Research on Multi-Parameter Interaction Influence Law and Multi-Objective Optimization of Common Rail Injector 2021-01-0545

In order to improve the injection performance of high pressure common rail fuel system and optimize the design of electronic control injector more effectively, the simulation model of high pressure common rail fuel system was built by using AMESim simulation platform, and the accuracy of the simulation model was verified by comparing with the experimental data. In this paper, the needle opening response, needle closing response and cycle fuel injection were used as performance evaluation indicators, the AMESim model was used to carry out quantitative analysis of evaluation indicators. Through quantitative analysis, the key characteristic parameters are identified and those are solenoid valve preload, control valve stem lift, control cavity oil inlet orifice diameter, control cavity oil outlet orifice diameter, needle lift and nozzle diameter. Combining the optimal Latin hypercube experimental design and the least squares regression method, the corresponding multivariate binomial response surface prediction models were obtained. Among them, the R-squared values of the prediction models are 0.9993, 0.9967 and 0.9996 respectively, indicating the effectiveness of the models. At the same time, the correlation between various characteristic parameters and their interactions with cycle fuel injection, needle opening response and needle closing response were revealed. On this basis, the NSGA-II algorithm was used for multi-objective optimization, the shape of the parato was obtained and the final solution was determined. The optimization results show that under the condition of rail pressure 160MPa, fuel injection pulse width 1.2ms, the needle opening response and needle closing response are improved by 21.78% and 7.38% respectively, and the cycle fuel injection is increased by 10.07%; Under the other working conditions, the optimized structure still improve the system performance.