新普锐斯混合动力汽车系统结构与故障诊断

混合动力(HEV)汽车是指汽车使用燃油驱动和电力驱动两种驱动工作方式。文章结合混合动力汽车系统结构原理与故障诊断及检修方法,以新普锐斯混合动力汽车架构及技术特点为例,着重就HEV、THSⅡ组成、主要部件功能,混合动力汽车工作安全、维护与检修特点方法进行分析和研究。     

混合动力电动汽车制动能量回馈系统分析

制动能量回收是混合动力电动汽车提高能量利用率的关键,而且有效的制动能量回收能够延长电动汽车的行驶里程。文章从HEV的制动模式的种类入手,在阐述了制动能量回收的约束条件之后,就混合电动汽车利用ABS进行有效制动实现防抱死现象分析HEV的制动能量回馈系统,希望能够给混合动力电动汽车制动能量回馈的研究提供相关参考。     

对伏安法测量太阳电池输出特性实验的研究

采用电流表内接法和外接法2种方法对太阳电池的输出特性进行了测量,发现采用内接法测量时电流表的内阻不可忽视。通过对数据的分析拟合求解出了电流表的内阻,用求得的电流表内阻值对内接法测量的数值进行拟合,所得数据与采用外接法测量所得的数据基本吻合。     

对伏安法测量太阳电池输出特性实验的研究

采用电流表内接法和外接法2种方法对太阳电池的输出特性进行了测量,发现采用内接法测量时电流表的内阻不可忽视.通过对数据的分析拟合求解出了电流表的内阻.用求得的电流表内阻值对内接法测量的数值进行拟合,所得数据与采用外接法测量所得的数据基本吻合.     

车用动力镍氢电池闪亮登场

动力电池一直困扰着世界“绿色”汽车的发展。国家“863计划”一个项目的完成．使我国在该领域又前进了一大步。由北京理工大学牵头，联合国家高技术绿色材料发展中心、中山中炬森莱高技术有限公司、北京航空航天大学等单位承担的《E07200HEV混合动力轿车用镍氢动力电池组及管理模块》课题在广东省中山市通过了验收。     

内燃机车交流传动及控制系统研究

内然机车是货运列车的重要动力来源,为了更好的发挥内然机车的作用,需要研究柴油机装置和列车动轮之间的动力传递。本文首先对内燃机车的交流传动进行研究,然后分析内燃机车的控制系统,期待有关人士一起深入研究,共同促进我国内燃机车整体制造水平的提升。     

HEV控制策略典型运用研究

本文简要叙述了HEV控制策略的含义,指出混合动力汽车开发的核心内容和技术难点是动力控制系统的开发,介绍了几种典型的HEV控制策略:静态逻辑门限控制策略、瞬时优化控制策略、全局最优控制策略、智能控制策略。     

混凝土自锚式悬索桥动力性能分析及成桥动力特性检测

作为反映结构动力特性的模态参数,固有频率、振型是评价桥梁动力性能的重要依据。以下以浙江省江山市北关大桥为例,基于ANSYS软件建立了该混凝土自锚式悬索桥的有限元计算模型,并对其进行模态分析,得出了相关模态参数。在此基础上结合自由振动和环境随机振动试验结果,对该桥的自振特性进行了分析。     

光伏阵列在不均匀光照下的输出特性仿真研究

文章以Matlab/Simulink为工具建立仿真模型,得到在不均匀光照下光伏阵列的输出特性.根据光伏发电的原理和光伏电池的内部结构,在simulink中搭建模型光伏阵列的模型.在不同的光照条件下,通过对模型的仿真得到I-U曲线和P-U曲线,根据仿真结果对输出特性进行总结并得出结论.     

振动在汽车动力传动系统中的研究

汽车动力传动系统的主要振动形式包括弯曲振动和扭转振动,现阶段研究动力传动系弯曲振动的主要方法是试验模态分析和有限元分析法。关于传动系统扭转振动方面的研究很多专家都获得了很大的成果并取得了一定的进步。但限于分析条件,对汽车动力传动系弯-扭振动藕合的研究尚不完善。因此,本文在研究动力传动系弯曲、扭转振动的的基础上,开展了弯-扭振动藕合特性影响的研究。     

Bias and Sensitivity of Multipliers

Multipliers measure the derivatives of endogenous variables with respect to exogenous shocks and are functions of the structural parameters of an economic model. Substitution of the structural parameter estimates yields a so-called derived estimate for a multiplier or any reduced-form parameter. Derived estimates are biased. This paper presents first-order approximations to the biases and sensitivities of multipliers. The good performance of a flawed formula in input–output analysis is illuminated.     

The Evolution of Production Structures,Analyzed by a Multi-layer Procedure

In this paper, a new method of so-called qualitative input–output analysis is outlined, which is called minimal flow analysis (MFA). It extracts the characteristic production structure given in an input–output table, on the basis of anendogenized threshold value. Formally, this is achieved by the binarization of the entries of different table layers which are reformulated according to the Eulerian sequence. The condensed characteristic structure of the economy is then obtained by means of graph theoretical methods. The new method is able to uncover production structures, even in highly aggregated tables. If applied to a chronological sequence of tables, as shown for German tables 1978–88 in detail, the MFA method can disclose the evoluton of sectoral structures.     

福建特色农产品物流发展模式研究

近年来,福建省特色农产品产量逐步提升,但缺乏完善的物流体系。文中在分析福建特色农产品物流发展现状和现有物流模式的基础上,剖析福建特色农产品现有物流模式存在问题,探索并提出构建福建特色农产品高效物流运作的模式。     

The Subsystem—MFA: A Qualitative Method for Analyzing National Innovation Systems—The Case of Germany

The paper develops a method derived from the so-called minimal flow analysis (MFA), based on a subsystem approach, to find the characteristic technology flow structure of a national innovation system. The analysis uses input–output tables for Germany for the years 1980 and 1986, as well as innovation expenditure vectors, released by the Ifo-Institut, detailed for 58 sectors for the same years. The data are integrated into a subsystem approach and deliver a matrix of technology providers and technology users, which is analyzed by a suitably modified version of MFA. The results, differentiated according to rather economic vs more technical aspects, show what the German innovation system looks like and show that there was little change between 1980 and 1986.     

Ranking sectors using fuzzy output multipliers

Using input–output analysis to model the effects of changes in industry final demands is fraught with problems, many of which relate to the fundamental limitations of the concomitant linear framework. A further issue concerns the accuracy of the results, a consequence of the uncertainty surrounding the values of multipliers. Such uncertainty can create problems where the values of output multipliers are used to inform resource directions. This paper utilizes (and develops) a fuzzy input–output model and investigates the ranking of industries based on fuzzy output multipliers. The non-triviality of the fuzzy model is exposited in a general problem, where imprecision is defined by a proportional level of imprecision (fuzziness) in the technical coefficients. Through a nascent method for ranking fuzzy numbers, comparisons are made between the fuzzy and more traditional (non-fuzzy) analysis.     

Disaggregating input–output tables in time: the temporal input–output framework

The input–output framework has evolved dramatically since its initial formulation. New analytical techniques and extensions have allowed a more comprehensive assessment of the economy and expanded its applicability. Nonetheless, the core of the framework has remained unchanged: an annually compiled input–output table, which conveys monetary flows between sectors in a region in a particular year. Hence, the technical coefficients derived from it are ‘average’ input compositions, neglecting fluctuations in production capacity, seasonality and temporal shocks within that period. This paper develops a consistent methodology to disaggregate the annual input–output table in its time dimension in order to estimate intra-year input–output matrices with distinct technical structures for a particular year. The main advantages in relation to the annual model are to allow seasonal effects to be studied within the input–output framework, to better understand the process of coefficient change and to offer a more comprehensive dynamic view of production.     

Uncertainty in Integrated Regional Models

This paper examines the nature of uncertainty in integrated econometric+input–output (ECIO) regional models. We focus on three sources of uncertainty: (a) econometric model parameter uncertainty; (b) econometric disturbance term uncertainty; and (c) input–output coefficient uncertainty. Through a series of Monte Carlo simulations we analyse the relative importance of each component as well as the question of how their interaction may propagate through the integrated model to affect the distributions of the endogenous variables. Our results suggest that there is no simple answer to the question of which source of uncertainty is most important in an integrated model. Instead, that answer is conditioned upon the focus of the analysis and whether the industry specific or macro level variables are of central concerns.     

Efficiency measurement with multiple outputs and multiple inputs

This paper discusses modeling technical and allocative inefficiencies in both cost minimizing and profit maximizing frameworks with special emphasis on multiple inputs and multiple outputs. Both primal and dual models are considered for this purpose. In the primal approach we use a separable output and input function (the constant elasticity of transformation output function and Cobb-Douglas input function). The dual models assume translog cost or profit functions. Technical inefficiency is assumed to be random in the cross-sectional models, and fixed firm-specific parameter in the panel data models. Allocative inefficiencies are always treated as input-specific parameters. We derive exact relations linking technical inefficiency and allocative inefficiencies to cost and profit when the underlying technology is represented by a flexible functional form such as the translog. It is shown that appending a one-sided homoscedastic error term to model technical inefficiency, or neglecting technical inefficiency altogether in a translog profit tunciton results in model misspecification and inconsistent parameter estimates.     

Evaluating the FLQ and AFLQ formulae for estimating regional input coefficients: empirical evidence for the province of Córdoba,Argentina

This paper uses survey-based data of the Argentinian province of Córdoba to conduct an empirical test of the performance of the Flegg's location quotient (FLQ) and augmented FLQ (AFLQ) formulae for estimating regional input coefficients. A comparison is made with conventional methods based on location quotients. The possibility of using prior information about the extent of self-sufficiency of particular sectors is explored. The empirical work employs a range of statistical criteria with contrasting properties, and examines performance in terms of each method's ability to estimate regional input coefficients, output multipliers and imports. Particular attention is paid to the problem of choosing a value for the unknown parameter δ in the FLQ and AFLQ formulae. These formulae are found to give the best overall results of the non-survey methods considered in the paper. However, the AFLQ typically produces slightly more accurate results than the FLQ, in line with the findings of previous studies.     

Alternative Approaches of Physical Input–Output Analysis to Estimate Primary Material Inputs of Production and Consumption Activities

In the last few years, a number of studies have been presented that link material flow accounting and input–output analysis (based on monetary input–output tables) for the calculation of direct and indirect resource inputs for production and consumption activities. The compilation of the first physical input–output tables for some European countries in the 1990s opened new possibilities for linking physical accounting and input– output analysis. Physical input–output analysis has so far only been applied for selected materials, but it has not been used for comprehensive assessments of material requirements of economic activities. In this paper, possibilities and limits of this new input–output approach are clarified. We present and discuss a procedure similar to monetary input– output analysis and develop an alternative approach to account for primary inputs and waste otherwise not included in the analysis. Based on aggregated input–output tables for Germany, we present numerical examples intended to compare the alternative approaches of physical input–output analysis.