Numerical Optimization of Spray-Guided Spark Assistance for Cold Idle Operation in a Heavy-Duty Gasoline Compression Ignition Engine

Le Zhao (), Yu Zhang, Yuanjiang Pei, Anqi Zhang and Muhsin M. Ameen
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Le Zhao: Aramco Americas: Aramco Research Center–Detroit, Novi, MI 48377, USA
Yu Zhang: Aramco Americas: Aramco Research Center–Detroit, Novi, MI 48377, USA
Yuanjiang Pei: Aramco Americas: Aramco Research Center–Detroit, Novi, MI 48377, USA
Anqi Zhang: Aramco Americas: Aramco Research Center–Detroit, Novi, MI 48377, USA
Muhsin M. Ameen: Argonne National Laboratory, Lemont, IL 60439, USA

Energies, 2023, vol. 16, issue 2, 1-14

Abstract: This article describes the results of a response surface model (RSM)-based numerical optimization campaign for spray-guided spark assistance at cold operations in a heavy-duty gasoline compression ignition (GCI) engine. On the basis of an earlier work on spark-assisted GCI cold combustion, a space-filling design of experiments (DoE) method was first undertaken to investigate a multitude of hardware design variables and engine operating parameters. The main design variables included the number of injector nozzles, fuel split quantities and injection timings, and spark timing. The objective variables were engine combustion efficiency (ŋ c ), maximum pressure rise rate (MPRR), and engine-out nitrogen oxide (NO x ) emissions. A total of 150 design candidates were automatically generated using the Sobol sequence method provided by the commercial software package, CAESES. Then, closed-cycle computational fluid dynamic (CFD) spark-assisted GCI simulations under cold idling operations were performed. The outcomes from the CFD-DoE design campaign were utilized to construct high-fidelity RSMs that allowed for further design optimization of the spark plug- and fuel injector-related design variables, along with fuel injection strategy parameters. A merit function with respect to objective variables was formulated with an appropriate weight assignment on each objective variable. Finally, the best design candidate was identified from the RSM-based optimization process and further validated in the CFD analysis. The best design candidate showed the potential to significantly improve combustion efficiency (ŋ c > 90%) over the baseline at cold idle while satisfying MPRR and NO x emissions constraints (MPRR < 5 bar/CAD and NO x < 4.5 g/kWh).

Keywords: gasoline compression ignition; cold operation; spark assistance; CFD; design of experiments; optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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