Nonlinear observer-based exhaust manifold pressure estimation and fault detection for gasoline engines with exhaust gas recirculation

Abstract

This article presents a nonlinear observer-based method to estimate the exhaust manifold pressure for the gasoline engines equipped with an exhaust gas recirculation system. A dynamic model is designed to estimate the exhaust manifold pressure, which includes both the intake manifold and exhaust manifold dynamics focusing on gas mass flows. Based on the developed model, a nonlinear exhaust manifold pressure observer is proposed to replace the exhaust manifold pressure sensor, and the global convergence is analyzed by a constructed Lyapunov function and the physical meaning of the time-varying parameters. The experimental validations show that the observer-based exhaust manifold pressure estimator is able to converge to the real value at arbitrary initial value and estimates the exhaust manifold pressure accurately during both the steady-state and transient conditions. Finally, the proposed exhaust manifold pressure observer is applied into the fault detection problem for the exhaust gas recirculation system. The experimental validations show that the observer is able to be used to estimate the exhaust gas recirculation ratio and as an extra signal to assist to detect the faults of the exhaust gas recirculation system accurately.

Modeling of engine thermal dynamics and its application in energy management of HEVs considering engine warming-up

“…The management system of the coolant temperature is activated after the coolant temperature reaches the nominal temperature, and the excess heat is taken away by the circulating coolant. Additional details regarding the test bench can be found in Jiang and Shen and Gao et al 28,29…”

“…The management system of the coolant temperature is activated after the coolant temperature reaches the nominal temperature, and the excess heat is taken away by the circulating coolant. Additional details regarding the test bench can be found in Jiang and Shen and Gao et al 28,29 Model validation for engine thermal dynamics 5. The NMSE is 0.9881 for identification condition, and the NMSE is 0.9632 for validation condition.…”

Non-Singleton Type-3 Fuzzy Approach for Flowmeter Fault Detection: Experimental Study in a Gas Industry

“…The results are compared with filter-based and embedded-based methods, and it is shown that model identification by the suggested variable selection approach improves the FD performance. In [5], the fault of pressure sensors is studied, and a dynamic model is optimized to predict the pressure. In this paper, a pressure observe is designed to predict the sensor output, and the convergence is theoretically analyzed.…”