Elimination of Fuel Pressure Fluctuation and Multi-injection Fuel Mass Deviation of High Pressure Common-rail Fuel Injection System

The influence of fuel pressure fluctuation on multi-injection fuel mass deviation has been studied a lot,but the fuel pressure fluctuation at injector inlet is still not eliminated efficiently.In this paper,a new type of hydraulic filter consisting of a damping hole and a chamber is developed for elimination of fuel pressure fluctuation and multi-injection fuel mass deviation.Linear model of the improved high pressure common-rail system（HPCRS）including injector,the pipe connecting common-rail with injector and the hydraulic filter is built.Fuel pressure fluctuation at injector inlet,on which frequency domain analysis is conducted through fast Fourier transformation,is acquired at different target pressure and different damping hole diameter experimentally.The linear model is validated and can predict the natural frequencies of the system.Influence of damping hole diameter on fuel pressure fluctuation is analyzed qualitatively based on the linear model,and it can be inferred that an optimal diameter of the damping hole for elimination of fuel pressure fluctuation exists.Fuel pressure fluctuation and fuel mass deviation under different damping hole diameters are measured experimentally,and it is testified that the amplitude of both fuel pressure fluctuation and fuel mass deviation decreases first and then increases with the increasing of damping hole diameter.The amplitude of main injection fuel mass deviation can be reduced by 73%at most under pilot-main injection mode,and the amplitude of post injection fuel mass deviation can be reduced by 92%at most under main-post injection mode.Fuel mass of a single injection increases with the increasing of the damping hole diameter.The hydraulic filter proposed by this research can be potentially used to eliminate fuel pressure fluctuation at injector inlet and improve the stability of HPCRS fuel injection.

Optimization study of a PEM fuel cell performance using 3D multi-phase computational fluid dynamics model

An optimization study using a comprehensive 3D, multi-phase, non-isothermal model of a PEM (proton exchange membrane) fuel cell that incorporates significant physical processes and key parameters affecting fuel cell performance is pre-sented and discussed in detail. The model accounts for both gas and liquid phase in the same computational domain, and thus allows for the implementation of phase change inside the gas diffusion layers. The model includes the transport of gaseous species, liquid water, protons, energy, and water dissolved in the ion-conducting polymer. Water is assumed to be exchanged among three phases: liquid, vapour, and dissolved, with equilibrium among these phases being assumed. This model also takes into account convection and diffusion of different species in the channels as well as in the porous gas diffusion layer, heat transfer in the solids as well as in the gases, and electrochemical reactions. The results showed that the present multi-phase model is capable of iden-tifying important parameters for the wetting behaviour of the gas diffusion layers and can be used to identify conditions that might lead to the onset of pore plugging, which has a detrimental effect on the fuel cell performance. This model is used to study the effects of several operating, design, and material parameters on fuel cell performance. Detailed analyses of the fuel cell per-formance under various operating conditions have been conducted and examined.

Multi-objective steady-state optimization of two-chamber microbial fuel cells

A microbial fuel cell(MFC)is a novel promising technology for simultaneous renewable electricity generation and wastewater treatment.Three non-comparable objectives,i.e.power density,attainable current density and waste removal ratio,are often conflicting.A thorough understanding of the relationship among these three conflicting objectives can be greatly helpful to assist in optimal operation of MFC system.In this study,a multiobjective genetic algorithm is used to simultaneously maximizing power density,attainable current density and waste removal ratio based on a mathematical model for an acetate two-chamber MFC.Moreover,the level diagrams method is utilized to aid in graphical visualization of Pareto front and decision making.Three biobjective optimization problems and one three-objective optimization problem are thoroughly investigated.The obtained Pareto fronts illustrate the complex relationships among these three objectives,which is helpful for final decision support.Therefore,the integrated methodology of a multi-objective genetic algorithm and a graphical visualization technique provides a promising tool for the optimal operation of MFCs by simultaneously considering multiple conflicting objectives.

The Energy Optimization Mathematic Algorithm on Multi-energy Resource Powertrain of Fuel Cell Vehicle

In order to solve the core issue of the energy regulation (ER) on multi-energy resource powertrain of fuel cell vehicle, the work functions of each component were defined; the mathematical algorithm model of energy regulation was established and the relevant solution was found. This algorithm was evaluated successfully on the hardware in loop (HIL) platform under three typical urban running cycles. The results showed ER control target had been realized and the mathematical algorithm was effective and reasonable. Based on the HIL simulation, some conclusions and ER strategies were made. According to the different power component parameters and real time control request, this algorithm should be modified and calibrated for application in the actual control system.

Pyrolyzed Iron Phthalocyanine-Modified Multi-Walled Carbon Nanotubes as Composite Anode in Marine Sediment Microbial Fuel Cells and Its Electrochemical Performance

Improving the performance of anode is a crucial step for increasing output power of marine sediment microbial fuel cells(MSMFCs)to drive marine monitor to work for a long term on the ocean floor.A pyrolyzed iron phthalocyanine modified multi-walled carbon nanotubes composite(FePc/MWCNTs)has been utilized as a novel nodified anode in the MSMFC.Its structure of the composite modified anode and electrochemical performance have been investigated respectively in the paper.There is a substantial improvement in electron-transfer efficiency from the bacteria biofilm to the modified anode via the pyrolyzed FePc/MWCNTs composite based on their cyclic voltammetry(CV)and Tafel curves.The electron transfer kinetic activity of the FePc/MWCNTs-modified anode is 1.86 times higher than of the unmodified anode.The maximum power density of the modified MSMFC was 572.3±14 m W m^-2,which is 2.6 times larger than the unmodified one(218.3±11 m W m^-2).The anodic structure and cell scale would be greatly minimized to obtain the same output power by the modified MSMFC,so that it will make the MSMFC to be easily deployed on the remote ocean floor.Therefore,it would have a great significance for us to design a novel and renewable long term power source.Finally,a novel molecular synergetic mechanism is proposed to elucidate its excellent electrochemical performance.

两种直升机多舱油箱惰化系统代偿损失比较

针对某型直升机多舱油箱,设计了冷却空气控温和燃油热沉控温的2种多舱油箱惰化系统。基于AMESim平台搭建了这2种系统模型,研究了这2种系统的控温效果和各舱油箱参数变化规律,并且引入代偿损失指标对这2种系统性能进行评估。仿真结果表明:2种惰化系统均能控制膜前温度维持在90℃;燃油热沉控温的多舱油箱惰化系统在整个飞行过程中,各舱油箱中最高燃油温度小于32℃,没有超过许用限制;对于直升机而言,由于油箱相比大型客机而言体积较小,通过计算可得,冷却空气控温的多舱油箱惰化系统的燃油代偿损失小于燃油热沉控温的多舱油箱惰化系统的燃油代偿损失。仿真结果为多舱油箱惰化系统的设计和优化提供了参考依据。

多元(U,Zr, Nb)C燃料制备技术与性能机理研究

多元(U,Zr, Nb)C燃料因具有熔点高、热导率高、低裂变气体释放率及优异的高温力学性能等优点,是目前大功率空间核推进反应堆选用燃料之一。本文采用碳热还原和液相烧结相结合的粉末冶金工艺制备多元(U,Zr, Nb)C燃料芯块,研究了工艺参数对烧结芯块反应动力学、相结构、导热性能和微观结构的作用机制和影响规律。结果表明:在1 800℃、50 MPa和1 h的烧结条件下,通过添加0.5%金属铀形成的液相烧结工艺制备得到芯块密度可达95.5%TD;当原料M/C(M为金属元素总量)摩尔比为1∶6.5时,可制备得到M/C比为1的正化学计量碳化物燃料;(U0.2,Zr, Nb)C的晶格常数比(U0.1,Zr, Nb)C的晶格常数略高;多元(U,Zr, Nb)C碳化物燃料芯块热导率与相成分、密度和温度均有关;芯块气孔分布较均匀,没有联通的开气孔存在,气孔尺寸在1~3μm。

核反应堆系统多维度多物理场耦合有限元分析研究

核反应堆系统庞杂且运行环境严苛,存在多物理场耦合的复杂现象。早期开发的多物理场耦合软件具有扩展性和通用性不足的缺点。因此,搭建多物理场耦合框架,针对耦合问题中的关键技术开展研究,对加快我国自主化多物理场耦合平台开发进程具有重要意义。本文介绍了西安交通大学核反应堆热工水力研究室开发的核反应堆多维度多物理场耦合有限元分析平台,主要包含热工流体计算模型的开发、燃料性能分析技术的研究以及多物理场耦合框架的建立等工作。在热工流体计算方面,开展了核反应堆系统两相流分析模型和液态金属快堆子通道分析模型研究,开发了系统分析程序NUSAC和子通道分析程序FLARE;在燃料性能分析技术方面,开展了包覆颗粒弥散燃料和板状燃料的性能分析研究,开发了针对多种燃料的燃料性能分析程序BEEs;在多物理场耦合分析方面,搭建了多物理场耦合框架,结合热工水力、中子物理和燃料性能分析程序,实现了核反应堆多物理场耦合的精细分析。本文搭建的核反应堆系统多维度多物理场耦合有限元分析平台可为核反应堆系统多维度多物理场耦合高保真数值模拟分析提供有力支持。

质子交换膜燃料电池多物理场建模及模型参数敏感性分析

受限于外部运行工况及内部多物理场参数的耦合作用机制,质子交换膜燃料电池的精确机理建模成为其研发和应用的瓶颈。该文通过探究燃料电池内部“电-热-流”多场耦合关系,构建准一维电堆动态模型,并基于单参数敏感性和多参数敏感性分析,得到不同模型参数的敏感度指标,完成了建模中部分关键参数的权重分析。为验证模型精度及耦合参数变动对输出特性的影响,在搭建Ballard NEXA 1.2 kW燃料电池测试平台的基础上开展变载及参数变动实验。结果表明,所构建的模型能够较为精确的模拟电堆特性,且对称因子、活化面积和压力系数的变动对电堆输出的影响较大。结果可为燃料电池电堆的测试及改型提供理论基础,并揭示电堆故障及老化过程中主要参数的衰退变化趋势。

螺旋金属燃料多物理耦合分析方法与概念设计研究

螺旋金属燃料具有导热系数高、导热路径短、强制旋流交混的特点,可实现更高的堆芯功率密度,进而减小堆芯体积,提高反应堆的安全性和经济性。本文介绍了上海交通大学反应堆热工水力实验室建立的螺旋金属燃料热工水力、中子物理、力学特性分析方法及多物理耦合分析框架。在热工水力方面,基于自研仪器实现了交混及沸腾临界行为精细化测量,建立了三维及精细化子通道分析方法;在中子物理方面,建立了适用于特殊能谱、复杂几何的截面及稳瞬态中子物理特性的分析方法;在力学方面,基于分子动力学方法建立了U-Zr合金燃料基础热物性模型,并开展了辐照条件下螺旋棒宏观力学特性研究。基于热工-物理-力学多物理分析和优化,提出了螺旋金属燃料组件及堆芯设计,具有无硼化、堆芯功率密度高、体积小、换料周期长的特点。

基于农机智能管理平台的田间燃油配给策略

在农业规模化生产中,为保证作业效率,农机燃油配给往往需要在田间完成。然而,现有的田间燃油配给方式存在不安全、不及时、缺乏科学系统的配给决策,导致燃油配给效率低、配送成本高等问题。针对上述问题,该研究结合农机燃油需求特点,提出基于农机智能管理平台的农机田间燃油配给策略。首先,以农机智能管理平台的实时数据为基础,基于可信性理论建立农机田间燃油配给的两阶段数学模型:第一阶段预优化,根据平台数据建立具有模糊需求和模糊时间窗的多目标车辆路径规划模型,第二阶段根据实际生产中发生的动态事件更新相关信息,重新规划未配送订单的配送路径;其次,以总配送成本最低及总满意度最高为目标,结合改进遗传算法求解农机田间燃油配给模型。最后,应用嫩江农场的数据进行实证分析,并与农场当前的配送成本等指标进行对比,验证可行性及实用性。结果表明:基于农机智能管理平台实时数据构建的农机田间燃油配给策略可以在降低配送成本的同时,保证较高的订单平均满意度,即时效性,与当前生产方案相比,配送路径减少了14条,虽然满意度较实际稍低,为72.85%,但总配送成本较当前方案降低了93.38%。研究结果可为农机田间燃油配给的智能化管理提供科学依据。

甲醇-柴油反应活性控制压燃发动机排放特性与经济性预测及优化

基于甲醇-柴油双燃料反应活性控制压燃(reactivity controlled compression ignition,RCCI)发动机台架试验数据,建立了基于粒子群算法(particle swarm optimization,PSO)优化BP神经网络的甲醇-柴油RCCI发动机排放特性、经济性预测智能模型,以发动机负荷、甲醇替代率、EGR率为输入参数,NO_(x)、烟度、CO、THC排放和当量有效燃油消耗率为输出,预测模型的决定系数(R^(2))分别为0.99,0.97,0.99,0.98和0.96,平均绝对百分比误差(mean absolute percentage error,MAPE)为6.46%,0.56%,3.12%,1.21%和0.3%,表明构建的PSO-BPNN模型能够有效预测甲醇-柴油RCCI发动机的NO_(x)、烟度、CO、THC排放和经济性。基于偏最小二乘回归(partial least squares regression,PLSR)分析了不同控制参数对发动机污染物排放和经济性的相关性,将PSO-BPNN预测模型与NSGA-Ⅱ算法相结合,以NO_(x)、烟度和当量有效燃油消耗率为目标对负荷、甲醇替代率和EGR率进行协同优化,将最优控制参数组合标定至双燃料发动机的控制系统进行试验验证。结果表明:优化后烟度变化不明显,NO_(x)排放平均降低39.6%,当量有效燃油消耗率平均降低2.6%。

基于多种群混沌遗传算法的GEO目标服务任务规划

面向地球同步轨道(geosynchronous Earth orbit,GEO)空间目标碎片清除、燃料加注等不同在轨服务需求,研究了“固定储油站+往返航天器”相结合的航天器任务规划问题。首先,建立了多任务混合的燃料最优双层任务规划模型,外层为目标服务序列规划,内层为轨道机动规划。随后,针对该连续-离散混合变量组合优化问题,提出了一种多种群混沌遗传算法(multi-group chaotic genetic algorithm,MGCGA),采用混合编码表征决策变量,引入立方混沌映射算子提高初始种群质量,多种群及精英保留策略使得算法在求解过程中能更为显著地逼近全局最优解。最后,参考实际GEO目标构建了典型算例,规划结果表明所提算法具有全局收敛性好、收敛速度快的优点。

燃料分级对贫预混多喷嘴燃烧器火焰动态响应特性影响的实验研究

贫预混多喷嘴燃料分级技术可以有效降低局部热负荷,从而降低NOx排放并拓宽工况范围,是现代重型燃气轮机低排放燃烧室的主要燃烧方式。本文开展了燃料分级及当量比变化对贫预混多喷嘴燃烧火焰动态响应的影响研究。利用扬声器产生火焰的受迫振荡,利用压力脉动传感器与光电倍增管完成了多喷嘴火焰响应特性的试验分析。试验表明,燃烧室内压力波动与热释放率波动随扰动频率同步变化。当量比低于0.53时,多喷嘴火焰传递函数呈现单峰的特征。当量比大于0.64时,多喷嘴火焰传递函数呈现双峰特征,且火焰响应增强。延迟时间τ随着当量比的增大而减小。燃料分级将使得火焰动态响应特征频率发生偏移。增加喷嘴数量使得火焰传递函数幅值上升,火焰响应增强,峰值频率增大,延迟时间偏短。对于采用多喷嘴燃料分级技术的燃烧室,负荷上升将导致火焰趋于不稳定。

燃料电池发动机系统多场耦合模型分析与温度控制方法

温度控制是实现燃料电池发动机快速响应、降低能耗与安全运行的保障,而电堆内部热量场与电化学场、流场相互影响,其耦合特性是温度控制的关键。以某中型燃料电池卡车为研究对象,构建“热-电-流”多场耦合模型,通过参数分析确立温度控制关键因素,设计模糊PID温度控制器,并通过多变工况验证控制效果。结果表明,通过所构建的模型能全面分析温度控制关键参数,所提出的控制器能有效提高响应速度,降低散热风扇转速和输出电压超调量,在设置的测试工况与NEDC工况下,温度的超调量分别降低了19.1%与1.64%。可为燃料电池发动机设计与控制提供基础,进一步推动大功率燃料电池的车载应用。

分壁精馏塔分离加氢裂化喷气燃料的设计与优化

分壁精馏塔(DWC)是一种典型的化工过程强化设备,具有节能和节约设备投资的优势,但在石油化工领域应用较少。基于加氢裂化喷气燃料实沸点蒸馏结果,以之分馏制备不同牌号轻质白油过程为研究对象,在传统分馏工艺(FP)的基础上提出了单隔壁分馏工艺(DWC-FP)和双隔壁分馏工艺(DPDWC-FP),并建立FP、DWC-FP和DPDWC-FP的严格稳态精馏模型;以年总成本(TAC)和再沸器负荷为目标函数,通过非支配排序遗传算法NSGA-Ⅱ优化工艺流程。结果表明,DWC在应用于石油馏分的分离过程中具有节能优势,DPDWC-FP工艺可在1个塔内实现4个产品的分离;与FP相比,DWC-FP和DPDWC-FP的TAC分别减少19.61%和24.09%。

基于Isight的增程式电动汽车定点控制策略优化

基于专家经验和工程经验制定的传统规则能量管理策略并不能适应当前增程式汽车复杂的行驶工况,为了更加精确地控制增程式汽车,使其获得更好的燃油经济性,考虑到增程器中发动机定点控制策略的发动机工作点切换规则影响,采用Cruise建立整车模型、Isight对其参数进行优化的方式探究发动机工作点切换规则对油耗的影响,比较其百公里油耗。研究结果表明,优化后NEDC工况、WLTC工况、混合工况的百公里燃油消耗量分别降低了3.51%、7.3%、8.5%,为增程式汽车定点控制策略优化提供了一种新方法,并验证了其可行性。

超音速火焰喷涂铁基非晶纳米晶涂层的工艺参数与性能试验

为了进一步深入研究铁基非晶涂层的制备和性能,利用人工神经网络和多因素多水平设计对超音速火焰喷涂技术制备的铁基非晶纳米晶涂层的工艺参数和性能进行了优化,以期对铁基非晶涂层的实际应用提供参考.多因素多水平试验通过设计分析方法和设计实验参数,建立神经网络模型,研究了煤油量、氧气量、送粉率和喷涂距离四项工艺参数对涂层孔隙率、硬度、结合强度和沉积效率的影响规律.采用扫描电镜、透射电镜等手段表征了粉末及涂层的显微结构和内部微观组织形貌;采用X射线衍射仪、同步热分析仪等设备对粉末和涂层成分、相组成和非晶程度进行了观察分析.验证了工艺参数优化过程的计算机模拟结果,确定了最佳喷涂工艺参数范围,进一步提升了涂层的性能.讨论了喷涂过程中孔隙形成的微观过程和非晶纳米晶对涂层性能的影响机理.研究表明各工艺参数对涂层性能是多因素互相影响的,理论上最佳喷涂工艺参数为煤油量23 L·h^(-1)、氧气量51 L·h^(-1)、送粉率72 g·min^(-1)、喷涂距离280 mm,制备出的铁基非晶涂层厚度约为270μm、孔隙率约为1.3%、结合强度约为84 MPa、硬度约为1110 HV_(0.3).涂层非晶程度在80%左右,纳米晶尺寸为3~5 nm,涂层在600℃以下不会发生晶化过程.

考虑坡度工况的混合动力系统多目标优化策略研究

为了优化上坡工况下的车辆性能,提出了一种考虑坡度工况的混合动力系统多目标优化策略。利用电机对转矩快速准确的响应特性,引入电机转矩优化系数作为控制变量,采用NSGA-Ⅱ算法实现平顺性与经济性的权衡优化。在Matlab/simulink平台上搭建整车模型,并在坡度工况下进行仿真试验,发现在坡度为5%的工况下,优化前的最大冲击度为19.6 m·s^(-3),优化后的最大冲击度为10.6 m·s^(-3),降低了45.91%;优化前的等效燃油消耗为0.5688 L,优化后的等效燃油消耗为0.6087 L,增加了7.01%。上述结果表明优化后的混合动力系统尽管经济性略有降低,但平顺性得到了大幅提高,验证了考虑坡度工况的混合动力系统多目标优化策略的有效性。