基于神经网络的内燃机车燃烧系统故障诊断

提出一种内燃机车燃烧系统故障诊断的新方法.燃烧系统的工作状态由柴油机功率、燃油消耗率、燃油压力、增压压力和排气温度等热工参数决定,介绍了有关参数的测量与计算,利用附加动量及自调整学习速率的BP神经网络对内燃机燃烧系统进行故障诊断.通过实例证明该方法是一种行之有效的方法.     

浅析40T支架搬运车液压系统油温变化对其效率的影响

介绍了油温变化对40T支架搬运车液压系统油液黏度、液压介质和橡胶类密封件的影响,分析了液压系统的总发热功率、总散热功率,结合动态热平衡的计算,找出了液压系统总效率与油温变化之间的关系,并给出其函数关系式。根据这种关系,通过一种工况的油温实测数据取样,计算出相应的效率值,定量地验证了液压系统油温变化引起效率变化的关系,得出了总效率随着温度变化而变化的结论,即温差增大时,总效率降低;温差减小时,总效率增大。通过该结论可以全面掌握系统的工作状态,通过降低油温有效提高效率。     

一种基于QoS参数归约的云计算环境能效评估方法

高性能、低功耗且具有QoS保障的高能效问题是云计算领域的一个研究难点。目前的研究主要是通过限定一个约束条件寻求另外指标的最优来实现三者之间的折衷或均衡,缺乏一种有效的能效计算方法和评估模型将三者整合,以更好地描述云环境能效的“程度”。提出一种云环境下QoS参数的归约方法和加权的能效模型,把系统性能作为一个关键因素引入QoS,并将离散的多个QoS参数度量值归约到同一个量纲区域内,获得评价权重矩阵,求得用户最终的QoS评价值,以单位能耗所提供的整体QoS水平值作为能效值,并且建立云数据中心的能效分级标识,最终将云环境下能效值刻画为一个定性的概念,实现了对云环境下能效的定性评估。此外,分别对单机环境和同构、异构的云计算环境中云数据中心的能效进行了评估分析,并进行了实验验证。实验结果表明,所提出的能效模型和评估方法在评价云系统的QoS水平和能源消耗方面是有效的。     

内燃机车燃烧系统性能评估与预测

提出一种内燃机车燃烧系统综合性能评估和预测的新方法;燃烧系统的工作性能由柴油机功率、燃油消耗率、燃油压力、增压压力和排气温度等热工参数决定,介绍了有关参数的测量与计算,利用模糊理论对燃烧系统进行性能评估,利用灰色神经网络对燃烧系统的性能进行预测;该成果应用于株洲电力机车研究所研制的内燃机车状态监测与诊断系统,实际评估和预测结果验证了采用模糊理论进行性能评估和利用神经网络进行预测的可行性与有效性,与机车的其它诊断方法比较,能更全面地评估和预测燃烧系统的状态,为内燃机车检修提供了可靠依据。     

电网设备能效综合评估算法及其应用

为了降低电网能耗,为其设备优化升级提供指导,以电网主要设备为研究对象,建立了能效综合评估算法。首先分析电网设备能效影响因素,建立设备能效模型,从单类设备综合损耗率与单台设备损耗率严重超标台数率两个方面挖掘能效指标并给出指标计算方法。考虑到各指标对能效影响的重要程度是多方面的,建立递阶层次结构模型,采用层次分析法计算指标的权重值,同时采用模糊综合评价法计算指标的能效量化分值,以克服其模糊性。采用所建立的算法对某电网的主要设备进行能效分析评估,结果表明了该方法的实用性和有效性。     

灌注泵性能参数测试系统研究

为了降低油田注氮采油的成本,大大提高石油采收效率,通常液氮泵车上采用灌注泵装置辅助进行开采作业。故对灌注泵的性能参数进行测量,并且对其参数进行在线检测,成为灌注泵性能测试系统研究的重要内容。需要检测主要参数有:灌注泵流量、扬程、功率、效率等参数,均采用了计算机测试系统实现对灌注泵各性能参数及其关系的测试与分析,以便于较好的满足液氮泵车在现场的直接使用。     

基于BLDCM的光伏水泵系统优化设计

在直流无刷电机的小功率光伏水泵系统效率优化问题的研究中,光伏阵列光电转化效率低,传统的直流无刷电机调速系统动态性能差、控制精度低,离心泵的扬程和流量匹配困难.为提高光伏水泵系统的效率,采用扰动观察法对光伏阵列的输出进行最大功率跟踪控制,采用变速积分的转速电流双闭环控制方法对直流无刷电机的调速系统进行优化控制,并根据离心泵的泵外特性和实际的应用环境对离心泵的扬程和流量进行最佳匹配.仿真结果表明扰动观察法能够快速、稳定的使光伏阵列跟踪输出最大功率;利用变速积分的转速电流双闭环调速系统动态响应性能良好,控制精度高;水泵的流量在满足用户需求的同时,扬程也符合提水要求,实现了扬程与流量的最佳匹配.经过优化,大大提高了光伏水泵系统的效率,成功完成了光伏水泵系统的优化设计.     

基于LS-SVM的涡轮增压发动机性能预测

针对神经网络方法在涡轮增压发动机性能预测方面存在的缺陷,提出了一种新的基于最小二乘支持向量机的涡轮增压发动机性能智能预测方法.介绍了最小二乘支持向量机的基本算法,分析了涡轮增压发动机的性能指标,选择发动机转速、压缩比、容积效率、平均指示压力和平均制动压力作为预测模型的输入参数,输出功率、输出扭矩和有效燃油消耗率作为预测模型的输出量,进一步建立了基于最小二乘支持向量机的涡轮增压发动机性能预测模型.仿真实例的预测结果表明,所建立的智能涡轮增压发动机性能预测模型是合理有效的.     

增程式电动汽车自校正变结构模糊控制策略

针对增程式纯电动汽车的结构,为了提高燃油效率保证燃油经济性、限制充放电电流、延长电池使用寿命,提出了一种基于自校正变结构模糊的增程器控制策略。综合考虑电池电量SOC及其变化率、驱动电机功率需求,通过模糊控制调整增程器的输出功率进行能量分配。首先根据SOC值与驱动电机功率需求设计多输入单输出模糊控制器,输出量为增程器的功率;其次根据SOC值将电池状态分为充电模式与放电模式,对不同模式制定不同的模糊控制规则,进行模糊控制器的变结构设计;再次根据SOC值的变化率进行自校正设计,通过限制SOC变化率实现对电池充放电电流的限制,达到对电池的保护功能;最后通过Cruise仿真软件和台架测试对该控制策略进行仿真验证,结果表明燃油经济性以及电池寿命均得到有效提升。     

单向混合三相电压航空整流电路功率控制北大核心CSCD

为了满足航空中频电源高效率、高可靠性及低谐波畸变率的要求,针对单向混合三相电压型整流器(UHTPVSR)拓扑结构特点,提出了一种最优功率控制策略。首先,对UHTPVSR进行总功率计算,按Vienna整流器承担较小负载功率,且确保其输入电流不失真的情况下,得到Vienna与SSTPR之间的最优功率配比;其次,通过输出功率瞬时值,按最优功率配比,计算出功率外环有功参考电流的前馈参考值,从而设计内环无源电流控制器。理论分析和仿真结果表明,当功率配比kPaa=0.5时,UHTPVSR效率为90.3%,SSTPR效率为94%,Vienna效率为86.7%,且UHTPVSR谐波畸变率为3.3%。     

Power conversion optimization for hydraulic systems controlled by variable speed drives

Pumps are widely used in various domestic and industrial applications, such as in water and waste water, food and beverage, and oil and gas applications. In most cases, a pump is controlled by an asynchronous motor which converts the electrical power into the mechanical power required for the pump operation. The motor can be either connected directly to the mains (DOL) or controlled by a variable speed drive (VSD). The energy management of a global pumping system becomes very important to reduce the energy cost of the installations and optimize the maintenance cost, for instance, by increasing the lifetime of the equipment. A VSD is essential to increase the energy efficiency of the overall pump system. A VSD allows delivering all possible mechanical working points (speed, torque), and consequently, only the mechanical power required by the system. Furthermore, a VSD plays an important role in optimizing the electrical energy consumed by the motor as a function of the mechanical energy provided to the pump. This is achieved by minimizing the electrical heat energy losses. In this paper, we propose an original method for electrical energy optimization for a complete pump system including a motor and drive. The objective is to determine the optimal pump speed that minimizes the electrical energy consumption for a hydraulic operating system point. We model the system including a VSD, a motor, a pump, and the hydraulic application. Subsequently, we define the process optimization problem for a single pump and multiple pumps systems. For the single pump system, we demonstrate that the solution of the optimization problem is equivalent to minimization of the drive and motor losses. For the multiple pumps system, we show that we must also optimize the pump losses. For the hydraulic system using multiple pumps, the process demand is actually shared between these pumps. Thus, the speed of each pump is set such that the total energy consumption of the global pumping system is optimized. The simulation and experimental results exhibit the relevance of this power optimization approach for hydraulic pumping systems.     

基于单片机的双燃料汽化器微机控制系统设计

汽油发动机双燃料汽化器采用乙醇和汽油分开放置的燃料储存方式,避免了乙醇汽油存在的诸多弊端,在此,设计了以AT89S52单片机为核心的双燃料汽化器的微机控制系统,该控制系统实现了双燃料汽化器的按键显示、缺液检测及报警、发动机转速测量及计算、乙醇泵堵转检测及保护、乙醇量喷射控制、液压缸液压杆限位检测及保护等功能,同时,能实时采集汽车发动机的转速信号,通过预置的软件对发动机转速进行分析,精确计算出乙醇单次喷射时间和喷射频率,从而准确控制乙醇与空气、汽油的按配比混合掺烧,提高了汽油的燃烧效率,降低了油耗,减少了有害物质的排放,达到了节能减排的目的;实际应用中,该控制系统运行稳定,抗干扰性能良好,控制准确,具有一定的实际应用价值。     

油田电网的谐波治理

在油田生产中,主要生产工艺由各种机泵完成,用电量占油田总用电量的80%以上。为降低能耗,目前油田各类机泵广泛应用调速变频器。但在降低能耗的同时产生了大量谐波,造成电网二次污染,常导致继电保护误动作、电气设备绝缘击穿、电力计量仪表误差增大等问题。通过谐波治理可以清洁电网,提高电能质量,降低无功损耗,具有较好的经济效益。     

基于多目标遗传算法的柴电混合动力船舶功率分配优化

船舶在传统的柴油机推进模式时,低负荷下船用主机性能不佳,燃油消耗率高,燃烧质量差,在提高经济指标和减少排放指标方面遇到瓶颈。柴-电动混合动力推进形式能够通过合理的分配,有效降低燃料消耗和排放。针对混合动力船舶的动力结构,构建关于油耗和污染物排放的多目标优化模型。采用多目标遗传算法(NSGA-II)优化功率在主机和发电机间的分配问题,旨在所有目标之间进行折衷处理,尽量达到Pareto最优。选取某深水三用工作船的典型负荷进行优化计算和仿真验证,仿真结果表明优化后的结果能够兼顾排放性和经济性,提高船舶能效。     

基于多目标优化模型的电动汽车增程器油耗及排放优化

针对增程式电动汽车油耗和排放优化问题,首先综合考虑增程器的油-电转换效率特性、HC排放特性、CO排放特性以及NOx排放特性,构造了增程器油耗和排放多目标优化模型,同时结合实际增程器工作中的机械和电气约束特征,分析了多目标优化模型的3种转速、转矩约束条件.然后采用多目标粒子群算法和加权尺度法对增程器油耗和排放多目标优化模型进行了离线优化,得出了增程器的最优全局工作点和各功率值下的多目标最优工作曲线.最后,采用NEDC,FTP和HWFET3种测试工况在AVL Puma Open发动机测试台架上进行了实验,并和基于最佳制动燃油消耗率(BSFC)的油耗单目标优化模型进行了比较.结果表明,本文提出的方法能够以微弱的油耗增加为代价,有效的改善整车的HC,CO和NOx排放.     

电动汽车增程器燃油效率优化控制

针对如何提高增程器燃油效率,降低整车油耗的问题,提出了一种基于PRP共轭梯度法的增程器燃油效率优化控制方法.首先,以产生给定能量燃油效率最高为优化性能指标,以发动机转矩和发电机转矩为寻优变量,建立了增程器燃油效率优化控制问题的离散系统模型.然后,对算法实现过程中发动机、发电机的最高转速和最大转矩限制的处理方法进行了阐述,给出了基于PRP共轭梯度法的增程器燃油效率优化控制问题的数值实现方法的详细步骤.最后,仿真和实验结果表明本文提出的优化控制方法可以有效提高增程器的燃油效率.     

Effects of engine thermal transients on the energy management of series hybrid solar vehicles

The paper focuses on investigating thermal-transients effects, associated to intermittent use of internal combustion engine (ICE), on fuel economy and hydrocarbon (HC) emissions of series hybrid solar vehicles (HSVs). An offline, non-linear constrained optimization is set-up to individuate the ICE power trajectory that simultaneously minimizes fuel consumption, suitably operates the battery and fully exploits daily solar contribution. The results highlight the importance of including thermal transients in HSV energy management. The combined effects of engine, generator and battery losses, along with cranking energy and thermal transients, produce non-trivial solutions for the engine/generator group, which should not necessarily operate at its maximum efficiency.     

Application of ANFIS Model for Thailand’s Electric Vehicle Consumption

Generally, road transport is a major energy-consuming sector. Fuel consumption of each vehicle is an important factor that affects the overall energy consumption, driving behavior and vehicle characteristic are the main factors affecting the change of vehicle fuel consumption. It is difficult to analyze the influence of fuel consumption with multiple and complex factors. The Adaptive Neuro-Fuzzy Inference System (ANFIS) approach was employed to develop a vehicle fuel consumption model based on multivariate input. The ANFIS network was constructed by various experiments based on the ANFIS Parameter setting. The performance of the ANFIS network was validated using Root Mean Square Error (RMSE) and Mean Average Error (MAE) which related to the setting of ANFIS parameters. The experimental results indicated that the training data sample, number, and type of membership functions are the most important factor affecting the performance of the ANFIS network. However, the number of epochs does not necessarily significantly improve the system performance, too many the number of epochs setting may not provide the best results and lead to excessive responding time. The results also demonstrate that three factors, consisted of the engine size, driving speed, and the number of passengers, are important factors that influence the change of vehicle fuel consumption. The selected ANFIS models with minimum error can be properly and efficiently used to predict vehicle fuel consumption for Thailand’s road transport sector.     

Artificial neural network and fuzzy expert system comparison for prediction of performance and emission parameters on a gasoline engine

This study is deals with artificial neural network (ANN) and fuzzy expert system (FES) modelling of a gasoline engine to predict engine power, torque, specific fuel consumption and hydrocarbon emission. In this study, experimental data, which were obtained from experimental studies in a laboratory environment, have been used. Using some of the experimental data for training and testing an ANN for the engine was developed. Also the FES has been developed and realized. In this systems output parameters power, torque, specific fuel consumption and hydrocarbon emission have been determined using input parameters intake valve opening advance and engine speed. When experimental data and results obtained from ANN and FES were compared by t-test in SPSS and regression analysis in Matlab, it was determined that both groups of data are consistent with each other for p > 0.05 confidence interval and differences were statistically not significant. As a result, it has been shown that developed ANN and FES can be used reliably in automotive industry and engineering instead of experimental work.     

应用椭圆齿轮流量计的内燃机油耗测量系统

介绍一种用于测量内燃机耗油的流量计,以实现对动力机械的燃油控制,达到节能减排的目的.采用椭圆齿轮的测量形式,开发了二次仪表.利用一台喷油泵试验台进行了系统性能验证实验,根据内燃机的实际工作状况,在内燃机三种工况下进行了实验,即最大扭矩转速、最大功率转速以及起动转速.实验结果表明,该测量系统工作稳定,在最大扭矩转速和最大...