DAE and ODE Based EKF:s and their Real-Time Performance Evaluated on a Diesel Engine
(English)Manuscript (preprint) (Other academic)
When estimating states in engine control systems there are limitations on the computational capabilities.This becomes especially apparent when designingobservers for stiff systems since the implementation requires small step lengths. One way to reduce the computational burden, is to reduce the model stiffness by approximating the fast dynamics with instantaneous relations, transformingan ODE model into a DAE model.
Performance and sample frequency limitations for extended Kalman filters based on both the original ODE model and the reduced DAE model for a diesel engine is analyzed and compared. The effect of using backward Euler instead of forward Euler when discretizing the continuous time model is analyzed.
The ideas are evaluated using measurement data from a diesel engine.The engine is equipped with throttle, EGR, and VGT and the stiff model dynamics arise as a consequence of the throttle between two control volumes in the air intake system. It is shown that even though the ODE, for each time-update, is less computationally demanding than the resulting DAE, an EKF based on the DAE model achieves better estimation performance than one based on the ODE with less computational effort. The main gain with the DAE based EKF is that it allows increased step lengths without degrading the estimation performance compared to the ODE based EKF.
Engineering and Technology
IdentifiersURN: urn:nbn:se:liu:diva-67596OAI: oai:DiVA.org:liu-67596DiVA: diva2:411486