汽车用动力锂离子电池发展现状

对汽车用动力锂离子电池材料、电池系统的组成及设计应用进行了介绍,对国内外锂离子电池系统主要供应商进行了综述,同时对目前车用锂离子电池系统还存在的主要问题及解决方法进行了探讨,并对锂离子电池系统在新能源汽车上的应用进行了展望。     

AHP_模糊综合评价法在桥梁工程风险评价中的应用探析

现代桥梁工程项目风险涉及面广、技术复杂,承包商若要成功地管理好项目,必须正确地评估及防范风险。桥梁工程风险评价影响因素较多,且多具模糊性和不确定性。该文在分析影响桥梁工程风险因素的基础上,建立了基于AHP_模糊综合评价的桥梁工程风险评价数学模型。该文在此基础上,通过对某长江大桥的风险评价,验证了运用该模型进行桥梁工程风险评价的合理性与可靠性。     

基于量子粒子群算法的门式刚架结构抗风优化

为弥补目前结构抗风优化仅针对高层建筑的不足,采用量子粒子群算法对一大跨屋盖结构进行了抗风优化.基于风洞试验数据库获得等效静力风荷载,并根据型钢表组成离散变量搜索空间.通过约束违反协调系数,构造了一种新的适应值模型,进一步建立了粒子越界处理方法,以保证优化的可行性和收敛性.通过10次运行计算以确定门式刚架的最优设计,并在全风向角下对优化结果进行校核.研究结果表明,目标函数随迭代单调递减收敛,总质量标准差仅为其平均值的4%,平均迭代24次,说明量子粒子群算法用于门式刚架抗风优化具有较好的健壮性和计算效率.      

Grafting watermelon seedling production management system based on process control strategy

Greenhouse environmental management, seedling bed scheduling, and fertilizer and water management are the core technologies of seedling nursery. Precision management and control of the whole production process guarantees high grated seedling quality. In order to improve management efficiency of grafted watermelon seedling production and seedling quality, this paper designs and develops a grafted watermelon seedling production management system based on process control methods by process control strategy, seedling bed planning design, and handheld device technology.     

Image fusion scheme based on nonsubsampled contourlet and block-based cosine transform

A kind of nonsubsampled contourlet and block-based cosine transform (NSCBCT) is developed, and its application in image fusion is studied in this paper. The construction of filtering banks is based on the nonsubsampled contourlet transform (NSCT) and block-based discrete cosine transform (B-DCT). We combine NSCT and B-DCT to design filters that lead to NSCBCT with better singularity representation than either of them in isolation. A design framework based on the hybrid approach is proposed, which allows for the fast implementation based on NSCT and B-DCT respectively. In addition, a new image fusion scheme based on NSCBCT for multispectral and panchromatic satellite images is proposed. Firstly, because it adopts NSCT, the fused satellite images have higher spatial resolution than those based on wavelets. Secondly, based on the localized high frequency information provided by B-DCT, the proposed fusion scheme can reduce the spectral distortion of the fused image further. Experimental results show that the proposed fusion method is able to increase the spatial resolution and reduce the spectral distortion of the fused image at the same time.     

Nonlinear analyses of exchange rates of six emerging markets

This paper presents some empirical evidences on the presence of nonlinearity of exchange rates of six emerging markets by using Brock-Dechert-Scheinkman (BDS) test and Volterra-Wiener-Korenberg (VWK) model, respectively. The nonlinear dependences are found in the exchange rates of six emerging markets. Furthermore, this paper applies the VWK model with surrogate data method to detect if their nonlinear dependences are deterministic or not. The results show that the above exchange rates are deterministic and nonlinear time series. These imply that the exchange rate markets do not conform to the requirements of the random walk hypothesis. Therefore, the nonlinear dynamic model should be used to analyze the exchange rates.     

基于乘客感知的常规公交服务质量评价方法

针对当前城市常规公交服务质量评价的理论研究与实践多侧重设施指标水平的统计分析,而对公交服务主体——乘客感受考虑不足的现状,引入＂顾客感知服务质量＂的概念。提出了以乘客感知和期望之差为基本依据的常规公交服务质量评价方法,建立了公交服务质量评价体系。选取上海市北安跨线和成都市119路公交线路为案例,通过分析实际调查数据,量化评价了两条公交线路的服务质量,验证了评价方法的可行性与有效性。案例研究表明,票价、候车时间、车内空间、换乘便利性是公交服务亟待改善的问题。     

TDOA Passive Location Based on Cuckoo Search Algorithm

This paper formulates a new framework to estimate the target position by adopting cuckoo search(CS)positioning algorithm. Addressing the nonlinear optimization problem is a crucial spot in the location system of time difference of arrival(TDOA). With the application of the Levy flight mechanism, the preferential selection mechanism and the elimination mechanism, the proposed approach prevents positioning results from falling into local optimum. These intelligent mechanisms are useful to ensure the population diversity and improve the convergence speed. Simulation results demonstrate that the cuckoo localization algorithm has higher locating precision and better performance than the conventional methods. Compared with particle swarm optimization(PSO) algorithm and Newton iteration algorithm, the proposed method can obtain the Cram′er-Rao lower bound(CRLB) and quickly achieve the global optimal solutions.     

Adaptive Sliding-Mode Tracking Control for an Uncertain Nonlinear SISO Servo System with a Disturbance Observer

An adaptive sliding mode controller with a disturbance observer (ASMC-DO) is proposed for the control of a single-input and single-output (SISO) servo system which has uncertain parameters, nonlinear friction, disturbance and input saturation. It is difficult to choose the suitable value of the parameters. The newly designed adaptive method is used to reduce the effects of system time-varying parameters, such as the moment of inertia and the damp coefficient. The robustness of object is improved. A DO is selected to approximate the compound disturbance and to render the estimate error convergent in finite time. The stability and the convergence of the closed-loop system are proved by using the Lyapunov theory. Experimental results show that the proposed ASMC-DO can better satisfy the influence of variable parameters and external disturbance to the control precision of the SISO servo system than other two controllers. The effectiveness of the proposed controller is showed. The control input stability and robust performances of the input saturation system are enhanced and the chattering is reduced.     

Adaptive Multi-Objective Optimization of Bionic Shoulder Joint Based on Particle Swarm Optimization

To get the movement mode and driving mechanism similar to human shoulder joint, a six degrees of freedom (DOF) serial-parallel bionic shoulder joint mechanism driven by pneumatic muscle actuators (PMAs) was designed. However, the structural parameters of the shoulder joint will affect various performances of the mechanism. To obtain the optimal structure parameters, the particle swarm optimization (PSO) was used. Besides, the mathematical expressions of indexes of rotation ranges, maximum bearing torque, discrete dexterity and muscle shrinkage of the bionic shoulder joint were established respectively to represent its many-sided characteristics. And the multi-objective optimization problem was transformed into a single-objective optimization problem by using the weighted-sum method. The normalization method and adaptive-weight method were used to determine each optimization index’s weight coefficient; then the particle swarm optimization was used to optimize the integrated objective function of the bionic shoulder joint and the optimal solution was obtained. Compared with the average optimization generations and the optimal target values of many experiments, using adaptive-weight method to adjust weights of integrated objective function is better than using normalization method, which validates superiority of the adaptive-weight method.