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Simscape is a physical modeling language developed by Mathworks Inc. The language uses equation statements instead of assignment statements to describe physical systems. The paper focuses on the Simscape language itself instead of using components in the Simscape libraries. The language will be introduced from a perspective different from the Mathworks' Physical Network point of view. Our perspective focuses on two types of variables at the connectors. In additional, internal variables are not separated into through and across variables. The alternative perspective is more general and easier to understand. The paper also illustrates how to develop components in a powertrain library following the proposed new perspective.

An iterative learning control (ILC) algorithm has been developed for a test cell electro-hydraulic, fully flexible valve actuation system to track valve lift profile under steady-state and transient operation. A dynamic model of the plant was obtained from experimental data to design and verify the ILC algorithm. The ILC is implemented in a prototype controller. The learned control input for two different lift profiles can be used for engine transient tests. Simulation and bench test are conducted to verify the effectiveness and robustness of this approach. The simple structure of the ILC in implementation and low cost in computation are other crucial factors to recommend the ILC. It does not totally depend on the system model during the design procedure. Therefore, it has relatively higher robustness to perturbation and modeling errors than other control methods for repetitive tasks.

Fully Flexible Valve Actuation (FFVA) systems provide maximum flexibility to adjust lift profiles of engine intake and exhaust valves. A research grade electro-hydraulic servo valve based FFVA system was designed to be used with an engine in a test cell to precisely follow desired lift profiles. Repetitive control was chosen as the control strategy. Crank angle instead of time is used to trigger execution to ensure repeatability. A single control is used for different engine speeds even though the period for one revolution changes with engine speeds. The paper also discusses lift profile extension, instantaneous lift profile switching capability and built-in safety features.

General Motors recently demonstrated two driveable test vehicles powered by a Homogeneous Charge Compression Ignition (HCCI) engine. HCCI combustion has the potential of a significant fuel economy benefit with reduced after-treatment cost. However, the biggest challenge of realizing HCCI in vehicle applications is controlling the combustion process. Without a direct trigger mechanism for HCCI's flameless combustion, the in-cylinder mixture composition and temperature must be tightly controlled in order to achieve robust HCCI combustion. The control architecture and strategy that was implemented in the demo vehicles is presented in this paper. Both demo vehicles, one with automatic transmission and the other one with manual transmission, are powered by a 2.2-liter HCCI engine that features a central direct-injection system, variable valve lift on both intake and exhaust valves, dual electric camshaft phasers and individual cylinder pressure transducers.

Object-oriented or component-based modeling greatly facilitates model development for large and complex multi-domain physical systems. It uses predefined and reusable component models. Connections between component models represent actual physical connections. Non-physical connections are not needed. Therefore, the model is much easier to be understood and used by general model users. The purpose of this paper is to demonstrate that object-oriented modeling is very suitable for mean-value engine models. Models for throttle, intake manifold, EGR valve and cylinder are developed separately and assemble together through connections. The component models are built from first principles in thermodynamics. Bidirectional flows are allowed at all ports for every component. The intake manifold uses mass, temperature and EGR mass fraction as state variables. Simulation results of a typical engine are included.

Many embedded powertrain and vehicle controls rely on speed and acceleration information. These measurements, however, are often noisy. Good filters are needed to reduce the noise. In some vehicles, acceleration sensors are not used due to cost. For those vehicles, estimators are needed to estimate acceleration. The paper introduces a new process to design speed filters, acceleration filters, and acceleration estimators. A physics-based discrete state equation is used to describe the relationship between speed, acceleration, and jerk. Then, a Kalman filter is developed to get the optimal estimates for speed and acceleration from available measurements. Vehicle test data shows that these filters are effective in reducing noise without introducing significant time lag. The filter design process requires little iteration because there is only one design parameter, which is the ratio of one-by-one covariance matrices of process and measurement noise.