为了降低缸内直喷汽油(Gasoline direct injection,GDI)发动机共轨系统的轨压波动,同时减少共轨系统结构参数实验标定的工作量,提出了基于改进型遗传算法的共轨系统结构参数优化设计方法。首先,在GT-suite搭建了GDI共轨系统模型,该模型...为了降低缸内直喷汽油(Gasoline direct injection,GDI)发动机共轨系统的轨压波动,同时减少共轨系统结构参数实验标定的工作量,提出了基于改进型遗传算法的共轨系统结构参数优化设计方法。首先,在GT-suite搭建了GDI共轨系统模型,该模型主要由高压泵模型、共轨管模型、喷油器模型及低压泵模型组成;其次,通过动力学特性分析了共轨管体积、阻尼孔直径对共轨压力波动及上升时间的影响,并验证了模型的合理性;然后设计了基于前馈和反馈相结合的共轨压力控制系统,在此基础上,以共轨压力波动及上升时间为目标函数,以阻尼孔直径和共轨管体积为优化变量,提出了基于改进型遗传算法的共轨系统多结构参数优化方法;最后,通过仿真实验验证了本文方法的有效性。展开更多
Production optimal control technologies have become important tools for efficiently developing oil and gas reservoirs in recent years.This paper presents an overview of the research and application of these technologi...Production optimal control technologies have become important tools for efficiently developing oil and gas reservoirs in recent years.This paper presents an overview of the research and application of these technologies in smart oilfield,including reservoir data matching and prediction,well production optimization,and automatic well monitoring and control technologies.With the support of the National Natural Science Foundation of China,we made years of effort and finally derived a novel data—driven reservoir data matching and prediction methods.Besides,the new automatic optimization technologies and flow monitoring and control devices were also presented.The proposed technologies helped improve the computational efficiency by hundreds of times compared to traditional technologies.The real-time optimization and control of the injection and production parameters was realized using the proposed technologies,which have been widely applied in actual reservoirs at home and abroad,achieving significant economic benefits.展开更多
文摘为了降低缸内直喷汽油(Gasoline direct injection,GDI)发动机共轨系统的轨压波动,同时减少共轨系统结构参数实验标定的工作量,提出了基于改进型遗传算法的共轨系统结构参数优化设计方法。首先,在GT-suite搭建了GDI共轨系统模型,该模型主要由高压泵模型、共轨管模型、喷油器模型及低压泵模型组成;其次,通过动力学特性分析了共轨管体积、阻尼孔直径对共轨压力波动及上升时间的影响,并验证了模型的合理性;然后设计了基于前馈和反馈相结合的共轨压力控制系统,在此基础上,以共轨压力波动及上升时间为目标函数,以阻尼孔直径和共轨管体积为优化变量,提出了基于改进型遗传算法的共轨系统多结构参数优化方法;最后,通过仿真实验验证了本文方法的有效性。
基金the National Natural Science Foundation of China(Grant Nos.51344003,51674039,51874044,51922007,and 51604035)the National Science and Technology Major Project of China(Grant No.2016ZX05014).
文摘Production optimal control technologies have become important tools for efficiently developing oil and gas reservoirs in recent years.This paper presents an overview of the research and application of these technologies in smart oilfield,including reservoir data matching and prediction,well production optimization,and automatic well monitoring and control technologies.With the support of the National Natural Science Foundation of China,we made years of effort and finally derived a novel data—driven reservoir data matching and prediction methods.Besides,the new automatic optimization technologies and flow monitoring and control devices were also presented.The proposed technologies helped improve the computational efficiency by hundreds of times compared to traditional technologies.The real-time optimization and control of the injection and production parameters was realized using the proposed technologies,which have been widely applied in actual reservoirs at home and abroad,achieving significant economic benefits.
