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.

Comparison between gradient based UCODE2005 and the ensemble Kalman Filter for transient groundwater flow inverse modeling

Gradient based UCODE_2005 and data assimilation based on the Ensemble Kalman Filter(EnKF) are two different inverse methods. A synthetic two-dimensional flow case with four no-flow boundaries is used to compare the UCODE_2005 with the Ensemble Kalman Filter(EnKF) for their efficiency to inversely calculate and calibrate a hydraulic conductivity field based on hydraulic head data. A zonal, random heterogeneous conductivity field is calibrated by assimilating the time series of heads observed in monitoring wells. The study results indicate that the two inverse methods, UCODE_2005 and EnKF, could be used to calibrate the hydraulic conductivity field to a certain degree. More available observations and information about the conductivity field, more accurate inverse results will be obtained for the UCODE_2005. On the other hand, for a realistic zonal heterogeneous hydraulic conductivity field, EnKF can only efficiently determine the hydraulic conductivity field at the first several assimilated time steps. The results obtained by the UCODE_2005 look better than those by the EnKF. This is possibly due to the fact that the UCODE_2005 uses observed head data at every time step, while EnKF can only use observed heads at first several steps due to the filter divergence problem.