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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).

Nowadays quasi-3D approaches are included in many commercial and research 1D numerical codes, in order to increase their simulation accuracy in presence of complex shape 3D volumes, e.g. plenums and silencers. In particular, these are regarded as valuable approaches for application during the design phase of an engine, for their capability of predicting non-planar waves motion and, on the other hand, for their low requirements in terms of computational runtime. However, the generation of a high-quality quasi-3D computational grid is not always straightforward, especially in case of complex elements, and can be a time-consuming operation, making the quasi-3D tool a less attractive option. In this work, a quasi-3D module has been implemented on the basis of the open-source CFD code OpenFOAM and coupled with the 1D code GASDYN.

The present paper investigates possible enhancement of ESP performance associated with the use of smart tires. In particular a novel control logic based on a direct feedback on the longitudinal forces developed by the four tires is considered. The control logic was developed using a simulation tool including a 14 dofs vehicle model and a smart tires emulator. Performance of the control strategy was evaluated in a series of handling maneuvers. The same maneuvers were performed on a HiL test bench interfacing the same vehicle model with a production ESP ECU. Results of the two logics were analyzed and compared.

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.

In the paper some methods are presented, with the corresponding practical examples, related to MonteCarlo (MC) techniques for thermal model/test correlation purposes. The MonteCarlo techniques applied to model correlation are intended to be used as an alternative to empirical ‘manual’ correlation techniques, gradients methods, matrix methods based on least square fit minimization. First of all, Design Of Experiments (DoE) tools are used to determine the model response to uncertain parameters and the confidence level of such a response. A sensitivity map is built, allowing the design of the test to maximize the response of the system to the uncertain parameters. Techniques derived from the extreme statistics are used to extrapolate data beyond test limits, with a sufficient confidence in the queue behaviour.

Wind turbines in cold climates are likely to suffer from icing events, deteriorating the aerodynamic performances of the blades and decreasing their power output. Continuous ice accretion causes an increase in the ice mass and, consequently, in the centrifugal force to which the ice shape is subjected. This can result in the shedding of chunks of ice, which can jeopardize the aeroelastic properties of the blade and, most importantly, the safety of the surrounding people and of the wind turbine structure itself. In this work, ice shedding analysis is performed on a quasi-3D, multi-step ice geometry accreted on the NREL 5MW reference wind turbine. A preliminary investigation is performed by including the presence of an ice protection system to decrease the adhesion surface of the ice on the blade. A reference test case with a simple geometry is used as verification for the correct implementation of the procedure.

This work presents a comprehensive numerical model for ice accretion and Ice Protection System (IPS) simulation over a 2D component, such as an airfoil. The model is based on the Myers model for ice accretion and extended to include the possibility of a heated substratum. Six different icing conditions that can occur during in-flight ice accretion with an Electro-Thermal Ice Protection System (ETIPS) activated are identified. Each condition presents one or more layers with a different water phase. Depending on the heat fluxes, there could be only liquid water, ice, or a combination of both on the substratum. The possible layers are the ice layer on the substratum, the running liquid film over ice or substratum, and the static liquid film between ice and substratum caused by ice melting. The last layer, which is always present, is the substratum. The physical model that describes the evolution of these layers is based on the Stefan problem. For each layer, one heat equation is solved.

In the ANNIE project - Applications of Neural Networks to Integrated Ergonomics - BE96-3433, a tool for integrating ergonomics into the design process is developed. This paper presents some features in the current ANNIE as applied to the design of car interiors. A variant of the ERGOMan mannequin with vision is controlled by a hybrid system for neuro-fuzzy simulation. It is trained by using an Elite system for registration of movements. An example of a trajectory generated by the system is shown. A fuzzy model is used for comfort evaluation. An experiment was performed to test its feasibility and it showed very promising results.

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.

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.

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.