Global ETD Search

51	Model-Based Approach for Resilient Vehicle Operation Shveta Dhamankar (16709415) 31 July 2023 (has links) <p>The vehicle industry has an endless appetite to get better. Often, this appetite is justified by the need of the hour. In the agricultural space, this translates to improving agricultural productivity in the face of population growth, reduced arable land and shortage of skilled farm labor. As for torsional vibrations, which have been around ever since the wheel was invented, the problem gets redefined with new regulations demanding new powertrains with improved fuel efficiency and reduced emissions.</p><p>A solution to the agriculture problem, involves efficiently automating the harvesting process.The first section of this thesis covers the ‘Auto-Unload’ where the goal of automation is achieved. This was done by building a simulation framework that was used to develop and synthesize the ‘AutoUnload’ controller. This controller was later deployed on a combine and a successful unloading on-the-go was demonstrated with a combine, tractor, and tractor-driven grain cart.</p><p>The solution to the second problem about drivetrain vibrations involved deriving a mathematical model for simulating the powertrain of a medium-duty truck. This was done to confirm resonance seen during testing done on a chassis dynamometer. The consequent control strategy to mitigate undesired vibration was to move the torque excitation away from the natural frequency of the system. This was achieved by a ‘gear-shifting’ algorithm. Comparison between on-road tests with and without the ‘gear-shifting’ algorithm showed that such a control strategy can effectively eliminate resonance. The solution methodology developed in this work is robust and transferable to higher engine torques and harvest speeds.</p> Automation engineering Control engineering Field robotics Agricultural engineering Agriculture Automation Robotics NVH Powertrain Drivetrain Driveline Transmission Modelling and Controls Feedback control systems Torsional Vibration Natural Frequency Resonance Harvesting
52	Estimation of Blocked Forces in an Assembly with Rear Drive Unit as a Source Bala, Srujeeth Khanna January 2021 (has links) Experimental validations are widely used for studying dynamic structural behaviors and these studies involve defining the structures completely as being used in real time. While in numerical simulations such detailed features are not specified to ease the computation, thereby deviating from accurate results. Hence experimental validations are more desired in product developments process. Applications of experimental verification for noise and vibration (referred to as NVH inautomotive industry) are expanding over the last few decades. Researchers are exploring ways to predict the responses on the new receiver using receiver independent forces, which led to evolution of component based TPA (Transfer Path Analysis) concept. The Component based TPA concept is an important development in automotive industry. It allows the auto manufacturers to make use of their available subsystems (like motor or a gearbox) in their newly developing vehicles. This has been made possible by defining the dynamic forces exerted by the source independent of receiving structure, which are then used to predict the responses on the new receiver. Evaluation of such receiver independent forces allows measurements to be made in a test rig rather than in the vehicle. This indeed helps in better communication between different departments or between suppliers and vehicle manufacturers, saves design iterations and time, and would help vehicle manufactures to predict the vehicle structural behaviors much before the first prototype is made. The method is based on the international standard ISO 20270:2019 (en) Acoustics – Characterization of sources of structure-borne sound and vibration – indirect measurement of blocked forces. The thesis is based on evaluating the source characterized forces that are used for predicting responses on a new receiving structure. For this, different methods in TPA are explored and for the rear drive unit application, in-situ method is chosen. The source characterized forces also termed as blocked forces are computed in different test set up and a validation check is performed. The obtained results are also compared with FEM and useful conclusions are drawn. And finally contact forces evaluated by integrating the subsystems are compared to the contact forces derived from the source characterized forces. / Experimentell verifiering av dynamiska krafter och vibrationer som uppkommer i fordon innebär mätning av tids-, frekvens- och/eller varvtalsberoende kvantiteter. Numeriska beräkningar har utvecklats till en hög nivå, men kan ännu inte beskriva alla förlopp och detaljer som förekommer i de verkliga processerna. På grund av detta krävs det fortfarande mätningar som en del av produktionsutvecklingen. Valideringsmetoder för ljud och vibrationer har utvecklats mycket desenaste decennierna, och ett mål har varit att utveckla mätmetoder där de uppmätta krafterna från en komponent som bidrar till buller kan mätas på ett sätt som inte beror på den testrigg eller det fordon den mäts i. Komponentbaserad TPA Transfer Path Analysis är en analysmetod som är viktig inom fordonsindustrin. Den gör det möjligt för en tillverkare att använda modeller av existerande komponenter (t.ex. motorer eller växellådor) i modeller för nya fordon. En grundläggande förutsättning är att de krafter som mäts är oberoende av den mottagande strukturen, det vill säga fordonet. Om krafterna är oberoende av strukturen där de mäts innebär det att komponenten kan mätas i en test rigg på ett annat ställe (till exempel hos en underleverantör) och att tillgång till fordon inte krävs för karaktäriseringen. Det underlättar kommunikationen mellan olika delar av organisationen och mellan underleveratörer och tillverkare och bidrar till att prediktera ljud och vibrationer innan den första prototypen är tillgänglig. Den föreslagna metoden är baserad på den internationella normen ISO 20270:2019 (en) Acoustics – Characterization of sources of structure-borne sound and vibration – indirect measurement of blocked forces. Examensarbetet handlar om att utveckla en mätmetod för att kunna ta fram krafter genererade av komponenter som är oberoende av testriggens egenskaper. De framtagna krafterna kan då användas i en virtuell fordonsmodell för att se ljud och vibrationsbidragen på fordonsnivå. Källan som har studerats är en slutväxel (rear drive unit) för fyrhjulsdrift i bil. Flera olikametoder för TPA har undersöks, och för karaktärisering av slutväxeln har in-situ metoden valts. Krafter som är oberoende av den mottagande strukturen kallas även ‘blocked forces’. Krafterna beräknas baserat på resultaten från flera olika delmätningar. Validering och även jämförelse medFEM beräkningar har gjorts liksom jämförelser mellan mätningar på enbart komponenten och av hela systemet. Component based TPA source characterized forces FEM Contact forces ISO20270:2019 Blocked forces Automotive NVH sound and vibration komponentbaserad TPA karaktärisering av bullerkällor FEM kontaktkrafter blockerade krafter bilindustri ljud och vibrationer ISO20270:2019 Mechanical Engineering Maskinteknik
53	Characterization of Structure-Borne Tire Noise Using Virtual Sensing Nouri, Arash 27 January 2021 (has links) Various improvements which have been made to the vehicle (reduced engine noise, reducedaerodynamic related NVH), have resulted in tire road noise as the dominant source of thevehicle interior noise. Generally, vehicle interior noise has two main sources, 1) travellinglow frequency excitation below 800 Hz from road surface through a structure- borne pathand 2) the high frequency (above 800 Hz) air-borne noise that is caused by air- pumpingnoise caused by tread pattern.The structure-borne waves of the circumference of the tire are generated by excitation atthe contact patch due to the road surface texture and characteristics. These vibrations arethen transferred from the sidewalls of the tire to the rim and then are transmitted throughthe spindle-wheel interface, resulting in high frequency vibration of vehicle body panels andwindows.The focus of this study is to develop several statistical-based models for analyzing the roadsurface and using them to predict the tire-road noise structure-borne component. In order todo this, a new methodology for sensing the road characteristics, such as asperities and roadsurface condition, were developed using virtual sensing and intelligent tire technology. In ad-dition, the spindle forces were used as an indicator to the structure-borne noise of the vehicle.Several data mining and multivariate analysis-based methods were developed to extractfeatures and to develop an empirical model to predict the power of structure-borne noiseunder different operational and road conditions. Finally, multiple data driven models-basedmodels were developed to classify the road types, and conditions and use them for the noisefrequency spectrum prediction. / Doctor of Philosophy / Multiple data driven models were developed in this study to use the vibration of the tirecontact patch as an input to sense some characteristics of road such as asperity, surface type,and the surface condition, and use them to predict the structure-borne noise power. Also,instead of measuring the noise using microphones, forces at wheel spindle were measuredas a metric for the noise power. In other words, a statistical model was developed that bysensing the road, and using the data along with other inputs, one can predict forces at thewheel spindle. NVH Structure-Borne Noise Tire-Pavement Interaction Noise Surface Condition Monitoring Intelligent Tire Statistical Modelling Deep Learning Machine Learning Signal Denoising Pattern Recognition End-to-End Learning Autoencoder Design of th
54	Fault detection of planetary gearboxes in BLDC-motors using vibration and acoustic noise analysis Ahnesjö, Henrik January 2020 (has links) This thesis aims to use vibration and acoustic noise analysis to help a production line of a certain motor type to ensure good quality. Noise from the gearbox is sometimes present and the way it is detected is with a human listening to it. This type of error detection is subjective, and it is possible for human error to be present. Therefore, an automatic test that pass or fail the produced Brush Less Direct Current (BLDC)-motors is wanted. Two measurement setups were used. One was based on an accelerometer which was used for vibration measurements, and the other based on a microphone for acoustic sound measurements. The acquisition and analysis of the measurements were implemented using the data acquisition device, compactDAQ NI 9171, and the graphical programming software, NI LabVIEW. Two methods, i.e., power spectrum analysis and machine learning, were used for the analyzing of vibration and acoustic signals, and identifying faults in the gearbox. The first method based on the Fast Fourier transform (FFT) was used to the recorded sound from the BLDC-motor with the integrated planetary gearbox to identify the peaks of the sound signals. The source of the acoustic sound is from a faulty planet gear, in which a flank of a tooth had an indentation. Which could be measured and analyzed. It sounded like noise, which can be used as the indications of faults in gears. The second method was based on the BLDC-motors vibration characteristics and uses supervised machine learning to separate healthy motors from the faulty ones. Support Vector Machine (SVM) is the suggested machine learning algorithm and 23 different features are used. The best performing model was a Coarse Gaussian SVM, with an overall accuracy of 92.25 % on the validation data. Planetary gearbox Fault detection Condition Monitoring Support Vector Machine (SVM) Machine Learning Supervised Machine Learning Defect Pinion Defect Planet Gear MATLAB LabVIEW Soundproof-box Noise Vibration Harshness (NVH) Gearmesh Frequency (GMF) Power Spectrum BLDC-motor Elektroteknik och elektronik
55	Minimization of Noise and Vibration Related to Driveline Imbalance using Robust Design Processes Al-Shubailat, Omar 17 August 2013 (has links) Variation in vehicle noise, vibration and harshness (NVH) response can be caused by variability in design (e.g. tolerance), material, manufacturing, or other sources of variation. Such variation in the vehicle response causes a higher percentage of produced vehicles to have higher levels (out of specifications) of NVH leading to higher number of warranty claims and loss of customer satisfaction, which are proven costly. Measures must be taken to ensure less warranty claims and higher levels of customer satisfactions. As a result, original equipment manufacturers (OEMs) have implemented design for variation in the design process to secure an acceptable (or within specification) response. The focus here will be on aspects of design variations that should be considered in the design process of drivelines. Variations due to imbalance in rotating components can be unavoidable or costly to control. Some of the major components in the vehicle that are known to have imbalance and traditionally cause NVH issues and concerns include the crankshaft, the drivetrain components (transmission, driveline, half shafts, etc.), and wheels. The purpose is to assess NVH as a result of driveline imbalance variations and develop a tool to help design a more robust system to such variations. program. Java quality engineering quality capability studies manufacturing processes manufacturing engineer design engineer sales profit customer concern warranty objectionable Eigen functions vectors Eigen Eigen values identity Euler differential equations differential transfer case shaft driveline static imbalance dynamic imbalance passenger customer driver inboard ear driver outboard ear steering wheel seat track variation Gamma distribution normal distribution standard deviation average variance mean phasor victor scalar linear system LTI linear time invariant transfer function output input microphone accelerometers tachometer channels order frequency frequency domain time domain convolution Transformation Fourier Transformer Fourier imaginary and real logarithmic decibel sensitivity curves run down run up two wheel drive Four Wheel Drive Nissan Truck OEM Original Equipment Manufacturers Data Acquisitions Channels Simulation Six Sigma variability Design Robust sensitivity Vibration Imbalance Noise Harshness NVH Driveline

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