New Polymerized Small Molecular Acceptors with Non-Aromatic π-Conjugated Linkers for Efficient All-Polymer Solar Cells

Developing new polymerized small molecular acceptor (PSMA) is pivotal for improving the performance of all-polymer solar cells. On the basis of this newly developed CH-series small molecule acceptors, two PSMAs are reported herein (namely PZC16 and PZC17, respectively). To reduce the molecular torsion caused by the traditional aromatic π-bridges, non-aromatic conjugated units (ethynyl for PZC16 and vinylene for PZC17) are adopted as the linkers and their effect on the photo-physical properties as well as the device performance are systematically investigated. Both polymer acceptors exhibit co-planar molecular conformation, along with broad absorption ranges and suitable energy levels. In comparison with the PM6:PZC16 film, the PM6:PZC17 film exhibits more uniform phase separation in morphology with a distinct bi-continuous network and better crystallinity. The PM6:PZC17-binary-based devices exhibit a satisfactory PCE of 16.33%, significantly higher than 9.22% of the PZC16-based devices. Impressively, PM6:PZC17-based large area device (ca. 1 cm²) achieves an excellent PCE of 15.14%, which is among the top performance for reported all-polymer solar cells (all-PSCs).     

基于 SVD-VMD 和 SVM 滚动轴承故障诊断方法

针对故障滚动轴承振动信号中含有干扰信号,难以准确提取出故障信息,提出了一种基于奇异值分解(SVD)、变分模态分解(VMD)、和支持向量机(SVM)的滚动轴承故障诊断方法。首先利用奇异值分解对信号进行处理,根据奇异值峰度差分谱来确定分解后重构矩阵的有效阶数,然后根据该有效阶数重构信号,对重构后的信号进行VMD分解,根据上述有效阶数确定分解的本征模态函数(IMF)分量的个数,从分解后的IMF分量中提取故障特征参数,将其作为支持向量机的输入参数进行故障诊断。最后采用合肥工业大学轴承试验机进行验证,并与直接进VMD分解及基于带通滤波器信号去噪的故障诊断方法进行对比,结果表明该方法能有效识别滚动轴承的故障类型,可用于滚动轴承故障诊断。     

面向低频振荡分析的直驱风电机组阻尼转矩建模

针对直驱风电机组直流电压环和锁相环失稳问题,基于直驱风电机组电流源型线性化模型,分析了电网强度、直流电容输入功率以及控制参数对直驱风电机组稳定性的影响;建立了适用于直流电压环和锁相环稳定性分析的电流源型阻尼转矩模型,通过阻尼转矩法揭示了直驱风电机组失稳机理;进一步地将阻尼转矩法拓展至多机并联系统。研究结果表明：电网强度的减小、直流电容输入功率的增加、控制参数(直流电压环比例参数、锁相环比例参数)的减小会降低直驱风电机组低频振荡模式(直流电压环模式、锁相环模式)的阻尼系数,当阻尼系数小于0时,该模式下系统失稳,表现为直驱风电机组发生低频振荡。     

Personalized Convolution for Face Recognition

International Journal of Computer Vision - Face recognition has been significantly advanced by deep learning based methods. In all face recognition methods based on convolutional neural network...     

Infrared target tracking based on proximal robust principal component analysis method

Applied Intelligence - Infrared target tracking plays an important role in both civil and military fields. The main challenges in designing a robust and high-precision tracker for infrared...     

世界主要国家工程科技重大计划与前沿问题综述

本文梳理了近年来世界各主要国家工程科技领域的重大战略计划和措施,简要分析了当前工程科技主要领域发展状况、水平,对主要国家工程科技领域计划的目标、路径与内容进行了比较分析,描绘了工程科技计划关系图、聚焦点和前沿问题。     

安时-卡尔曼交叉运行的电池荷电状态估算策略及其微控制器在环验证

为了提高电池管理系统(BMS)的性能,研究了电池荷电状态(SOC)的估算方法,并根据SOC估算算法精度和系统实时性要求,提出了安时(AH)积分算法-卡尔曼(Kalman)算法(AH-Kalman)交叉运行的SOC估算策略。该策略用开路电压(OCV)法确定SOC初值,以实时性较强的AH积分法为主,采用间歇运行的Kalman滤波法修正安时计量法积分误差。建立了系统仿真模型,验证了卡尔曼滤波算法对安时积分法积累误差的修正作用。将控制算法生成C代码下载到目标控制器,搭建微控制器在环测试验证(PILS)平台,进行了与传统卡尔曼滤波算法的复杂度对比分析。结果表明,所提出AHKalman交叉运行的SOC估算策略在保证了SOC估算精度的同时也具有较好的实时性,便于实际应用。