Surface Insulation Resistance Degradation and Electrochemical Migration on Printed Circuit Boards

Widespread adoption of lead-free materials and processing for printed circuit board (PCB) assembly has raised reliability concerns regarding surface insulation resistance (SIR) degradation and electrochemical migration (ECM). As PCB conductor spacings decrease, electronic products become more susceptible to these failures mechanisms, especially in the presence of surface contamination and flux residues which might remain after no-clean processing. Moreover, the probability of failure due to SIR degradation and ECM is affected by the interaction between physical factors (such as temperature, relative humidity, electric field) and chemical factors (such as solder alloy, substrate material, no-clean processing). Current industry standards for assessing SIR reliability are designed to serve as short-term qualification tests, typically lasting 72 to 168 hours, and do not provide a prediction of reliability in long-term applications. The risk of electrochemical migration with lead-free assemblies has not been adequately investigated. Furthermore, the mechanism of electrochemical migration is not completely understood. For example, the role of path formation has not been discussed in previous studies. Another issue is that there are very few studies on development of rapid assessment methodologies for characterizing materials such as solder flux with respect to their potential for promoting ECM. In this dissertation, the following research accomplishments are described: 1). Long-term temp-humidity-bias (THB) testing over 8,000 hours assessing the reliability of printed circuit boards processed with a variety of lead-free solder pastes, solder pad finishes, and substrates. 2). Identification of silver migration from Sn3.5Ag and Sn3.0Ag0.5Cu lead-free solder, which is a completely new finding compared with previous research. 3). Established the role of path formation as a step in the ECM process, and provided clarification of the sequence of individual steps in the mechanism of ECM: path formation, electrodeposition, ion transport, electrodeposition, and filament formation. 4). Developed appropriate accelerated testing conditions for assessing the no-clean processed PCBs' susceptibility to ECM: a). Conductor spacings in test structures should be reduced in order to reflect the trend of higher density electronics and the effect of path formation, independent of electric field, on the time-to-failure. b). THB testing temperatures should be modified according to the material present on the PCB, since testing at 85oC can cause the evaporation of weak organic acids (WOAs) in the flux residues, leading one to underestimate the risk of ECM. 5). Correlated temp-humidity-bias testing with ion chromatography analysis and potentiostat measurement to develop an efficient and effective assessment methodology to characterize the effect of no-clean processing on ECM.

Energy Management of a Battery-Ultracapacitor Hybrid Energy Storage System in Electric Vehicles

Electric vehicle (EV) batteries tend to have accelerated degradation due to high peak power and harsh charging/discharging cycles during acceleration and deceleration periods, particularly in urban driving conditions. An oversized energy storage system (ESS) can meet the high power demands; however, it suffers from increased size, volume and cost. In order to reduce the overall ESS size and extend battery cycle life, a battery-ultracapacitor (UC) hybrid energy storage system (HESS) has been considered as an alternative solution. In this work, we investigate the optimized configuration, design, and energy management of a battery-UC HESS. One of the major challenges in a HESS is to design an energy management controller for real-time implementation that can yield good power split performance. We present the methodologies and solutions to this problem in a battery-UC HESS with a DC-DC converter interfacing with the UC and the battery. In particular, a multi-objective optimization problem is formulated to optimize the power split in order to prolong the battery lifetime and to reduce the HESS power losses. This optimization problem is numerically solved for standard drive cycle datasets using Dynamic Programming (DP). Trained using the DP optimal results, an effective real-time implementation of the optimal power split is realized based on Neural Network (NN). This proposed online energy management controller is applied to a midsize EV model with a 360V/34kWh battery pack and a 270V/203Wh UC pack. The proposed online energy management controller effectively splits the load demand with high power efficiency and also effectively reduces the battery peak current. More importantly, a 38V-385Wh battery and a 16V-2.06Wh UC HESS hardware prototype and a real-time experiment platform has been developed. The real-time experiment results have successfully validated the real-time implementation feasibility and effectiveness of the real-time controller design for the battery-UC HESS. A battery State-of-Health (SoH) estimation model is developed as a performance metric to evaluate the battery cycle life extension effect. It is estimated that the proposed online energy management controller can extend the battery cycle life by over 60%.

Texture-Detail Preservation Measurement in Camera Phones: An Updated Approach

Recent advances in mobile phone cameras have poised them to take over compact hand-held cameras as the consumer’s preferred camera option. Along with advances in the number of pixels, motion blur removal, face-tracking, and noise reduction algorithms have significant roles in the internal processing of the devices. An undesired effect of severe noise reduction is the loss of texture (i.e. low-contrast fine details) of the original scene. Current established methods for resolution measurement fail to accurately portray the texture loss incurred in a camera system. The development of an accurate objective method to identify the texture preservation or texture reproduction capability of a camera device is important in this regard. The ‘Dead Leaves’ target has been used extensively as a method to measure the modulation transfer function (MTF) of cameras that employ highly non-linear noise-reduction methods. This stochastic model consists of a series of overlapping circles with radii r distributed as r−3, and having uniformly distributed gray level, which gives an accurate model of occlusion in a natural setting and hence mimics a natural scene. This target can be used to model the texture transfer through a camera system when a natural scene is captured. In the first part of our study we identify various factors that affect the MTF measured using the ‘Dead Leaves’ chart. These include variations in illumination, distance, exposure time and ISO sensitivity among others. We discuss the main differences of this method with the existing resolution measurement techniques and identify the advantages. In the second part of this study, we propose an improvement to the current texture MTF measurement algorithm. High frequency residual noise in the processed image contains the same frequency content as fine texture detail, and is sometimes reported as such, thereby leading to inaccurate results. A wavelet thresholding based denoising technique is utilized for modeling the noise present in the final captured image. This updated noise model is then used for calculating an accurate texture MTF. We present comparative results for both algorithms under various image capture conditions.