Dynamic Exhaust Valve Flow 1-D Modelling During Blowdown Conditions

2019-01-0058

01/15/2019

Event
International Powertrains, Fuels & Lubricants Meeting
Authors Abstract
Content
To conduct system level studies on internal combustion engines reduced order models are required in order to keep the computational load below reasonable limits. By its nature a reduced order model is a simplification of reality and may introduce modeling errors. However what is of interest is the size of the error and if it is possible to reduce the error by some method. A popular system level study is gas exchange and in this paper the focus is on the exhaust valve. Generally the valve is modeled as an ideal nozzle where the flow losses are captured by reducing the flow area. As the valve moves slowly compared to the flow the process is assumed to be quasi-steady, i.e. interpolation between steady-flow measurements can be used to describe the dynamic process during valve opening. These measurements are generally done at low pressure drops, as the influence of pressure ratio is assumed to be negligible. As it is very difficult to measure time-resolved mass flow it is hard to test validity of these modeling assumptions. Experimental data indicates that the model overestimates valve flow during the blowdown event. As the blowdown pulse contains a significant portion of the energy in the cylinder at exhaust valve opening, it is therefore of importance to model this correctly. In this paper experimental results from previously published research have been compared to simulation results and the deviation from quasi-steady behavior has been quantified. The deviation appears to be a function of pressure ratio over the valve and valve opening speed. A model is proposed to compensate for the observed effects.
Meta TagsDetails
DOI
https://doi.org/10.4271/2019-01-0058
Pages
7
Citation
Holmberg, T., Cronhjort, A., and Stenlaas, O., "Dynamic Exhaust Valve Flow 1-D Modelling During Blowdown Conditions," SAE Technical Paper 2019-01-0058, 2019, https://doi.org/10.4271/2019-01-0058.
Additional Details
Publisher
Published
Jan 15, 2019
Product Code
2019-01-0058
Content Type
Technical Paper
Language
English