缸内直喷汽油机共轨系统结构参数优化

Structure parameters optimization of common rail system for gasoline direct injection engine

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。

To reduce the common rail pressure fluctuation and reduce the workload of experimental calibration of structure parameters for Gasoline Direct Injection （GDI） engine, a structure parameters optimization method of common rail system is proposed based on improved genetic algorithm. First, a model of GDI common rail system, including high-pressure pump, common rail pipe, injector and low- pressure pump, is developed in GT-suite environment. Second, the effects of common rail pipe volume and damping orifice diameter of the rail pressure fluctuation and rise-time are analyzed by dynamics, and the rationality of the model is verified. Finally, a control system of the common rail pressure is designed based on feedforward and feedback. On this basis, an improved genetic algorithm is used to optimize the damping orifice diameter and common rail pipe volume, considering the common rail pressure fluctuation and rise-time as the objective functions. Simulation results show the effectiveness of the proposed optimization method.