直喷式柴油机燃烧压力振荡研究

利用燃烧理论、波动理论、有限元理论，研究直喷式柴油机燃烧压力振荡特性．研究表明，直喷式柴油机燃烧压力振荡具有多阶共振频率，实机缸内燃烧压力振荡是多个共振模态的叠加．经试验验证，本文计算结果与试验吻合较好．     

喷油器参数对柴油机性能的影响分析

在大量实验研究的基础上，分析了不同结构参数的孔式喷油器对直喷式柴油机性能的影响，同时分析了喷孔孔径，惯量对喷油、运转及燃烧过程的影响，可为喷油器参数与柴油机的合理匹配提供参考。     

柴油机活塞环组-缸套润滑状态和摩擦功耗的分析方法和应用(英文)

本文研究了表面粗糙度对柴油机活塞环—缸套摩擦副润滑性能的影响。文中考虑了温度效应,从而克服了以往分析这类问题的数学模型所存在的缺陷。此外,文中还介绍了本文作者在S195柴油机内按装的测量油膜厚度的遥测新方法。测量结果和分析计算结果一致。最后,文中还定量地给出了S195柴油机活塞环组摩擦功耗的大小。     

钢壳陶瓷排气道气缸盖中试关键技术研究与应用

介绍钢壳陶瓷涂层排气道气缸盖部分中试关键技术研究结果：2mm厚薄壁异形钢壳模具CAD／CAM，钢壳和气缸盖的铸造工艺，BF8L513风冷增压柴油机装用该种气缸盖后功率提高9．4％（油量增加9．4％），最大扭矩与原机缸盖相同，缸盖平均温度在标定工况时降低5．6℃，最大扭矩工况时降低1．9℃，该种气缸盖顺利通过1000h全速全负荷可靠性试验，500h变工况热冲击可靠性试验和50000km装车道路试验，已达到整机使用的可靠性要求，研制的工装设备超过年产4000件该种气缸盖的能力。     

复合陶瓷强化技术在柴油机气门上的应用

对柴油机进排气门表面进行复合陶瓷强化处理,可以提高气门耐磨性、耐高温和抗氧化腐蚀能力,大幅度延长气门的使用寿命,减少故障发生.本文介绍了复合陶瓷气门的性能特点、工艺加工过程及应用效果.     

通过柴油机性能参数确定示功图方法的研究

提出一种利用柴油机性能参数，如柴油机功率，爆发压力等，计算其示功图以及放热率的新方法，该方法是利用双韦贝函数替代柴油机放热规律，以模拟计算出的爆发压力和功率与实测值最接近为目标函数最优选取双韦贝函数中的五个常数，然后利用优选出的结果进行柴油机工程过程计算，从而得出示功图，算例分析表明，采用上述方法计算出的示功图与实测示范图吻合。     

用于标定和优化的高压共轨柴油机建模

高压共轨柴油机可控燃油喷射参数的增加,在使对燃烧的控制更加灵活的同时也带来标定和优化工作量显著增加的问题.为适应高效率的需要,提出并研究了基于模型的标定优化,即采用神经网络在一些工况点上建立模型,再通过自适应神经模糊推理系统(ANFIS)进行插值,将模型由这些工况点扩展到所需工况空间.模型精度由对象、建模所用数据量及模型参数调整共同决定.试验在一台六缸高压共轨柴油机上进行.理论分析和试验结果表明 该方法可以在保证精度的同时有效减少标定优化的试验工作量.     

Study of CNG／diesel dual fuel engine＇s emissions by means of RBF neural network

Great efforts have been made to resolve the serious environmental pollution and inevitable declining of energy resources. A review of Chinese fuel reserves and engine technology showed that compressed natural gas (CNG)/diesel dual fuel engine (DFE) was one of the best solutions for the above problems at present. In order to study and improve the emission performance of CNG/diesel DFE, an emission model for DFE based on radial basis function (RBF) neural network was developed which was a black-box input-output training data model not require priori knowledge. The RBF centers and the connected weights could be selected automatically according to the distribution of the training data in input-output space and the given approximating error. Studies showed that the predicted results accorded well with the experimental data over a large range of operating conditions from low load to high load. The developed emissions model based on the RBF neural network could be used to successfully predict and optimize the emissions performance of DFE. And the effect of the DFE main performance parameters, such as rotation speed, load, pilot quantity and injection timing, were also predicted by means of this model. In resum6, an emission prediction model for CNG/diesel DFE based on RBF neural network was built for analyzing the effect of the main performance parameters on the CO, NOx emissions of DFE. The predicted results agreed quite well with the traditional emissions model, which indicated that the model had certain application value, although it still has some limitations, because of its high dependence on the quantity of the experimental sample data.     

Simultaneously catalytic removal of NO<Subscript><Emphasis Type="Italic">x</Emphasis></Subscript> and particulate matter on diesel particulate filter

Diesel engines combine a high fuel economy with high durability and low maintenance costs and are, there-fore, used on a large scale for transportation purposes.However, the environmental pollution by diesel-engine exhausts has become more and more serious in the lastdecade, and currently the regulation of diesel emissions becomes tightened especially with respect to nitrogen ox-ides (NOx) and particulate matters (PM). Since the reduc-tion of both NOx and PM to the admitted level cannot be …