Enzhe Song

Identification and quantification analysis of nonlinear dynamics properties of combustion instability in a diesel engine

The cycling combustion instabilities in a diesel engine have been analyzed based on chaos theory. The objective was to investigate the dynamical characteristics of combustion in diesel engine. In this study, experiments were performed under the entire operating range of a diesel engine (the engine speed was changed from 600 to 1400 rpm and the engine load rate was from 0% to 100%), and acquired real-time series of in-cylinder combustion pressure using a piezoelectric transducer installed on the cylinder head. Several methods were applied to identify and quantitatively analyze the combustion process complexity in the diesel engine including delay-coordinate embedding, recurrence plot (RP), Recurrence Quantification Analysis, correlation dimension (CD), and the largest Lyapunov exponent (LLE) estimation. The results show that the combustion process exhibits some determinism. If LLE is positive, then the combustion system has a fractal dimension and CD is no more than 1.6 and within the diesel engine operating range. We have concluded that the combustion system of diesel engine is a low-dimensional chaotic system and the maximum values of CD and LLE occur at the lowest engine speed and load. This means that combustion system is more complex and sensitive to initial conditions and that poor combustion quality leads to the decrease of fuel economy and the increase of exhaust emissions.

Investigation on the fuel injection quantity fluctuation of a common-rail fuel injection system using response surface methodology:

Variations in the parameters affect the injection characteristics of a common-rail injection system and leads to fluctuation in the fuel injection quantity. This paper is aimed at combining the numerical modelling and design of experiments to investigate the significant effects of the interactions between the common-rail injector parameters on the fluctuation in the fuel injection quantity using response surface methodology. A numerical model of a common-rail injector was developed. The model was validated by comparing simulation results with experimental measurements, which showed that it can accurately predict the fuel injection quantity of the system. The design of experiments was performed using a two-level five-factor D-optimal design. The factors studied were the pre-tension of the control valve spring, the diameter of the outlet orifice, the diameter of the inlet orifice, the needle lift and the diameter of the nozzle holes. A quadratic response surface model was suggested by means of partial least-squares regression analysis. The distribution of the standardized residuals, the relation between the predicted fluctuation and the observed fluctuation in the fuel injection quantity, the coefficient R2 of determination and the adjusted coefficient R adj 2 of determination for the response surface model were analysed, which demonstrated the significance of the model. Analysis of the F value and the p value for the model terms at the 95% confidence level revealed that the interactions between the control valve spring pre-tension and the nozzle hole diameter, between the outlet orifice diameter and the nozzle hole diameter, between the inlet orifice diameter and the nozzle hole diameter and between the needle lift and the nozzle hole diameter had significant effects on the fluctuation in the fuel injection quantity of the system. Furthermore, the significant effects of the interactions between these parameters were analysed in detail.

Nonlinear Modeling and Analysis of Pressure Wave inside CEUP Fuel Pipeline

Operating conditions dependent large pressure variations are one of the working characteristics of combination electronic unit pump (CEUP) fuel injection system for diesel engines. We propose a precise and accurate nonlinear numerical model of pressure inside HP fuel pipeline of CEUP using wave equation (WE) including both viscous and frequency dependent frictions. We have proved that developed hyperbolic approximation gives more realistic description of pressure wave as compared to classical viscous damped wave equation. Frictional effects of various frequencies on pressure wave have been averaged out across valid frequencies to represent the combined effect of all frequencies on pressure wave. Dynamic variations of key fuel properties including density, acoustic wave speed, and bulk modulus with varying pressures have also been incorporated. Based on developed model we present analysis on effect of fuel pipeline length on pressure wave propagation and variation of key fuel properties with both conventional diesel and alternate fuel rapeseed methyl ester (RME) for CEUP pipeline.

Investigation on Electromagnetic Models of High-Speed Solenoid Valve for Common Rail Injector

A novel formula easily applied with high precision is proposed in this paper to fit the - curve of soft magnetic materials, and it is validated by comparison with predicted and experimental results. It can accurately describe the nonlinear magnetization process and magnetic saturation characteristics of soft magnetic materials. Based on the electromagnetic transient coupling principle, an electromagnetic mathematical model of a high-speed solenoid valve (HSV) is developed in Fortran language that takes the saturation phenomena of the electromagnetic force into consideration. The accuracy of the model is validated by the comparison of the simulated and experimental static electromagnetic forces. Through experiment, it is concluded that the increase of the drive current is conducive to improving the electromagnetic energy conversion efficiency of the HSV at a low drive current, but it has little effect at a high drive current. Through simulation, it is discovered that the electromagnetic energy conversion characteristics of the HSV are affected by the drive current and the total reluctance, consisting of the gap reluctance and the reluctance of the iron core and armature soft magnetic materials. These two influence factors, within the scope of the different drive currents, have different contribution rates to the electromagnetic energy conversion efficiency.

Study of Nonlinear Characteristics and Model Based Control for Proportional Electromagnet

The nonlinear characteristics of proportional electromagnet caused by hysteresis bring great difficulties on its accurate position tracking control by current. In order to enhance the practicability and reliability of long stroke electromagnet in case of position sensor fault and improve the position tracking performance during current closed-loop control, experimental investigations on the electromagnet actuator hysteresis characteristics of diesel engine governor are carried out to analyze the system dynamic features and the effects of hysteresis on actuator position tracking performance. It is clear that hysteresis can significantly hinder the accurate position control of the electromagnet actuator. Consequently, the fuel injection will be delayed, which will lead to hysteresis of engine speed control as well as deterioration of engine performance. In this paper, the hysteresis phenomenon of an actuator and its influence on control performance of engine are investigated. The model of proportional electromagnet actuator (PEA) is established and the hysteresis principle is analyzed. Then the inverse model control strategy based on neural network (NN) is proposed to linearize the transfer behavior of electromagnet and compensate for the magnet hysteresis. Rapid control prototyping (RCP) experiment based on MicroAutoBox is further implemented to validate the real-time performance of the proposed control strategy in D6114 diesel engine. The results show that the speed fluctuation (SF) under steady-state conditions (especially under idle speed condition) and the recovery time as well as the overshoot under transient conditions are significantly improved. This makes it possible to develop redundant electromagnet driving control strategy.

Influential factors’ correlation analysis upon common rail system fuel injection quantity for diesel engines

The coherence of the fuel injection quantity determines the working stability of the common rail system. The variations in the parameters of the common rail injector have significant influence on coherence of the fuel injection quantity of the system. The bond graphs for the main components of the common rail injector were proposed, respectively, based on the bond graph methodology in this article. The fuel injection quantities of the system at different rail pressures and injection pulse widths had been obtained by numerically solving and programming the obtained state equations in MATLAB. The predicted results of the fuel injection quantity by the model are in excellent agreement with the experimental measurements which were obtained from a test bench. Through the correlation analysis of the influential factors on the fuel injection quantity, the correlation coefficients between the fuel injection quantity and the single influential factor and quadratic influential factor at different rail pressures and injection pulse widths were obtained, respectively. Moreover, the variation characteristics of correlation between the fuel injection quantity and its influential factors had been analyzed in detail. The results show that the nozzle hole diameter and the inlet orifice diameter are the main influential factors on the fuel injection quantity among the selected parameters. The quadratic factors under the action of the parameter itself and the quadratic factors under the interaction between the delivery chamber diameter and nozzle hole diameter, needle seat semi-angle and needle cone semi-angle, nozzle hole diameter and inlet orifice diameter and inlet orifice diameter and outlet orifice diameter have significant effect on the fuel injection quantity, and they are the main influential factors on the fuel injection quantity among the quadratic factors.

Fuel Injection Quantity Fluctuation Prediction of Common Rail System Based on Bond Graph Model

Common rail injection system (CRIS) is an advanced technology which meets the stringent emission standards of diesel engines and satisfies consumer demand for better fuel efficiency and increased power. The coherence of fuel injection quantity is the key injection characteristic for CRIS to match diesel engines successfully. As a critical component for CRIS, the variation of injector characteristic parameters has significant influence on the coherence of fuel injection quantity of the system. In this paper, combining numerical modeling and design of experiments, the response predicted relation between fuel injection quantity fluctuation of CRIS and its influence factors had been investigated. A numerical model of common rail injector was presented for the purpose of creating a tool for simulation experiments. The model is developed using power bond graph method, which is a modeling method that has shown its superiority in modeling systems consisting of sub-models from several energy domains in a unified approach. Experiments were conducted at the same model conditions to validate the model. The results are quite encouraging and in agreement with model predictions, which imply that the model can accurately predict the fuel injection quantity of CRIS and it can be used to simulation and design experiments. Experiments were designed using D-optimal method in which the characteristic parameters of common rail injector were chosen as design factors and the fuel injection quantity fluctuation was selected as the response. The fuel injection quantity fluctuation responses at different design factor levels were obtained using the developed numerical model which had been validated. A regressive prediction model of fuel injection quantity fluctuation was suggested according to the simulation experiments by means of partial least-squares regression (PLR) analysis. Analysis of variance, normal distribution of standardized residuals and relation between observed and predicted fuel injection quantity fluctuation for the regressive prediction model were analyzed which demonstrate the favorable goodness of fit and significance of the regressive model to predict fuel injection quantity fluctuation of the system. By changing design factor levels, the comparisons between numerical results of the bond graph model and the predicted fuel injection quantity fluctuation of the regressive prediction model were conducted. Results show that the regressive prediction model can reliably predict the fuel injection quantity fluctuation caused by the variation of characteristic parameters of common rail injector. Research results of this paper can provide novel ideas to predict fuel injection quantity fluctuation and a theoretical guidance for design and parameters optimization of CRIS.Copyright