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Development of propulsion control systems frequently involves large-scale transient simulations, e.g. Monte Carlo simulations or drive-cycle optimizations, which require fast dynamic plant models. Models of the air-path—for internal combustion engines or fuel cells—can exhibit stiff behavior, though, causing slow numerical simulations due to either using an implicit solver or sampling much faster than the bandwidth of interest to maintain stability. This paper proposes a method to reduce air-path model stiffness by adding an impedance in series with potentially stiff components, e.g. throttles, valves, compressors, and turbines, thereby allowing the use of a fast-explicit solver. An impedance, by electrical analogy, is a frequency-dependent resistance to flow, which is shaped to suppress the high-frequency dynamics causing air-path stiffness, while maintaining model accuracy in the bandwidth of interest.

Mean Value Engine Models (MVEMs) are simplified, dynamic engine models which are physically based. Such models are useful for control studies, for engine control system analysis and for model based engine control systems. Very few published MVEMs have included the effects of Exhaust Gas Recirculation (EGR). The purpose of this paper is to present a modified MVEM which includes EGR in a physical way. It has been tested using newly developed, very fast manifold pressure, manifold temperature, port and EGR mass flow sensors. Reasonable agreement has been obtained on an experiemental engine, mounted on a dynamometer.

Long term control of the AFR (Air/Fuel Ratio) of spark ignition engines is currently accomplished with a selvoscillating PI control loop. Because of the intake/exhaust time delay, the oscillation frequency and hence bandwidth of this loop is small. This paper describes a new approach to the design of this control loop using a novel observer system. In this way the bandwidth of this important loop is increased by a factor of 2 - 6 times, leading to more accurate overall AFR control. Moreover the observer approach is so robust and allows such feedback levels that it reduces significantly the accuracy required in the calibration of the base fuel control system with which it is be used. It can be used with either conventional- or advanced observer based- base fuel strategies.