机载准双级压缩蒸发制冷系统动态仿真

基于MATLAB Simulink使用移动界面法建立了蒸发器、冷凝器分区集总参数动态模型,采用补气-压缩模型和闪发器模型结合迭代计算时间步长内系统的中间补气压力和流量,建立了准双级压缩机模型,将蒸发循环制冷系统各个部件整合形成准双级压缩蒸发循环制冷系统,用以研究机载准双级蒸发循环制冷系统动态特性。研究表明在单一参数或者多参数改变时系统能较好的提供动态特性参数并提供动态特性仿真曲线,对进一步研究机载蒸发循环制冷系统故障诊断、机载蒸发循环控制方法等有参考意义。     

涡旋式水源热泵系统性能仿真

为了预测涡旋式水源热泵系统变结构和变工况稳态性能,建立了稳态涡旋式热泵系统仿真模型.其中涡旋式压缩机模型考虑了吸、排气换热对工质流量和排气温度的影响以及流量、排气温度和输入功率三者的耦合关系;通过增加电子膨胀阀开度对蒸发器出口过热度的控制模型,反映了过热度对膨胀阀流量的影响.系统算法综合了顺序模块法和连续迭代法,改善了迭代收敛性,且易于实现部件模型的模块化.与实验结果对比表明:模型预测值与实验值的误差小于4.4％.     

液体再循环制冷系统的离心泵

相对于直接膨胀系统,液体再循环制冷系统具有较高的效率和操作灵活性,这两个优势补偿了其系统复杂性增加的缺点。液体再循环制冷系统有时称作超量供液系统,或者泵循环制冷系统,其基本设备如图1所示。正如术语“超量供液”所表示的那样,供给蒸发器的液体比实际蒸发的液体多得多。通过提供过量的液体到蒸发器,蒸发器盘管内表面保持完全湿润且最适于传热。     

变负荷下制冷系统容量调节技术研究

针对高精度恒温恒湿制冷系统绝大部分时间运行在可变负荷条件下的现状,提出一种基于关键阀件联调变容技术的制冷系统。通过分析制冷系统负荷率与制冷剂流量的匹配关系,设计制冷剂流量自动分配方法,调节制冷剂在蒸发器中的蒸发量,使之与负荷变化相适应。与典型制冷系统开展性能对比试验研究,结果表明,采用关键阀件联调变容技术改造的制冷系统比改造前节能25%以上,控温精度高（〈0.2℃）,可以有效延长压缩机的使用寿命。     

变工况涡旋压缩机性能拟合方程的建立

采用最小二乘法原理建立涡旋压缩机的性能拟合方程，提供变工况时以蒸发温度、冷凝温度或蒸发压力、冷凝压力相关的压缩机五大性能参数（质量流量、制冷量、输入功率、运行电流、COP）的通用拟合方程。为建立完整的空调和制冷系统提供数值计算，为空调和制冷系统的动态特性模拟和优化设计提供通用、方便的数学模型。     

GREATLAB仿真软件在风管送风式空调制冷系统中的设计应用

用GREATLAB仿真软件对1.5HP风管送风式空调制冷系统压缩机、冷凝器、蒸发器、节流毛细管四个主要部件进行仿真模拟设计,代入到整个制冷系统的动态仿真模块进行仿真计算得出名义制冷工况下空调机组制冷量、功率、吸气温度、排气温度、吸气压力、排气压力等参数,并进行实验验证,得出名义工况下制冷量与仿真计算制冷量误差在5%以内。结果表明:GREATLAB仿真软件能够用于指导商用一拖一空调系统的设计,可作为开发和优化商用空调系统的有效工具。     

大型结冰风洞制冷系统蒸发压力预测与降温过程优化研究

构建了液氨蒸发器热力学仿真模型,进行了蒸发压力以及风洞降温的预测与验证。采用BP神经网络算法对试验数据和仿真数据进行训练,建立了氨制冷系统蒸发压力快速预测模型,分析了试验高度和试验风速对风洞降温速度的影响,提出了变风速降温控制方式,对比分析了不同降温控制过程的降温时间及系统能耗。结果表明:对于高空环境试验,先进行风洞减压再降温,可以有效缩短降温时间、减小系统能耗;试验风速75 m/s时风洞系统降温速度最快,高于75 m/s时可以通过降温过程变风速控制方法降低系统能耗。     

变步长LMS自适应均衡算法研究

为解决宽带无线通信中由多径信道产生的符号间干扰,对最小均方(LeastMeanSquares,以下简称LMS)自适应均衡算法进行深入分析。针对LMS算法收敛速度和稳态均方误差相互矛盾的问题,重点研究变步长LMS算法,在现有算法的基础上,进行步长分析,提出一种新型变步长LMS算法。利用信道响应长度、均衡器阶数、收敛误差共同控制迭代步长,简化步长设置,提升算法的收敛速度并降低稳态均方误差。仿真分析表明新型变步长LMS算法有更好的收敛特性。     

变排量压缩机汽车空调制冷系统特性分析

为了解决变排量压缩机汽车空调系统振荡和蒸发器结霜问题,对该系统稳态特性进行分析。建立了变排量压缩机汽车空调制冷系统稳态模型,模拟结果与试验数据吻合较好。系统存在变排量压缩机定转速定行程、变转速定行程、定转速变行程和变转速变行程四种运行方式,本文对四种方式下汽车空调制冷系统的稳态特性进行了分析。研究首次发现,在变活塞行程情况下,与定行程方式下性能参数——对应关系不同,蒸发压力、制冷量等系统参数表现为多值对应关系,系统存在“性能带”,可使蒸发压力保持在一个较小的范围内变化。变排量压缩机汽车空调制冷系统性能带的发现和提出,丰富和发展了制冷系统特性分析理论。     

日光型植物生长箱迹负荷制冷系统的设计

本文从气候条件的变化和植物生长要求的温度等方面详细分析了植物生长环境试验箱制冷系统的变负荷特性提出了采用新结构蒸发器，改进制冷管路系统，和超常规送风量设计等措施。     

Generic simulation model of multi-evaporator variable refrigerant flow air conditioning system for control analysis

Generic simulation models noted as AGM-I and AGM-II for performance and control analysis of variable refrigerant flow (VRF) systems were developed. Firstly, simulation models from component to whole VRF system were addressed. Then the simulation models were validated using experimental data reported in an open literature. The average error percentages to predict system cooling capacity, energy consumption and COP are 4.69%, 4.64%, 1.19%, respectively. Finally, tests were carried out. Results show that the developed models are fast computing and evaporator-number independent. From the computation speed point of view, the AGM-I is more suitable for multi-evaporator VRF system, while the AGM-II is more suitable for the one evaporator VRF system. Test results also show the system models good ability responding to varying conditions, including inlet air temperature of the evaporator, outdoor air temperature, opening of the EEVs and compressor speed, which are all very important variables for the control analysis.     

基于决策树算法的多联机气分插反故障诊断

本文将决策树算法应用于多联机气分插反故障诊断中,搭建了多联机实验平台采集数据,根据专家知识及数据变化模型验证选取了建模的特征变量,采用决策树C5.0算法构建气分插反故障诊断模型,进一步对由模型分类规则生成的最优变量即过冷器的EEV（电子膨胀阀）进行深入分析和验证。结果表明：将决策树算法应用于多联机气分插反故障诊断的方法,准确率为96%,有较高的准确性和可靠性,此诊断方法能满足多联机故障诊断实际运用的需要。由于多联机发生气分插反故障时,系统过热度降低,为保证多联机系统的制冷效果和能效比,可通过增大过冷器EXV开度调节。     

Stochastic Subset Optimization for optimal reliability problems

Reliability-based design of a system often requires the minimization of the probability of system failure over the admissible space for the design variables. For complex systems this probability can rarely be evaluated analytically and so it is often calculated using stochastic simulation techniques, which involve an unavoidable estimation error and significant computational cost. These features make efficient reliability-based optimal design a challenging task. A new method called Stochastic Subset Optimization (SSO) is proposed here for iteratively identifying sub-regions for the optimal design variables within the original design space. An augmented reliability problem is formulated where the design variables are artificially considered as uncertain and Markov Chain Monte Carlo techniques are implemented in order to simulate samples of them that lead to system failure. In each iteration, a set with high likelihood of containing the optimal design parameters is identified using a single reliability analysis. Statistical properties for the identification and stopping criteria for the iterative approach are discussed. For problems that are characterized by small sensitivity around the optimal design choice, a combination of SSO with other optimization algorithms is proposed for enhanced overall efficiency.     

Non-smooth/non-convex economic dispatch by a novel hybrid differential evolution algorithm

This paper presents a novel stochastic optimisation approach to determining the feasible optimal solution of the economic dispatch (ED) problem considering various generator constraints. Many practical constraints of generators, such as ramp rate limits, prohibited operating zones and the valve point effect, are considered. These constraints make the ED problem a non-smooth/non-convex minimisation problem with constraints. The proposed optimisation algorithm is called self-tuning hybrid differential evolution (self-tuning HDE). The self-tuning HDE utilises the concept of the 1/5 success rule of evolution strategies (ESs) in the original HDE to accelerate the search for the global optimum. Three test power systems, including 3-, 13-and 40-unit power systems, are applied to compare the performance of the proposed algorithm with genetic algorithms, the differential evolution algorithm and the HDE algorithm. Numerical results indicate that the entire performance of the proposed self-tuning HDE algorithm outperforms the other three algorithms.     

变频空调制热工况仿真模块的开发与实验研究

在美国能源部动态建筑能耗模拟软件EnergyPlus的基础上,提出适合于动态能耗计算的变频多联空调（VRF）能耗算法,并开发相应的计算模块;同时,建立VRF实验测试系统,在冬季测试数据的基础上,进行能耗仿真比较验证。结果表明,平均供热量和耗电量误差分别为34．97％和26．51％,VRF能耗计算模块能够追踪EnergyPlus负荷计算的精度,并且正确反映机组的能耗特性。     

An efficient joint channel estimation and decoding algorithm for turbo-coded space?time orthogonal frequency division multiplexing receivers

The challenging problem in the design of digital receivers of today's and future high-speed, high data-rate wireless communication systems is to implement the optimal decoding and channel estimation processes jointly in a computationally feasible way. Without realising such a critical function perfectly at receiver, the whole system will not work properly within the desired performance limits. Unfortunately, direct implementation of such optimal algorithms is not possible mainly due to their mathematically intractable and computationally prohibitive nature. A novel algorithm that reaches the performance of the optimal maximum a posteriori (MAP) algorithm with a feasible computational complexity is proposed. The algorithm makes use of a powerful statistical signal processing tool called the expectation maximisation (EM) technique. It iteratively executes the MAP joint channel estimation and decoding for space'time block-coded orthogonal frequency division multiplexing systems with turbo channel coding in the presence of unknown wireless dispersive channels. The main novelty of the work comes from the facts that the proposed algorithm estimates the channel in a non-data-aided fashion and therefore except a small number of pilot symbols required for initialisation, no training sequence is necessary. Also the approach employs a convenient representation of the discrete multipath fading channel based on the Karhunen'Loeve (KL) orthogonal expansion and finds MAP estimates of the uncorrelated KL series expansion coefficients. Based on such an expansion, no matrix inversion is required in the proposed MAP estimator. Moreover, optimal rank reduction is achieved by exploiting the optimal truncation property of the KL expansion resulting in a smaller computational load on the iterative estimation approach.     

基于SVR-OCSVM模型的多联机系统用能评估与诊断

直接根据多联机系统能耗数据的变化来判断导致能耗大幅波动的因素是很困难的。本文提出一种有效的可用于多联机系统的能耗评估与诊断方法:将支持向量回归(SVR)算法与单类支持向量机(OCSVM)算法相结合,首先通过提取系统能耗数据集特征,去除非稳态数据,根据提取的特征变量与系统能耗建立SVR模型,预测多联机系统能耗;然后将实际能耗值与预测能耗值之差和之比分别标准化,作为输入变量,建立单类支持向量机(OCSVM)模型进行样本判别,确定是否为导致系统能耗异常的原因,以此评估诊断多联机系统能耗情况。本文基于多联机能耗正常的数据集构建了能耗评估与诊断模型,并用多联机系统能耗异常数据集验证了模型的可靠性。结果表明:基于SVR-OCSVM模型的能耗评估与诊断模型具有较高的准确度,基本能达到70%以上。     

EnergyPlus中变频多联空调系统蒸发温度控制能耗仿真模块的开发与实验验证

在当前建筑节能的理念和科技背景下,如何选用合适的空调系统方式来节约建筑物设备能耗,是建筑节能领域学者们最关注的问题之一.由于变频多联空调系统(VRF系统)具有良好的节能性,这种系统的仿真研究近年来发展迅速.利用基于BESP平台的EnergyPlus软件中建立的变频多联空调系统仿真模块和性能曲线法新增加的变频多联空调系统在改变蒸发温度的情况下VRF空调系统制冷量和能耗的计算功能,对实际办公室进行的夏季典型日空调系统能耗进行计算,并与实验结果进行对比及误差分析,对原模型进行了改进并提出了相应的建议.     

Complex process monitoring using modified partial least squares method of independent component regression

In this paper, first, some disadvantages of original partial least squares method of independent component analysis (ICA-PLS) are analyzed. Then ICA-PLS is modified for regression purpose.Disadvantages of the original ICA-PLS algorithm are as follows: 1) the regression coefficient matrix and residual matrix cannot been given so that the computation time may increase with the number of samples; and 2) ICA-PLS lacks the ability to give better monitoring performance when the correlation structure of measured variables is nonlinear, which is often the case for industrial processes.To solve the above problems, we modified the original algorithm in following aspects: 1) the regression coefficient matrix and residual matrix in ICA-PLS are given so that the computation time is decreased; and 2) to solve the nonlinear problem, ICA-PLS and kernel trick is first combined for nonlinear regression purpose, which is called iterative ICA-KPLS in this paper. The iterative calculation of ICA-KPLS will be time consuming when the sample number becomes larger. Hence, the regression coefficient matrix and residual matrix in ICA-KPLS are given to avoid the expensive computation time when the number of samples is huge.The proposed methods are applied to the quality prediction in fermentation process and Tennessee Eastman process. Applications indicate that the proposed approach effectively captures the relations in the process variables and use of ICA-KPLS instead of ICA-PLS improves the predictive ability. The expensive computation time is avoided by using the coefficient matrix and residual matrix.