC) is therefore, necessary to extract heat created during the compression process. The present research describes the physics and develops the optimized simulation method that defines the process and gives insight into the development of CACs.

The study of spray-wall interaction is of great importance to understand the dynamics during fuel-surface impingement process in modern internal combustion engines. The identification of droplet post-impingement pattern (contact, transition, non-contact) and droplet characteristics can quantitatively provide an estimation of energy transfer for spray-wall interaction, thus further influencing air-fuel mixing and emissions under combusting conditions. Theoretical criteria of single droplet post-impingement pattern on a dry wall have been experimentally and numerically studied by many researchers to quantify the hydrodynamic droplet behaviors. However, apart from model fidelity, another issue is the scalability. A theoretical criterion developed from one case might not be well suited to another scenario. In this paper, a data-driven approach for single droplet-dry wall post-impingement pattern utilizing arithmetical machine learning classification methods is proposed and demonstrated.

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.

Sound intensity measurement techniques that used a two-microphone configuration, were first developed in the late 1970s. Originally, the focus was on improving precision during testing or post-processing. However, with the advent of modern, sophisticated equipment, the focus has shifted to the apparatus. Availability of phase-matched microphones has made post-test correction obsolete as the microphones eliminate a majority of the errors before the data is even collected. This accuracy, however, comes at a cost, as phase-matched microphones are highly priced. This paper discusses employing the method of improving post-processing precision, using inexpensive, current equipment. The phase error of the system is corrected using a simple calibration technique and a handheld phase calibrator that is similar to the one used for amplitude calibration of microphones.

Carbon Nanotube (CNT) thin film speakers produce sound with the thermoacoustic effect. Alternating current passes through the low heat capacity CNT thin film changing the surface temperature rapidly. CNT thin film does not vibrate; instead it heats and cools the air adjacent to the film, creating sound pressure waves. These speakers are inexpensive, transparent, stretchable, flexible, magnet-free, and lightweight. Because of their novelty, developing a model and better understanding the performance of CNT speakers is useful in technology development in applications that require ultra-lightweight sub-systems. The automotive industry is a prime example of where these speakers can be enabling technology for innovative new component design. Developing a multi-physics (Electrical-Thermal-Acoustical) FEA model, for planar CNT speakers is studied in this paper. The temperature variation on the CNT thin film is obtained by applying alternating electrical current to the CNT film.

The AutoDrive Challenge competition sponsored by General Motors and SAE gives undergraduate and graduate students an opportunity to get hands-on experience with autonomous vehicle technology and development as they work towards their degree. Michigan Technological University has participated in the AutoDrive Challenge since its inception in 2017 with students participating through MTU’s Robotic System Enterprise. The MathWorks Simulation Challenge has been a component of the competition since its second year, tasking students with the development of perception, control and testing algorithms using MathWorks software products. This paper presents the pedagogical approach graduate student mentors used to enable students to build their understanding of autonomous vehicle concepts using familiar tools. This approach gives undergraduate students a productive experience with these systems that they may not have encountered in coursework within their academic program.