Optimal estimation of injection rate for high-pressure common rail system using the extended Kalman filter

被引：9

作者：

Fei, Hongzi ^{[1
]}

Liu, Bingxin ^{[1
]}

Wang, Liuping ^{[2
]}

Fan, Liyun ^{[1
]}

机构：

[1] Harbin Engn Univ, Coll Power & Energy Engn, Harbin 150001, Peoples R China

[2] RMIT Univ, Sch Engn, Melbourne, Vic 3000, Australia

来源：

MEASUREMENT | 2023年 / 220卷

基金：

中国国家自然科学基金;

关键词：

High-pressure common rail; Rail pressure; Injection rate; extended Kalman filter; Optimal estimation; PERFORMANCE; EMISSIONS; MASS;

D O I：

10.1016/j.measurement.2023.113385

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

This paper presents an innovative estimation method of the fuel injection rate based on the rail pressure measurement signal for a high-pressure common rail system. A dynamic mathematical model of the injection process is constructed. To meet the requirement of the estimator design, a nonlinear state space model with three state variables is derived. On this basis, an optimal estimation method for the injection rate is proposed based on the extended Kalman filter, and the impact of noise covariance matrices is thoroughly examined. The results demonstrate that the proposed method enables fast convergence of the estimated injection rate. The coefficient R2 values between the estimated and the actual injection rate curves exceed 94%, and the estimated errors of the injection volume are within 5%.

引用

页数：11

共 23 条

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