Erik Höckerdal

Air Mass-Flow Measurement and Estimation in Diesel Engines Equipped with GR and VGT

With stricter emission legislations and customer demands on low fuel consumption, good control strategies are necessary. This may involve control of variables that are hard, or even impossible, to measure with real physical sensors. By applying estimators or observers, these variables can be made available. The quality of a real sensor is determined by e.g. accuracy, drift and aging, but assessing the quality of an estimator is a more subtle task. An estimator is the result of a design work and hence, connected to factors like application, model, control error and robustness.The air mass-flow in a diesel engine is a very important quantity that has a direct impact on many control and diagnosis functions. The quality of the air mass-flow sensor in a diesel engine is analyzed with respect to day-to-day variations, aging, and differences in engine configurations. The investigation highlights the necessity of continuous monitoring and adaption of the air mass-flow. One way to do this is to use an estimator. Nine estimators are designed for estimation of the air mass-flow with the aim of assessing different quality measures. In the study of the estimators and quality measures it is evident that model accuracy is important and that special care has to be taken, regarding what quality measure to use, when the estimator performance is evaluated.

Model Based Engine Map Adaptation Using EKF

Abstract A method for online map adaptation is developed. The method utilizes the EKF as a parameter estimator and handles parameter aging, operating point dependent model and measurement quality. Map adaptation, by construction, gives marginally stable models with locally unobservable modes, that are handled. The method is also suitable for offline calibration of maps where the only requirement of the data is that the entire operating region of the system is covered. The method is applied to a truck engine where an air mass-flow sensor adaptation map is estimated based on data from a diesel engine during an ETC. It is shown that an adaptation map can be found in a measurement sequence not specially designed for adaptation.

Off- and On-Line Identification of Maps Applied to the Gas Path in Diesel Engines

Maps or look-up tables are frequently used in engine control systems, and can be of dimension one or higher. Their use is often to describe stationary phenomena such as sensor characteristics or engine performance parameters like volumetric efficiency. Aging can slowly change the behavior, which can be manifested as a bias, and it can be necessary to adapt the maps. Methods for bias compensation and on-line map adaptation using extended Kalman filters are investigated and discussed. Key properties of the approach are ways of handling component aging, varying measurement quality, as well as operating point dependent model quality. Handling covariance growth on locally unobservable modes, which is an inherent property of the map adaptation problem, is also important and this is solved for the Kalman filter. The method is applicable to off-line calibration of maps where the only requirement of the data is that the entire operating region of the system is covered, i.e. no special calibration cycles are required. Two truck engine applications are evaluated, one where a 1-D air mass-flow sensor adaptation map is estimated, and one where a 2-D volumetric efficiency map is adapted, both during a European transient cycle. An evaluation on experimental data shows that the method estimates a map, describing the sensor error, on a measurement sequence not specially designed for adaptation.

Observer Design and Model Augmentation for Bias Compensation Applied to an Engine

Abstract A systematic design method for reducing bias in observers is developed. The method utilizes an observable default model of the system together with measurement data from the real system and estimates a model augmentation. The augmented model is then used to design an observer which reduces the estimation bias compared to a default observer. A key result is the theoretical analysis that characterizes the possible augmentations is also conducted. The method is applied to a truck engine where the resulting augmented observer reduces the estimation bias with 50% in an ETC.

Bias reduction in DAE estimators by model augmentation: Observability analysis and experimental evaluation

A method for bias compensation in model based estimation utilizing model augmentation is developed. Based on a default model, that suffers from stationary errors, and measurements from the system a low order augmentation is estimated. The method handles models described by differential algebraic equations and the main contributions are necessary and sufficient conditions for the preservation of the observability properties of the default model during the augmentation.

Real-time performance of DAE and ODE based estimators evaluated on a diesel engine

Computation and sampling time requirements for real-time implementation of observers is studied. A common procedure for state estimation and observer design is to have a system model in continuous time that is converted to sampled time with Euler forward method and then the observer is designed and implemented in sampled time in the real time system. When considering state estimation in real time control systems for production there are often limited computational resources. This becomes especially apparent when designing observers for stiff systems since the discretized implementation requires small step lengths to ensure stability. One way to reduce the computational burden, is to reduce the model stiffness by approximating the fast dynamics with instantaneous relations, transforming an ordinary differential equations (ODE) model into a differential algebraic equation (DAE) model. Performance and sampling frequency limitations for extended Kalman filter (EKF)’s based on both the original ODE model and the reduced DAE model are here analyzed and compared for an industrial system. Furthermore, the effect of using backward Euler instead of forward Euler when discretizing the continuous time model is also analyzed. The ideas are evaluated using measurement data from a diesel engine. The engine is equipped with throttle, exhaust gas recirculation (EGR), and variable geometry turbines (VGT) and the stiff model dynamics arise as a consequence of the throttle between two control volumes in the air intake system. The process of simplifying and modifying the stiff ODE model to a DAE model is also discussed. The analysis of the computational effort shows 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.

Cylinder Pressure Based Cylinder Charge Estimation in Diesel Engines with Dual Independent Variable Valve Timing

With stricter emission legislations and demands on low fuel consumption, new engine technologies are continuously investigated. At the same time the accuracy in the over all engine control and diag ...