CALCE EPSC Graduate Student Theses and Dissertation Abstracts (2019)

Bakhshi, Roozbeh (Ph.D.)
Maximizing the Financial Returns of Using Lidar Systems in Wind Farms for Yaw Error Correction Applications

Wind energy is an important source of renewable energy with significant untapped potential around the world. However, the cost of wind energy production is high and efforts to lower the cost of energy generation will help enable more widespread use of wind energy. Ideally, wind turbines have to be aligned with wind flow at all times. However, this is not the case and there exists and angle between a wind turbine nacelle’s central axis and the wind flow. This angle is called yaw error. Yaw error lowers the efficiency of turbines as well as lowers the reliability of key components in turbines. LIDAR devices can correct the yaw error; however, they are expensive and there is a trade-off between their costs and benefits. In this dissertation, a stochastic discrete-event simulation is developed that models the operation of a wind farm. By maximizing the Net Present Value (NPV) changes associated with using LIDAR devices in a wind farm, the optimum number of LIDAR devices and their associated turbine stay time will be determined. These optimum values are a function of number of turbines in the wind farm for specific turbine sizes. The outcome of this dissertation will help wind farm owners and operators to make informed decisions about purchasing LIDAR devices for their wind farms.

Hendricks, Christopher (Ph.D.)
Failure mechanicms in overdischarged and overcharged lithium-ion batteries

Lithium-ion batteries are employed in applications as varied as consumer electronics, electric vehicles, satellites, and airplanes. As lithium-ion battery systems are increasingly scaled to large systems, safety and reliability are paramount. Catastrophic failure of a lithium-ion battery can cause damage to the host system and pose a risk to human life. While many lithium-ion batteries degrade in a benign fashion, others can enter into thermal runaway, generate gas within the battery, and catch fire and/or spontaneously disassemble. Determining precursors to catastrophic failure will allow for early failure mitigation strategies that can reduce the effects of a thermal runaway or prevent it from occurring in the first place. This research will identify several critical factors affecting performance and safety in lithium-ion batteries that are exposed to overdischarge or overcharge abuse. Lithium-ion batteries that are operated outside of their intended voltage range can experience both performance and safety degradation. Operation at voltages below the battery manufacturer’s recommended lower voltage limit results in overdischarge. Overdischarge of lithium-ion batteries can lead to copper dissolution, and the use of X-ray photoelectron spectroscopy (XPS) and X-ray absorption fine structure (XAFS) analysis combines surface- and bulk-level analysis to characterize the risk of short circuit due to copper dissolution and re-precipitation. Operation at voltages above the battery manufacturer’s recommended upper voltage limit results in overcharge. Overcharge initiates exothermic reactions within the battery that can lead to thermal runaway. Furthermore, gas is generated during these side reactions, causing pressure buildup within lithium-ion cells as they undergo abuse. Pressure evolution is measured and a model developed to explain the relationship between state of charge, temperature, and internal cell pressure.

Jameson, N. Jordan (Ph.D.)
Analysis and Impedance-based Detection of Electromagnetic Coil Insulation Degradation

Electromagnetic induction coils are widely used in a variety of applications, such as motors, solenoid valves, and relays. Many of these applications are safety-critical. Failure of the insulation that protects the windings in electromagnetic coils is a significant cause of coil failure and can have severe implications for system reliability. An effective insulation health monitoring program can reduce maintenance and replacement costs, predict the useful lifetime of the coil, and improve the operational availability of the system in which the coil is used. Impedance monitoring of coils has emerged as a promising approach for non-invasive, in-situ insulation health assessments of electromagnetic coils. Yet, little was understood about the relationship between coil impedance and traditional insulation health metrics, such as insulation capacitance and insulation resistance. Furthermore, relating the impedance measurements to chemical and mechanical characteristics of the insulation material is important to understanding the relationship between impedance measurements and the state of the insulation at failure. This study describes the development an improved method of electromagnetic coil insulation health monitoring and shows the uncovered relationships between coil impedance and the insulation electrical, chemical, and mechanical properties.

Li, Nga ManJennifa (Ph.D.)
Effects of Ferroelectric Properties on Mechanical Behavior of Class II Multilayer Ceramic Capacitors

Class II Multilayer Ceramic Capacitors (MLCCs) are one of the most widely adopted types of passive components in modern electronic systems due to their high volumetric efficiency. Mechanical failures are dominant in MLCCs due to the brittle nature of the ceramic dielectric. Over the years, there have been many studies on the effect of design parameters, assembly parameters on crack susceptibility of these parts. Barium Titanate (BaTiO3) based ceramic is used as the dielectric in Class II MLCCs. This material is responsible for capacitance aging and temperature dependent properties in these units. Changes in mechanical properties due to electrical and mechanical loading or loading history is widely reported in the literature for bulk BaTiO3 and other ferroelectric materials. However, these effects have yet to be reported for Class II MLCCs components in the literature. With the indentation technique becoming more popular in research and development, more studies have adopted the technique for assessing mechanical properties of MLCCs and other electronic components. However, indentation measured properties are dependent on test parameters. In the case of ferroelectric materials, the properties also depend on texture of the specimen and other electromechanical coupling effects. In this study, baseline measurements of mechanical properties under various test parameters as well as treatment history of MLCCs are established using the Oliver-Pharr method. Two mechanisms are evaluated for the potential change in flexural strength for MLCCs with DC voltage history. The first one is the fracture toughness anisotropy caused by domain switching. The second one is the change in stress distribution in the MLCC body with the increase in effective dielectric texture (crystallinity) due to poling under a bending load. Finally, flexural strength is measured for commercial MLCCs with different volumetric ratio of effective dielectric, and an empirical relationship is developed to relate the change in flexural strength to the applied poling voltage and the volumetric ratio of the tested units.

Manoharan, Subramani (Ph.D.)
Interfacial Degradation of Copper Wire Bonds in Thermal Aging and Cycling Condition

Lu, Yizhou (Ph.D.)
Prognostic Modeling for Reliablity Predictions of Power Electronic Devices

The applications of semiconductor power electronic devices, including power and RF devices, in industry have stringent requirements on their reliability. Power devices are subject to various types of failure mechanisms under various stressors. Prognostics and health management (PHM) allows detecting signs of failures, providing warnings of failures in advance, and performing condition-based maintenance. There is a pressing need to develop a robust prognostic model to detect anomalous behavior and predict the lifetime of devices that can be applicable to different types of power transistors. In the present dissertation, a comprehensive prognostic model for remaining useful life (RUL) prediction of semiconductor power electronic devices is developed. The model consists of an anomaly detection module and a RUL prediction module including a non-linear system process model describing the evolution of parametric degradation, and a measurement model. The anomaly detection module uses principal component analysis (PCA) for dimensionality reduction and feature extraction, as well as k-means clustering to establish baseline clusters in the feature space. The novel singular-value-weighted distance (SVWD) is developed as the distance measure in the feature space, based on which Fisher criterion (FC) is used for anomaly probability calculation. The system process model incorporates variables concerning loading conditions and physics-of-failure of devices, and uses particle filter (PF) approach for process model training and RUL prediction. For PF methodology, a novel resampling technique, called MHA-replacement resampling, is developed to solve the particle degeneracy in classic PF techniques and sample impoverishment in traditional resampling techniques. The developed prognostic model is first implemented on IGBT modules for validation. It was reported that the module package of power transistors was susceptible to various types of fatigue-related failure modes due to coefficient of thermal expansion (CTE) mismatches under temperature/power cycles introducing thermomechanical stresses. The physics-of-failure "driving variable" is derived from Paris equation. The model is validated on several time-series IGBT module degradation data under power cycles from literature sources, based on SIR particle filter for RUL prediction with good accuracy. Then the model is implemented on GaN HEMTs, a representative of wide-bandgap semiconductor power devices. GaN HEMTs are susceptible to degradation mechanisms such as ohmic contact inter-diffusion that leads to voiding in the field plate at high temperature under RF accelerated life tests (ALTs). The time-series data of the physics-of-failure "driving variable" is obtained from diffusion computation in Mathematica with the temperature prole coming from COMSOL thermal simulation. The RUL prediction results based on SIR lter are also satisfactory for GaN HEMTs. For each type of device, the new resampling technique is validated through performance benchmarking against state-of-the-art resampling techniques. Another reliability threat for GaN HEMTs, especially in aerospace and nuclear applications, is the degradation due to radiation effect on the device performance. Gamma radiation has been found to lead to generation of defects in AlGaN/GaN layers, which form complexes acting as carrier traps, thus reducing carrier density and current. EPC GaN HEMTs are irradiated under a wide range of Gamma ray doses and critical DC characteristics are recorded before and after radiation to quantify their shifts during the irradiation. Future work needed to allow implementation of the developed prognostic model for RUL estimation is proposed.

Huang, Hao (Ph.D.)
Mechanical Characterization of Pressure-sensitive (PSA) Bonded Assembly

This study focuses on comprehensive empirical and mechanistic understanding of the mechanical behavior of adhesive joints bonded with pressure sensitive adhesives (PSAs). PSAs are capable of very large deformation. The stress-strain and creep behavior of such joints are complex due to constant competition between cavitation dynamics in the bulk and at interfaces; and fibrillation and nonlinear visco-plastic behavior of the PSA material. The behavior is further altered by the presence of flexible or semi-rigid carrier layers because they alter the stress field within the joint and also provide additional interfaces for sequential cavity nucleation and growth. These mechanisms are known to result in multiple phases and transitions in their stress-strain and creep curves. The number of transitions depends on the presence (or absence) of carrier layers and the severity of the secondary transitions depends on the flexural compliance of the carrier layers). The effective mechanical response of the PSA joint is therefore affected by this complex set of events during slow deformation process, including the final stage when the PSA starts to debond from the substrate and/or carrier layer. This morphological evolution of the PSA depends on the adhesive material properties, joint configuration (joint aspect ratio and presence/absence of carrier layers), bonding substrate surface properties (surface energy, roughness and presence of contaminants), carrier layer properties (surface energy, surface roughness and flexural rigidity) and loading conditions (loading rate, stress level and temperature). This study consists of experimentation and mechanistic modeling. In the experimental study, bonded PSA test specimens were fabricated for selected PSA/substrate combinations, after detailed parametric study to gain insights into the influences of the lamination conditions (bonding pressure, bonding time, bonding pressure, post-cure and aging protocols). The joint performance parameters of interest for this parametric study include (i) tensile strength, ductility and creep resistance; (ii) peak stress and peak strain; and (iii) number of transitions and severity of transitions. These specimens were subjected to mechanical tests on a dynamic mechanical analyzer (DMA) to measure stress-strain response and creep response for different loading conditions. In the modeling phase, mechanistic models are developed to provide fundamental insights about the dominant deformation mechanisms in PSA bonded assemblies This has the added advantage of reducing the enormous amount of physical testing that engineers would need to conduct to empirically characterize every PSA-substrate combination of interest over all the loading conditions of interest The predictive mechanistic model is based on enhancement of a simple ‘block’ model that has been proposed in the literature for simulating the stress-strain and creep behavior of the PSA/substrate at different loading conditions. This model acts as a virtual test, predicting the mechanical response of a PSA bonded assembly by explicitly accounting for the PSAs’ nonlinear visco-plastic material properties, cavity dynamics in the bulk and at the interfaces, fibrillation dynamics, and other system configurations such as bonding substrate surface properties and carrier layer properties. This model is shown to be able to predict the stress-strain and creep behavior of PSA bonded assemblies under a broad range of operating conditions, after proper calibration by a few corner cases of physical tests. The predictive model can become a virtual testing method that for real-time prognostic health management (PHM) for PSA bonded assemblies. Test equipment includes a commercially available Dynamic Mechanical Analysis (DMA), to conduct the constant speed stress-strain test and constant force uniaxial creep test on the sample of selected PSA bonded assemblies at selected loading conditions. An observation fixture is also designed for studying the morphological evolution of PSA layer by video recording the cavitation and debonding at the PSA-substrate interface during tensile deformation of a PSA bonded assembly. Complexity in the study includes: (i) structural change of PSA system due to cavitation and fibrillation; (ii) sequential cavitation and fibrillation due to additional interface introduced by carrier layer; (iii) joint parameter (material, configuration, surface roughness and surface energy); (iv) nonlinear rate-dependent plastic material properties of bulk PSA; and (v) implementation of new material model into commercial FEA tools.