Zero Dimension Heat Release Modeling for Gasoline, Ethanol, Isobutanol and Diisobutylene Operating in Compression Ignition with Varying Injection Strategies

Author:

Peng Qian1,Rockstroh Toby2,Hall Carrie1,Pamminger Michael2

Affiliation:

1. Illinois Institute of Technology

2. Argonne National Laboratory

Abstract

<div class="section abstract"><div class="htmlview paragraph">Gasoline compression ignition shows great potential in reducing NOx and soot emissions with competitive thermal efficiency by leveraging the properties of gasoline fuels and the high compression ratio of compression ignition engines operating air-dilute. Meanwhile, its control becomes challenging due to not only the properties of different gasoline-type fuels but also the impacts of injection strategies on the in-cylinder reactivity. As such, a computationally efficient zero-dimension combustion model can significantly reduce the cost of control development. In this study, a previously developed zero-dimension combustion model for gasoline compression ignition was extended to multiple gasoline-type fuel blends and a port fuel injection/direct fuel injection strategy. Tests were conducted on a 12.4-liter heavy-duty engine with five fuel blends. A modification was made to the functional ignition delay model to cover the significantly different ignition delay behavior between conventional and oxygenated fuel blends. The parameters in the model were calibrated with only gasoline data at a load of 14 bar brake mean effective pressure. The results showed that this physics-based model can be applied to the other four fuel blends at three different pilot injection strategies without recalibration. For all tests, the error of the maximum pressure is within 14 bar, and that of combustion phasing and indicated mean effective pressure is within 2 CAD and 1.1 bar, respectively. In addition, the model was validated with 7 bar BMEP data and had the same level of accuracy as the 14 bar cases.</div></div>

Publisher

SAE International

Subject

Artificial Intelligence,Mechanical Engineering,Fuel Technology,Automotive Engineering

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