电动汽车用高功率电机控制器设计与验证∗

针对电动汽车控制器高功率密度的要求,开发了一款高功率电机控制器.阐述了该控制器的结构设计方案和电气原理,并对硬件和软件的设计方案进行了详细介绍,提出了基于单面散热IGBT模块的高功率控制器设计方案,并针对该高功率控制器的散热效果进行了仿真研究.最后,对高功率电机控制器进行了台架试验,试验结果表明,所设计的高功率电机控制器具有良好的控制器性能和更高的功率密度.     

Correction to: Bismuth Yttrium Oxide (Bi3YO6), A New Electrode Material For Asymmetric Aqueous Supercapacitors

Journal of Inorganic and Organometallic Polymers and Materials - The original version of this article unfortunately contained mistakes. In line 9 of the abstract, 5% should read as 2%. The...     

Accu Roll轧管机的背景、现状及前景

对Accu Roll轧管机的产生背景进行了回顾,对目前国内Accu Roll轧管机的使用现状进行了分析,在肯定其优点的同时,指出了该类轧管机存在的共同问题,提出了完善轧管机性能的可能途径及选择轧管机应注意的问题。     

PZT／Terfenol-D／PVDF层状复合磁电材料谐振特性

采用热压法制备出二层锆钛酸铅(PZT)／聚偏氟乙烯(PVDF)与1层Tb0.28Dy0.72Fe2(Terfenol-D)／PVDF叠层结构的三元复合磁电材料，研究了不同PVDF含量，以及不同层厚比tp／L对样品的介电常数、介电损耗、电阻率、谐振频率以及磁电转换系数αE33，αE31的影响规律，结果显示PVDF的含量和层厚比都存在最佳值(最佳值出现在产0．5，tp／L=2／7)，并且在这个最佳值处，磁电转换系数达到最大。     

双包络TI-环面蜗杆传动的二次包络分析

在一次包络分析的基础上,着重进行了二次包络齿面接触分析,推导出了蜗杆和蜗轮齿面方程。齿面接触分析表明：齿面呈双线接触,润滑条件好,承载能力大,在重型机械传动装置中具有实用价值。     

大液相负荷下斜孔塔板的流体力学性能

针对大液相负荷气液传质操作 ,通过冷模实验 ,重新确定了普通斜孔塔板的液体力学性能 ,并给出了新的关联式。同时基于普通正排斜孔塔板在大液量操作条件下压降大 ,泄漏和雾沫夹带严重等缺点 ,沿用梯形导向浮阀的思想 ,提出了变正排为斜排的改进方案 ,并在相同条件下对两者的液体力学性能进行初步比较。证明了斜排斜孔塔板是一种适合大液体处理量且操作弹性较宽的塔板     

内陆核电厂放射性废液中硼酸的反渗透分离实验研究

建设内陆核电是我国经济社会发展的必然需求,但由于内陆核电自然环境和社会环境的特殊性,必须更进一步考虑排放对环境和公众的安全影响,对放射性废液进行深化处理,在解控排放的基础上进一步降低排放水平。本文在内陆AP1000机组已实施的放射性废液处理系统改进的基础上,开展了放射性废液深化处理研究,通过大量实验考察了不同进水pH值、硼浓度、含盐量、水温等水质条件和不同工作压力、回收率等运行条件下反渗透装置对硼酸的去除性能和对模拟放射性核素的截留能力。结果表明,通过控制适当的工艺条件,可以去除废液中80%以上的硼酸,同时保持很好的核素去除效果,达到进一步降低排放水平的目的。研究成果可为内陆核电厂放射性废液处理系统深化处理工程应用提供有力的技术支撑,并为后续内陆核电放射性废液深化处理提供参考。     

非晶态NiB配位催化2-亚丁基环己酮的选择加氢动力学研究

以超细非晶态NiB为催化剂、乙醇为溶剂 ,研究了常压条件下 2 -亚丁基环己酮的选择催化氢化反应。确定了反应对 2 -亚丁基环己酮的反应级数n =1,80℃下准一级反应的速率常数为k =3.4× 10 -3 min-1。同时考察了氢化过程中外扩散的影响以及温度、催化剂用量对反应的影响。求得反应的活化能Ea =16 .391kJ/mol。     

Backstepping control for output-constrained nonlinear systems based on nonlinear mapping

In this paper, nonlinear mapping (NM)-based backstepping control design is presented for a class of strict-feedback nonlinear systems with output constraint. By mapping output value set onto the set of all real numbers, the constrained system is transformed into a new strict-feedback unconstrained system to employ the traditional backstepping control while simultaneously preventing the constraint from being violated. It is proved that the original system has the similar convergence and bounded properties with the new one. Besides the nominal case where full knowledge of the plant is available, we also tackle scenarios wherein parametric uncertainties are present. Furthermore, the comparison with barrier Lyapunov function-based algorithm reveals the advantages of NM algorithm. The closed-loop system is guaranteed to be stable in the sense that all signals involved remain bounded, and the tracking error converges to zero asymptotically. Simulation studies illustrate the performance of the proposed control.     

Two-dimensional bilinear preserving projections for image feature extraction and classification

Two-dimensional locality preserving projections (2DLPP) was recently proposed to extract features directly from image matrices based on locality preserving criterion. A significant drawback of 2DLPP is that it only works on one direction (left or right) to reduce the dimensionality of the image matrices and thus too many coefficients are needed for image representation in low-dimensional subspace. In this paper, we propose a novel method called two-dimensional bilinear preserving projections (2DBPP) for image feature extraction. We generalized the image-based (2D-based) feature extraction techniques into bilinear cases, in which 2DLPP is a special case of our proposed method. In order to obtain the bilinear projections, we proposed an iteration method by solving the corresponding generalized eigen-equations. Moreover, analyses show that 2DBPP has stronger locality preserving abilities than 2DLPP. By using the label information and defining different local neighborhood graphs, the proposed framework is further extended to supervised case. Experiments on three databases show that 2DBPP and its supervised extension are superior to some other image-based state-of-the-art techniques.