Study of cell voltage uniformity of proton exchange membrane fuel cell stack with an optimized artificial neural network model

The cell voltage uniformity of the proton exchange membrane fuel cell stack, which may consist of tens or hundreds of cells in series, plays a significant role in the stack's lifetime and performance. But it is challenging to predict the multi-cell voltages and the uniformity with a physics-based model due to complex stack geometry and huge computation efforts. In this work, we develop an artificial neural network model to estimate the steady-state cell voltage distributions of a 60 kW 140-cell stack. The optimized and well-trained model can efficiently reproduce the 140-cell voltages at different operating conditions with the error of less than 2 mV. The increased cathode gas pressure improves the cell voltage consistency and stack performance, while the voltage uniformity worsens with ascending load current. The efficient model prediction of cell voltages is beneficial for accurate evaluation of fuel cell performance, health state, and reliability.     

Predicting bond failure after 1.5 ms of bonding,an initial study

We employ a real-time nondestructive contact resistance method to rapidly predict the end state of ultrasonic wire bonds. We classified 64 bonds as either successful (bond attached) or failed (bond unattached) with a support vector machine method. This method predicts with 92% accuracy, 92% sensitivity, and 92% specificity as early as 1.5 ms into the ultrasonic processing whether the final bond will be attached. The importance of detecting a tentative failure (on the single bond level) at an early stage is that corrective action can be taken to maximize the yield.     

Phonon-limited electron mobility in III-nitride heterojunctions

Low-field electron mobility limited by phonons in GaN-, InN- and AlN-based heterojunctions (HJs) for temperatures T < 300 K is studied within the framework of Boltzmann transport formalism by an iterative method. Electrons are assumed to occupy the lowest subband and scattered by the inelastic polar LO phonons and by quasi-elastic acoustic phonons through the deformation potential and piezoelectric couplings. Numerical calculations of the energy dependence of the first-order perturbation distribution function ϕ(E) for the polar LO phonons and of the acoustic phonon relaxation rates τ^− 1(E) bring out the characteristic features of phonon scattering in nitride HJs. The temperature and concentration dependences of phonon-limited mobility are compared with the low-temperature and high-energy relaxation time approximations, commonly used for ϕ. Calculations, taking into account other relevant scattering mechanisms, obtain good agreement with available Hall mobility data for GaN/AlGaN HJ.     

Global stabilization of high-order nonlinear time-delay systems by state feedback

We consider the problem of global stabilization by state feedback for a class of high-order nonlinear systems with time-delay. By developing a novel dynamic gain-based backstepping approach, a state feedback controller independent of the time-delay is explicitly constructed with the help of appropriate Lyapunov–Krasovskii functionals. The precise knowledge (even the upper bound) of the time-delay is not required. It is proved that the states of the nonlinear time-delay systems can be regulated to the origin while all the closed loop signals are globally bounded. Finally, both physical and academic examples are given to illustrate the applications of the proposed scheme.     

基于FPGA的红外热成像闪光灯激励电源

红外热成像技术是一种快速有效的无损检测技术,广泛应用于航空航天、轨道交通、核工业等领域。激励电源是红外热成像检测系统中的关键设备,其性能将影响缺陷的检测结果。采用线性放大产生激励的方式存在增益带宽积的限制,较难满足红外热成像技术对激励频率范围和输出功率的要求。本文采用数字的方式将电压进行调制,实现了较大功率的输出,提高了对缺陷的检测效率。为满足红外热成像技术对输出功率、参数调整、以及多种工作模式的要求,本文设计了一款基于FPGA的数字化闪光灯激励电源。该电源主要包括低频正弦产生电路、全桥斩波电路和FPGA控制系统三部分,其中控制系统为核心部分。试验证明,该电源实现脉冲和锁相两种激励模式,参数调整方便,能够满足红外热成像技术对激励电源提出的要求。     

Design of moiré-free metal meshes using ray tracing for touch screen panels

Using a ray tracing technique, we investigate the dependence of the moiré effect on the crossing angles between touch screen panels (TSPs) and display panels, the metal grid structures (spacing and width), and metal grid shapes (non-uniform and random grids). Of those design parameters, adjusting the crossing angle (∼45°), reducing the grid width (∼1 μm), and employing a random grid in the shape of irregular hexagon are found to suppress the moiré phenomenon to a great extent. We also provide the simulation scheme that can capture the moiré patterns observed experimentally and useful design guidelines for metal grids.     

Improving the load-following capability of a solid oxide fuel cell system through the use of time delay control

As a new energy technology with distributed generation prospects, the load-following capability of solid oxide fuel cell (SOFC) systems is one of the main obstacles for commercial operation. This paper introduces a time delay control with an observer (TDO) in the fuel supply system to enhance the load-following capability to realize rapid load-following without fuel starvation. A dynamic model reflecting a 5-kW SOFC system with components such as a cell stack, combustor, heat exchanger and gas supply is developed in MATLAB/Simulink to implement time delay control. TDO is improved to TDOF (time delay control with an observer and filter) to avoid the undesirable impact of external disturbances (such as fuel disturbances) on the stability of the SOFC system. The fuel supply system can be driven by the TDOF controller to closely follow the reference trajectory based on the past responses and the input variables of the system during load-following operation. Simulation results reveal that the SOFC system is able to meet the requirement of load-following due to the satisfactory dynamic performance when the TDOF controller is applied in the fuel supply system. The system is appropriate for complicated power environments.     

Comparison of visualization of optimal clustering using self-organizing map and growing hierarchical self-organizing map in cellular manufacturing system

The present research deals with the cell formation problem (CFP) of cellular manufacturing system which is a NP-hard problem thus, the development of optimum machine-part cell formation algorithms has always been the primary attraction in the design of cellular manufacturing system. In this proposed work, the self-organizing map (SOM) approach has been used which is able to project data from a high-dimensional space to a low-dimensional space so it is considered a visualized approach for explaining a complicated CFP data set. However, for a large data set with a high dimensionality, a traditional flat SOM seems difficult to further explain the concepts inside the clusters. We propose one such possible solution for a large CFP data set by using the SOM in a hierarchical manner known as growing hierarchical self-organizing map (GHSOM). In the present work, the two novel contributions using GHSOM are: the choice of optimum architecture through the minimum pattern units extracted at layer 1 for the respective threshold values and selection. Furthermore, the experimental results clearly indicated that the machine-part visual clustering using GHSOM can be successfully applied in identifying a cohesive set of part family that is processed by a machine group. Computational experience specifically with the proposed GHSOM algorithm, on a set of 15 CFP problems from the literature, has shown that it performs remarkably well. The GHSOM algorithm obtained solutions that are at least as good as the ones found the literature. For 75% of the cell formation problems, the GHSOM algorithm improved the goodness of cell formation through GTE performance measure using SOM as well as best one from the literature, in some cases by as much as more than 12.81% (GTE). Thus, comparing the results of the experiment in this paper with the SOM and GHSOM using the paired t-test it has been revealed that the GHSOM approach performed better than the SOM approach so far the group technology efficiency (GTE) measures of performance of the goodness of cell formation is concerned.     

Properties enhancement of SnAgCu solders containing rare earth Yb

In order to enhance the properties of SnAgCu lead-free solders in microelectronic packaging, various contents of rare earth Yb were incorporated into the alloys. Results indicated that the addition of Yb can improve the wettability, tensile strength, thermal fatigue behavior of lead-free alloys. The lead-free solder with 0.05%Yb addition exhibited the best comprehensive properties as compared to the alloys with other Yb weight fractions. And found that after soldering, the initial interfacial IMC thickness of SnAgCuYb solder joint was smaller than that of SnAgCu solder joints, and this signified that the addition of Yb was effective in retarding the growth of the IMC layer. In addition, the Yb can refine the microstructures of SnAgCu solder, excessive Yb added can form bulk Sn–Yb phase and deteriorate the properties.     

A multi-agent architecture for diagnosing simultaneous faults along water canals

Water is intensively used in mankind activities, in particular in agriculture. Water is commonly conveyed for agriculture purposes through water canal networks which are large-scale spatially distributed systems crossing extensive regions. In the presence of leaks, unauthorized water withdrawals, water depth sensor faults or gate faults, the quality of service can be severely compromised. A system able to diagnose which type of fault is present at a given time is of vital importance to access the current state of the water canal and proceed to restore its nominal condition. This paper proposes a multi-agent architecture to simultaneously detect, isolate and estimate lateral outflows (e.g., leaks or water withdrawals) and hardware faults (e.g., a gate obstruction or a downstream water depth sensor fault) in water canal networks. First, the main canal network is broken down into several subsystems composed of a single canal pool with the corresponding gate. Then, an agent is assigned to each subsystem aiming at its fault diagnosis. The approach is based on the generation and evaluation of residuals obtained from the comparison of model-based output signals with real data. Application to an experimental water canal bears out the proposed architecture as a valuable tool for monitoring and supervising general water canals.