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2012-04-16
Journal Article
2012-01-0951
Trevor Sweafford, Hwan-Sik Yoon, Yanying Wang, Anthony Will
Recent advancements in simulation software and computational hardware make it realizable to simulate a full vehicle system comprised of multiple sub-models developed in different modeling languages. The so-called, co-simulation allows one to develop a control strategy and evaluate various aspects of a vehicle system, such as fuel efficiency and vehicle drivability, in a cost-effective manner. In order to study the feasibility of the synchronized parallel processing in co-simulation this paper presents two co-simulation frameworks for a complete vehicle system with multiple heterogeneous subsystem models. In the first approach, subsystem models are co-simulated in a serial configuration, and the same sub-models are co-simulated in a parallel configuration in the second approach.
2010-10-19
Technical Paper
2010-01-2325
Lawrence Michaels, Sylvain Pagerit, Aymeric Rousseau, Phillip Sharer, Shane Halbach, Ram Vijayagopal, Michael Kropinski, Gregory Matthews, Minghui Kao, Onassis Matthews, Michael Steele, Anthony Will
Model-based control system design improves quality, shortens development time, lowers engineering cost, and reduces rework. Evaluating a control system's performance, functionality, and robustness in a simulation environment avoids the time and expense of developing hardware and software for each design iteration. Simulating the performance of a design can be straightforward (though sometimes tedious, depending on the complexity of the system being developed) with mathematical models for the hardware components of the system (plant models) and control algorithms for embedded controllers. This paper describes a software tool and a methodology that not only allows a complete system simulation to be performed early in the product design cycle, but also greatly facilitates the construction of the model by automatically connecting the components and subsystems that comprise it.
2008-04-14
Technical Paper
2008-01-1016
Michael Livshiz, Minghui Kao, Anthony Will
The growing complexity of engine control systems and integration with transmission and vehicle dynamics controls systems have lead to the use of torque-based engine control. Torque-based control enables flexibility and expandability of the powertrain control system structure. It allows various engine actuation technologies (active fuel management (AFM), cam phasing, supercharger, etc.) to be easily incorporated, and to enable a simpler control structure than current production controls. Torque-based control structure is developed to coordinate and achieve better engine, transmission, hybrid, and vehicle dynamics controls. This paper describes the role of Engine Torque Control in a torque-based control system. It gives an overview of Engine Torque Control architecture with main elements, and discusses control system requirements.
2004-03-08
Technical Paper
2004-01-0902
Michael Livshiz, Minghui Kao, Anthony Will
The growing complexity of engine control systems and its integration with vehicle dynamics controls systems has lead to the use of torque-based engine control. Torque-based control enables flexibility and expandability of the powertrain control system structure. It allows new engine technologies (displacement on demand, cam phasing, supercharger, etc.) to be easily incorporated, to coordinate better engine and transmission controls, and to enable a simpler control structure than current production controls. This paper describes the role of Engine Torque Control in a torque-based control system and it formulates main requirements to a model-based control strategy. Development of this strategy is impossible without an accurate model of powertrain system. There are many publications describing models of powertrain system elements for research purpose, however only few provided us with information about model validation, calibration process and accuracy for production.
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