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Identification of ringing operation for low temperature combustion engines

机译:识别低温内燃机的振铃操作

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摘要

High-efficiency and low-emission low temperature combustion modes including homogeneous charge compression ignition (HCCI) are limited at high load conditions due to rapid pressure rise rate, short combustion duration and ringing operation. This study uses two different HCCI engines to investigate combustion-generated ringing at a number of HCCI engine operating points between misfire and ringing zones for ethanol and n-heptane fuels. Ringing intensity (RI) is investigated along with main HCCI combustion parameters and engine-out emissions. The results show the RI generally increases by advancing crank angle of 50% fuel burnt (CA50) and also decreasing burn duration (BD). It is found that adjusting CA50 can provide a control knob for the RI since all the extreme noisy data points have CA50 < 9 CAD aTDC. In-cylinder pressure at 5, 10, 15 CAD aTDC (P-5,P-10 and P-15) and maximum in-cylinder pressure (P-max) show strong correlation with RI. To this end, P-5, P-10 and P-15 and P-max are used to develop an artificial neural network (ANN) model to predict RI. Experimental data at 155 steady-state points are used to evaluate the ANN model for two totally different HCCI engines running with high and low octane fuels. The validation results indicate that the ANN model can predict RI with less than 4.2% error. The ANN model can be used to identify HCCI ringing operation for combustion control applications. (C) 2016 Elsevier Ltd. All rights reserved.
机译:包括均质充量压缩点火(HCCI)在内的高效率和低排放的低温燃烧模式在高负载条件下受到限制,原因是压力上升速度快,燃烧持续时间短和响动操作。这项研究使用了两种不同的HCCI发动机来研究乙醇和正庚烷燃料在失火区和振铃区之间的许多HCCI发动机工作点处燃烧产生的振铃。研究了振铃强度(RI)以及主要的HCCI燃烧参数和发动机排放物。结果表明,RI通常通过提前50%燃料燃烧的曲柄角(CA50)以及减少燃烧持续时间(BD)而增加。已经发现,调整CA50可以为RI提供控制旋钮,因为所有极端嘈杂的数据点的CA50 <9 CAD aTDC。 5、10、15 CAD aTDC(P-5,P-10和P-15)时的缸内压力和最大缸内压力(P-max)与RI有很强的相关性。为此,P-5,P-10和P-15以及P-max用于开发人工神经网络(ANN)模型来预测RI。使用155个稳态点的实验数据来评估两种使用高辛烷值燃料和低辛烷值燃料的完全不同的HCCI发动机的ANN模型。验证结果表明,人工神经网络模型可以预测RI,误差小于4.2%。 ANN模型可用于识别用于燃烧控制应用的HCCI振铃操作。 (C)2016 Elsevier Ltd.保留所有权利。

著录项

  • 来源
    《Applied Energy》 |2016年第1期|142-152|共11页
  • 作者单位

    Islamic Azad Univ, Dept Automot Engn, Automot Fuel & Emiss Res Ctr AFERC, Shahreza Branch, Shahreza, Iran;

    Michigan Technol Univ, Dept Mech Engn Engn Mech, 1400 Townsend Dr, Houghton, MI 49931 USA;

    Michigan Technol Univ, Dept Mech Engn Engn Mech, 1400 Townsend Dr, Houghton, MI 49931 USA;

    Univ Teknol Malaysia, Fac Mech Engn, Automot Dev Ctr ADC, Johor Baharu, Malaysia;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    HCCI; LTC; Ringing operation; Ringing intensity; Artificial neural network;

    机译:HCCI;LTC;响铃操作;响铃强度;人工神经网络;
  • 入库时间 2022-08-18 00:08:14

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