基于模型的基于缸内压力传感器的火花点火发动机燃烧相位控制的燃烧持续时间和点火时间预测

Xin Wang, Amir Khameneian, P. Dice, Bo Chen, M. Shahbakhti, J. Naber, Chad Archer, Qiuping Qu, C. Glugla, G. Huberts
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引用次数: 7

摘要

燃烧相位,可以定义为50%燃烧质量分数(CA50)的曲柄角,是影响发动机效率、扭矩输出和排放的最重要参数之一。在均匀火花点火(SI)发动机中,点火正时控制算法通常是基于多个乘法器的映射,这需要大量的校准工作。本文提出了一种基于模型的点火时间预测框架,该框架采用计算效率高的面向控制的燃烧模型,用于实时燃烧相位控制。燃烧持续时间从点火时间到CA50 (ΔθIGN-CA50)在单个气缸循环的基础上,由燃烧模型在这项工作中开发的预测。该模型以SI发动机湍流火焰传播的物理特性为基础,包含了最重要的控制参数,包括点火正时、可变气门正时、空燃比和发动机负荷,这些参数主要受节气门开启位置和前三个参数的共同影响。使用64个测试点进行模型校准,开发的燃烧模型可以覆盖广泛的发动机运行条件,从而大大减少了校准工作。校正模型的均方根误差(RMSE)为1.7曲柄角度(CAD),相关系数(R2)为0.95。利用道路车辆试验数据对基于模型的燃烧持续时间和点火正时算法的性能进行了评价。将模型预测的燃烧持续时间和点火正时与实验数据进行比较,83%的预测误差在±3cad范围内。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Model-Based Combustion Duration and Ignition Timing Prediction for Combustion Phasing Control of a Spark-Ignition Engine Using In-Cylinder Pressure Sensors
Combustion phasing, which can be defined as the crank angle of fifty percent mass fraction burned (CA50), is one of the most important parameters affecting engine efficiency, torque output, and emissions. In homogeneous spark-ignition (SI) engines, ignition timing control algorithms are typically map-based with several multipliers, which requires significant calibration efforts. This work presents a framework of model-based ignition timing prediction using a computationally efficient control-oriented combustion model for the purpose of real-time combustion phasing control. Burn duration from ignition timing to CA50 (ΔθIGN-CA50) on an individual cylinder cycle-by-cycle basis is predicted by the combustion model developed in this work. The model is based on the physics of turbulent flame propagation in SI engines and contains the most important control parameters, including ignition timing, variable valve timing, air-fuel ratio, and engine load mostly affected by combination of the throttle opening position and the previous three parameters. With 64 test points used for model calibration, the developed combustion model is shown to cover wide engine operating conditions, thereby significantly reducing the calibration effort. A Root Mean Square Error (RMSE) of 1.7 Crank Angle Degrees (CAD) and correlation coefficient (R2) of 0.95 illustrates the accuracy of the calibrated model. On-road vehicle testing data is used to evaluate the performance of the developed model-based burn duration and ignition timing algorithm. When comparing the model predicted burn duration and ignition timing with experimental data, 83% of the prediction error falls within ±3 CAD.
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