Browsing by Subject "failure analysis"

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    Design and Analysis of a Composite Monocoque for Structural Performance : a Comprehensive Approach
    (2019-08) Kamble, Meghana P.; Dalir, Hamid; Tovar, Andres; El-Mounayri, Hazim
    Lately numerous studies have been performed to design composite monocoques with high strength and low weight for various student level racing contests. The objective of this paper is to develop an insightful methodology to design and de veloped a light-weight composite monocoque. The monocoque is designed to pass the mandatory static load tests laid down by the International Automobile Feder ation (FIA)Formula 3. These Formula 3 tests are considered the baseline of the desired structural integrity of the composite monocoque. The presented design tech nique emphasises on a monocoque developed for Sports Car Club of America (SCCA) races. The three standard load tests performed on the monocoque are Survival Cell Side test, Fuel Tank test and Side Intrusion test. A sandwich layup of bi-directional woven carbon/epoxy prepreg and aluminium honeycomb is optimized for minimum weight while predicting the unknown properties of layup and ensuring the mono coque doesnt experience failure. The approach intends to achieve minimum weight with high torsional rigidity and is capable of being used for the design and analysis of any kind of formula type composite monocoque.
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    Model-Based Adaptive Fault Diagnosis in Lithium Ion Batteries: A Comparison of Linear and Nonlinear Approaches
    (SAE, 2017) Sidhu, Amardeep; Izadian, Afshin; Anwar, Sohel; Mechanical Engineering, School of Engineering and Technology
    In this paper, multiple-model adaptive estimation techniques have been successfully applied to fault detection and identification in lithium-ion batteries. The diagnostic performance of a battery depends greatly on the modeling technique used in representing the system and the associated faults under investigation. Here, both linear and non-linear battery modeling techniques are evaluated and the effects of battery model and noise estimation on the over-charge and over-discharge fault diagnosis performance are studied. Based on the experimental data obtained under the same fault scenarios for a single cell, the non-linear model based detection method is found to perform much better in accurately detecting the faults in real time when compared to those using linear model based method.