Real time power management strategy for fuel cell hybrid electric bus based on Lyapunov stability theorem

The fuel cell/battery durability and hybrid system stability are major considerations for the power management of fuel cell hybrid electric bus (FCHEB) operating on complicated driving conditions. In this paper, a real time nonlinear adaptive control (NAC) with stability analyze is formulated for power management of FCHEB. Firstly, the mathematical model of hybrid power system is analyzed, which is established for control-oriented design. Furthermore, the NAC-based strategy with quadratic Lyapunov function is set up to guarantee the stability of closed-loop power system, and the power split between fuel cell and battery is controlled with the durability consideration. Finally, two real-time power management strategies, state machine control (SMC) and fuzzy logic control (FLC), are implemented to evaluate the performance of NAC-based strategy, and the simulation results suggest that the guaranteed stability of NAC-based strategy can efficiently prolong fuel cell/battery lifespan and provide better fuel consumption economy for FCHEB.     

针对细微特征进行K-means聚类的电台分选识别技术

现代战场中的无线通信设备日益增多，精准获取个体信息已成为研究热点，但也是难点。针对通信电台，提出了一种分选识别技术。该技术从电台物理层特性出发，对其辐射信号的细微特征进行K-means聚类以实现分选，分选的同时提取各个个体的特征属性值，未知信号通过与特征属性值相关运算实现个体识别。该技术无需先验知识，无需训练运算，通过实验验证，其可行、高效，易于工程实现。     

A Tradeoff Between Accuracy and Speed for K-Means Seed Determination

With a sharp increase in the information volume, analyzing and retrieving this vast data volume is much more essential than ever. One of the main techniques that would be beneficial in this regard is called the Clustering method. Clustering aims to classify objects so that all objects within a cluster have similar features while other objects in different clusters are as distinct as possible. One of the most widely used clustering algorithms with the well and approved performance in different applications is the k-means algorithm. The main problem of the k-means algorithm is its performance which can be directly affected by the selection in the primary clusters. Lack of attention to this crucial issue has consequences such as creating empty clusters and decreasing the convergence time. Besides, the selection of appropriate initial seeds can reduce the cluster’s inconsistency. In this paper, we present a new method to determine the initial seeds of the k-mean algorithm to improve the accuracy and decrease the number of iterations of the algorithm. For this purpose, a new method is proposed considering the average distance between objects to determine the initial seeds. Our method attempts to provide a proper tradeoff between the accuracy and speed of the clustering algorithm. The experimental results showed that our proposed approach outperforms the Chithra with 1.7% and 2.1% in terms of clustering accuracy for Wine and Abalone detection data, respectively. Furthermore, achieved results indicate that comparing with the Reverse Nearest Neighbor (RNN) search approach, the proposed method has a higher convergence speed.     

基于归一化水体指数及其阈值自适应算法的水体遥感反演效果分析

归一化水体指数（NDWI）是水体遥感反演的一种重要指标，其阈值及修正直接影响反演结果的精度。基于Landsat-8与GF-1光学多光谱影像，使用归一化水体指数法阈值0（TH₀）、最大类间方差法（OTSU）自适应阈值（TH_otsu）与均值漂移聚类算法（Mean-Shift）自适应阈值（TH_MS）分别对典型正常水体、云雾覆盖水体、富营养化水体、高含泥沙水体进行水体遥感提取与效果分析，结果表明：正常水体以TH₀为阈值提取精度最高，THMS提取精度次之，TH_otsu提取精度最差；而云雾覆盖水体、富营养化水体以及含泥沙水体使用THMS提取精度最高，尤其少量云雾覆盖下的水体，TH_MS具有更明显的优势，TH₀提取精度次之，TH_otsu提取精度最差；对于不同的阈值，Land?sat-8比GF-1总体表现出更高的水体提取精度。Mean-Shift算法应用于NDWI阈值修正与水体遥感反演具有快速、水质适应性强、效果稳定的优势，对尤其是复杂条件下的水体信息遥感反演具有较好的提取效果。     

Ultrasonically dispersed multi-composite strategy of NiCo2S4/Halloysite nanotubes/carbon: An efficient solid-state hybrid supercapacitor and hydrogen evolution reaction material

Herein, we have developed a novel hybrid material based on NiCo₂S₄ (NCS), halloysite nanotubes (HNTs), and carbon as promising electrodes for supercapacitors (SCs). Firstly, mesoporous NCS nanoflakes were prepared by co-precipitation method followed by physically mixing with HNTs and carbon, and screen printed on nickel foam. After ultrasonication, a uniform distribution of the Carbon/HNTs complex was observed, which was confirmed by surface morphological analysis. When used as electrode material, the NCS/HNTs/C hybrid displayed a maximum specific capacity of 544 mAh g^?1 at a scan rate of 5 mV s^?1. Later, a solid-state hybrid SCs was fabricated using activated carbon (AC) as the negative and NCS/HNTs/C as the positive electrode (NCS/HNTs/C//AC). The device delivers a high energy density of 42.66 Wh kg^?1 at a power density of 8.36 kW kg^?1. In addition, the device demonstrates long-term cycling stability. Furthermore, the optimized NCS, NCS/HNTs, and NCS/HNTs/C nanocomposites also presented superior hydrogen evolution reaction (HER) performance of 201, 169, and 116 mV in the acidic bath at a current density of 10 mA cm^?2, respectively. Thus, the synthesis of NCS/HNTs/C nanocomposite as positive electrodes for hybrid SCs opens new opportunities for the development of next-generation high energy density SCs.     

基于混合模式快速电荷平衡的神经刺激器

设计实现了一种可用于脊髓神经刺激器的多通道大电流神经刺激器。提出将电极短接和插入短电流脉冲相结合的混合模式,在大电流下,能更加快速地实现电荷平衡。电路设计上,将ADC动态比较器的回踢噪声消除技术应用于神经刺激器,使得动态比较器在输入压差较小时能够输出正确的比较结果,从而将电极上残留电压保持在更安全的范围内。基于CSMC 0.25 μm BCD工艺进行设计与仿真,结果表明,在单向且最大刺激电流为4 mA、刺激脉宽为60 μs、刺激周期为750 μs的条件下,该15 V、16路神经刺激器能实现±50 mV安全电压的有源电荷平衡。     

直流配网型混合动力系统在车客渡船上的应用

针对车客渡船动力负荷切换频繁,传统柴油机推进油耗高、排放和噪声大的问题,提出一种基于变速发电机组和超级电容储能装置的直流配网型混合动力系统。目前系统已成功应用于“江苏路渡3011”轮,实船运行数据显示:该混合动力系统不仅能达到较好的节油效果、降低排放,更在操控性、舒适性上优于传统的柴油机推进模式。     

聚类混合型数据的密度峰值改进算法

聚类混合型数据，通常是依据样本属性类别的不同分别进行评价。但这种将样本属性划分到不同子空间中分别度量的方式，割裂了样本属性原有的统一性；导致对样本个体的相似性评价产生了非一致的度量偏差。针对这一问题，提出以二进制编码样本属性，再由海明差异对属性编码施行统一度量的新的聚类算法。新算法通过在统一的框架内对混合型数据实施相似性度量，避免了对样本属性的切割，在此基础上又根据不同属性的性质赋予其不同的权重，并以此评价样本个体之间的相似程度。实验结果表明，新算法能够有效地聚类混合型数据；与已有的其他聚类算法相比较，表现出更好的聚类准确率及稳定性。     

基于混合蚁群算法的异质车队低碳VRP研究

针对货运车辆在配送调度过程中产生大量碳排放的问题，建立模型将多种影响碳排放量的因素协同优化。模型中考虑了不同载重量的异质车队，两个节点之间有多条道路的柔性路径，以及车辆重量随卸货而减少的动态负载等因素，以碳排放量、行驶时间和行驶路程为优化目标，并加入了节点需求时间窗、根据速度变化划分路段、交接和卸货时间的约束。提出了一种混合蚁群算法，利用蚁群算法信息素强度更新方式保持群体记忆性，利用粒子群算法的快速收敛特性增加计算效率。通过随机数值算例的仿真优化与对比分析，验证了算法和模型的有效性。     

Stochastic stabilization and destabilization of nonlinear and time‐varying hybrid systems by noise

The aim of this article is to design a suitable strength function g(t,x,r(t)) such that the Wiener noise g(t,x(t),r(t))dw(t) either stabilizes or destabilizes a given nonlinear and time‐varying hybrid system . To this end, the basic properties, including the existence and uniqueness of the local and global solutions and the nonzero property of solutions of the nonlinear and time‐varying hybrid stochastic systems, are first investigated as the theoretical basis of the article. Second, two theorems and the corresponding corollaries on the stability and instability of the hybrid stochastic systems are established. Third, the design method for the noise strength g(t,x,r(t)) is then proposed based on the established theorems. We also point out that the Markov jump r(t) may have a stabilizing (respectively, destabilizing) effect when we design the noise strength g(t,x,r(t)) so that the introduced noise g(t,x(t),r(t))dw(t) stabilizes (respectively, destabilizes) the corresponding hybrid system. Finally, we illustrate our method using two examples. Compared with the existing literature, our method is suitable for a wider class of nonlinear and time‐varying systems with weaker conditions than quasi‐linear systems.