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RESEARCH PRODUCT
Using an Adaptive High-Gain Extended Kalman Filter With a Car Efficiency Model
Eric BusvelleNicolas BoizotJuergen SachauKenneth D. Sebestasubject
0209 industrial biotechnologyHigh-gain antennaEngineeringbusiness.industry020208 electrical & electronic engineering02 engineering and technologyKalman filterFilter (signal processing)Invariant extended Kalman filter[SPI.AUTO]Engineering Sciences [physics]/AutomaticExtended Kalman filter020901 industrial engineering & automationControl theoryEngine efficiency[ SPI.AUTO ] Engineering Sciences [physics]/Automatic0202 electrical engineering electronic engineering information engineeringFast Kalman filterObservabilitybusinessComputingMilieux_MISCELLANEOUSdescription
The authors apply the Adaptive High-Gain Extended Kalman Filter (AEKF) to the problem of estimating engine efficiency with data gathered from normal driving. The AEKF is an extension of the traditional Kalman Filter that allows the filter to be reactive to perturbations without sacrificing noise filtering. An observability normal form of the engine efficiency model is developed for the AEKF. The continuous-discrete AEKF is presented along with strategies for dealing with asynchronous data. Empiric test results are presented and contrasted with EKF-derived results.Copyright © 2010 by ASME
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2010-09-01 |