发明名称 |
Optimized tuner selection for engine performance estimation |
摘要 |
A methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine which seeks to minimize the theoretical mean-squared estimation error. Theoretical Kalman filter estimation error bias and variance values are derived at steady-state operating conditions, and the tuner selection routine is applied to minimize these values. The new methodology yields an improvement in on-line engine performance estimation accuracy.
|
申请公布号 |
US8386121(B1) |
申请公布日期 |
2013.02.26 |
申请号 |
US20100791907 |
申请日期 |
2010.06.02 |
申请人 |
THE UNITED STATES OF AMERICA AS REPRESENTED BY THE ADMINISTRATOR OF NATIONAL AERONAUTICS AND SPACE ADMINISTRATION;SIMON DONALD L.;GARG SANJAY |
发明人 |
SIMON DONALD L.;GARG SANJAY |
分类号 |
G01M17/00 |
主分类号 |
G01M17/00 |
代理机构 |
|
代理人 |
|
主权项 |
|
地址 |
|