Integrated Simulation of Engine Performance and AFR Control of a Stoichiometric Compression Ignition (SCI) Engine 2011-01-0698
This paper describes the advantage of the integrated simulation platform and presents the results of performance simulations and the feed-forward air-fuel ratio (AFR) controller design of a new concept stoichiometric compression ignition (SCI) engine based on this platform. In this integrated simulation environment, the SCI engine was modeled in GT-Power and a simplified production engine control module (ECM) is implemented in Simulink/Matlab for the performance simulation and AFR control.
The integrated engine and controller model was used to investigate constant-speed load-acceptance (CSLA) performance. During performance simulation, searching for operating conditions is difficult but critical for performance analysis. Trial and error method would require a long time to do. Based on the integrated simulation, a proportional-integral (PI) controller was designed to find the accurate operating conditions. At the same time, this method makes it easy to conduct batch simulation under various conditions. Several simulation cases will be discussed in this paper to show the improvements in efficiency and accuracy of the simulations.
The results show that performance simulation and control design will benefit each other. Feedback control design can help in finding operating conditions quickly and control the engine to perform at required steady state and transient conditions. Furthermore, engine performance simulation results can be utilized in control design and the control performance can be tested by the detail engine model. More benefits could be found in engine onboard diagnostics (OBD) design and verification because no simplified engine model could be comparable to the detailed engine model in GT-Power.
Citation: Wu, H., Wang, X., Winsor, R., and Baumgard, K., "Integrated Simulation of Engine Performance and AFR Control of a Stoichiometric Compression Ignition (SCI) Engine," SAE Technical Paper 2011-01-0698, 2011, https://doi.org/10.4271/2011-01-0698. Download Citation
Hai Wu, Xinlei Wang, Richard Winsor, Kirby Baumgard
Univ. of Illinois at Urbana-Champaign, John Deere Power Systems
SAE 2011 World Congress & Exhibition
Powertrain Control and Optimization, 2011-SP-2317