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Fast Simulation of Wave Action in Engine Air Path Systems Using Model Order Reduction
ISSN: 1946-3936, e-ISSN: 1946-3944
Published April 05, 2016 by SAE International in United States
Citation: Stockar, S., Canova, M., Xiao, B., Dai, W. et al., "Fast Simulation of Wave Action in Engine Air Path Systems Using Model Order Reduction," SAE Int. J. Engines 9(3):1398-1408, 2016, https://doi.org/10.4271/2016-01-0572.
Engine downsizing, boosting, direct injection and variable valve actuation, have become industry standards for reducing CO2 emissions in current production vehicles. Because of the increasing complexity of the engine air path system and the high number of degrees of freedom for engine charge management, the design of air path control algorithms has become a difficult and time consuming process. One possibility to reduce the control development time is offered by Software-in-the-Loop (SIL) or Hardware-in-the-Loop (HIL) simulation methods. However, it is significantly challenging to identify engine air path system simulation models that offer the right balance between fidelity, mathematical complexity and computational burden for SIL or HIL implementation.
In this paper, a new modeling approach is presented to predict the performance of the exhaust system of a downsized boosted engine, including the ability to predict the influence of pressure wave propagation on the exhaust flows and turbine performance. A key feature of the proposed model is the use of a model order reduction technique that approximates the conservation laws in partial differential equation form as a reduced-order system of nonlinear ordinary differential equations. The result is a model that can be easily implemented into SIL or HIL simulation tools as a “virtual engine” and offers significantly lower computational requirements compared to 1D gas dynamic simulators.
To evaluate the accuracy of the reduced-order model, simulation results are compared against the industry standard tool used for engine performance simulation (GT-Power), for a range of different operating conditions. A set of metrics to quantify the accuracy and computation time of the model is proposed and used to perform a complete analysis.