基于信息融合的汽油机过渡工况进气流量预测方法  

A Forecast Method of Gasoline Engine Air Induction under Transient Condition Based on Information Fusion

作　　者：吴义虎[1] 宫唤春[1] 侯志祥[1] 袁翔[1] 

机构地区：[1]长沙理工大学

出　　处：《汽车技术》2007年第8期50-54,共5页Automobile Technology

基　　金：国家自然科学基金资助项目(50276005)。

摘　　要：在分析汽油机过渡工况下各种影响进气流量因素的基础上,提出了一种基于信息融合的进气流量预测方法。通过该方法提取了汽油机过渡工况的动态特征参数信息,建立了进气流量神经网络预测模型,并以车用汽油机加、减速工况实测数据为样本进行了仿真研究,结果表明,该方法能够准确地实时预测汽油机过渡工况的进气流量,同时能够消除空气流量传感器的滞后特性。A method of airflow forecast based on information fusion and different influence analysis on airflow under transient condition is presented in this paper.The dynamic characteristic information under transient conditions axe extracted by this method,the neural network forecast model of airflow is established, and the simulation research is carried out based on the real measuring data under gasoline engine acceleration and deceleration conditions,the results show that this method can accurately forecast induction airflow under gasoline engine transient condition,and eliminate the lagging characteristic of the airflow sensor at the same time.

关 键 词：汽油机 过渡工况 进气流量 预测 

分 类 号：U467.4[机械工程—车辆工程]