Prediction of Cyclic Variability and Knock-Limited Spark Advance (KLSA) in Spark-Ignition (SI) Engine

Zongyu Yue, K. Edwards, C. Sluder, S. Som
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Abstract

Engine knock remains one of the major barriers to further improve thermal efficiency of Spark Ignition (SI) engines. Knock can be suppressed by lowering the compression ratio, or retarding the spark ignition timing, however, at an expense of efficiency penalty. SI engine is usually operated at knock-limited spark advance (KLSA) to achieve possibly maximum efficiency with given engine hardware and fuel properties, such as Research Octane Number (RON), Motor Octane Number (MON), and heat of vaporization, etc. Co-optimization of engine design and fuel properties is promising to improve the engine efficiency and predictive CFD models can be used to facilitate this optimization process. However, difficulties exist in predicting KLSA in CFD simulations. First, cyclic variability of SI engine demands that multi-cycle results are required to capture the extreme conditions. Secondly, Mach Courant-Friedrichs-Lewy (CFL) number of 1 is desired to accurately predict the knock intensity (KI), resulting in unaffordable computational cost, especially for multi-cycle simulations. In this study, a new approach to numerically predict KLSA using large Mach CFL number of 50 is proposed. This approach is validated against experimental data for a boosted Direct Injection Spark Ignition (DISI) engine at multiple loads and spark timings. G-equation combustion model coupled with well-mixed chemical kinetic model are used to predict the turbulent flame propagation and end-gas auto-ignition, respectively. Simulations run for 10 consecutive engine cycles at each condition. The results show good agreement between model predictions and experiments in terms of cylinder pressure, combustion phasing and cyclic variation. Engine knock is predicted with early spark ignition timing, indicated by significant pressure wave oscillation and end-gas heat release. Maximum Amplitude of Pressure Oscillation (MAPO) analysis is performed to quantify the KI, and the slope change point in KI extrema is used to indicate the KLSA accurately. Using a smaller Mach CFL number of 5 also results in the same conclusions thus demonstrating that this approach is insensitive to the Mach CFL number. The use of large Mach CFL number allows us to achieve fast turn-around time for multi-cycle engine CFD simulations.
火花点火(SI)发动机循环变异性和限敲火花提前(KLSA)预测
发动机爆震是影响火花点火(SI)发动机进一步提高热效率的主要障碍之一。爆震可以通过降低压缩比或延迟火花点火时间来抑制,然而,这是以牺牲效率为代价的。在给定发动机硬件和燃料性能(如研究辛烷值(RON)、发动机辛烷值(MON)和汽化热等)的情况下,SI发动机通常在碰撞限制火花提前(KLSA)下运行,以达到可能的最高效率。发动机设计和燃油性能的协同优化有望提高发动机效率,而预测CFD模型可用于促进这一优化过程。然而,在CFD模拟中预测KLSA存在困难。首先,SI发动机的循环变异性要求多循环结果来捕捉极端条件。其次,为了准确预测爆震强度(KI),要求Mach couran - friedrichs - lewy (CFL)数为1,导致计算成本难以承受,特别是对于多周期模拟。本文提出了一种利用大马赫数50数值预测KLSA的新方法。该方法通过增压直接喷射火花点火(DISI)发动机在多种负载和火花时间下的实验数据进行了验证。采用g方程燃烧模型和混合化学动力学模型分别对湍流火焰传播和末端气体自燃进行了预测。在每种条件下,模拟运行了10个连续的发动机循环。结果表明,在气缸压力、燃烧相位和循环变化方面,模型预测与实验结果吻合较好。发动机爆震预测与早期的火花点火时间,表明明显的压力波振荡和末端气体热释放。利用最大压力振荡幅度(MAPO)分析来量化KI,并利用KI极值的斜率变化点来准确指示KLSA。使用较小的马赫数CFL也得到相同的结论,从而表明该方法对马赫数CFL不敏感。大马赫数的使用使我们能够实现多循环发动机CFD模拟的快速周转时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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