New 0D/1D Physical Approach for Modelling the Gas Dynamics Behavior Inside the Intake System of an Engine

作     者：David CHALET Mohamad YASSINE Jérome MIGAUD 

作者机构：Ecole Centrale de Nantes LHEEA lab. (ECN/CNRS) Nantes France MANN+HUMMEL France Laval France 

出 版 物：《Journal of Thermal Science》 (热科学学报（英文版）)

年 卷 期：2018年第27卷第4期

页      面：394-403页

核心收录：

学科分类：080704[工学-流体机械及工程] 08[工学] 0807[工学-动力工程及工程热物理] 

基　　金：article is done in a joined International Teaching and Research Chair entitled “Innovative Intake and Thermo-management Systems” between MANN+HUMMEL and Ecole Centrale de Nantes 

主　　题：gas dynamics compressible flow transfer function accuracy simulation time engine 

摘      要：The competition among carmakers to introduce the most innovative solutions is growing day by day. Since few years, simulation is being used widely in automotive industries. Instead of building costly prototypes and expending fuel for doing tests on a real engine, simulation became a good solution before taking new decisions. Concerning the study of gas dynamics and pressure wave s propagation in the intake system of an internal combustion engine, a precise modelling is needed in order to obtain good results. Unfortunately, the computational time for these simulations is considered as high compared to the real time. The main objective of the new approach presented in this paper, is to reduce simulation time of models in the internal combustion engine simulation code, allowing them to accomplish many engine simulations faster than one-dimensional non-linear approach. A transfer function is defined to link directly the relative pressure and the air mass flow rate. In a second time, the model is included into an internal combustion engine simulation code. The results obtained with this code are compared to experimental ones which are measured on a one-cylinder engine test bench. A good agreement is obtained between the experimental results and the numerical one. The model was improved by adding a transfer function for temperature evolution. The convergence time is then reduced as well as the global simulation time of the model.