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首页> 外文会议>ASME Internal Combustion Engine Division fall technical conference 2010 >SPARK ADVANCE REAL-TIME OPTIMIZATION BASED ON COMBUSTION ANALYSIS
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SPARK ADVANCE REAL-TIME OPTIMIZATION BASED ON COMBUSTION ANALYSIS

机译：基于燃烧分析的火花提前实时优化

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Future emission regulations could force manufacturers to install in-cylinder pressure sensors on production engines. The availability of such a signal opens a new scenario in terms of combustion control: many settings that previously were optimized off-line, can now be monitored and calibrated in realtime. One of the most effective factors influencing performance and efficiency is the combustion phasing: in gasoline engines Electronic Control Units (ECU) manage the Spark Advance (SA) in order to set the optimal combustion phase.SA optimal values are usually determined by means of calibration procedures carried out on the test bench by changing the ignition angle while monitoring Brake and Indicated Mean Effective Pressure (BMEP, IMEP) and Brake Specific Fuel Consumption (BSFC). The optimization process relates BMEP, IMEP and BSFC mean values with the control setting (SA). However, the effect of SA on combustion is not deterministic, due to the cycle-to-cycle variation: the analysis of mean values requires many engine cycles to be significant of the performance obtained with the given control setting.This paper presents a novel approach to SA optimization, with the objective of improving the performance analysis robustness, while reducing the test time. The approach can be either used in the calibration phase or in on-board applications, if the in-cylinder pressure signal is available: this would allow maintaining the optimization active throughout the entire engine life.The methodology is based on the observation that, for a given running condition, IMEP can be considered a function of a single combustion parameter, represented by the 50% Mass Fraction Burned (50%MFB). Due to cycle-to-cycle variation, many different MFB50 and IMEP values are obtained during a steady state test carried out with constant SA, but these values are related by means of a unique relationship. The distribution on the plane IMEP-MFB50 forms a parabola, therefore the optimization could be carried out by choosing SA values maintaining the scatter around the vertex. Unfortunately the distribution shape is slightly influenced by heat losses (i.e., bySA): this effect must be taken into account in order to avoid over-advanced calibrations.SA is then controlled by means of a PID (Proportional Integer Derivative) controller, fed by an error that is defined based on the previous considerations: a contribution is related to the MFB50-IMEP distribution, and a second contribution is related to the net Cumulative Heat Release (CHR_(net))-IMEP distribution. The latter is able to take into account for heat losses.Firstly, the methodology has been tested on in-cylinder pressure data, collected from different SI engines; then, it has been implemented in real-time, by means of a programmable combustion analyzer: the system performs a cycle-to-cycle combustion analysis, evaluating the combustion parameters necessary to calculate the target SA, which is then actuated by the ECU. The approach proved to be efficient, reducing the number of engine cycles necessary for the calibration to less than 1000 per operating condition.
机译：未来的排放法规可能会迫使制造商在生产发动机上安装缸内压力传感器。这种信号的可用性开启了燃烧控制方面的新局面：许多以前离线优化的设置现在可以实时监控和校准。影响性能和效率的最有效因素之一是燃烧阶段：在汽油发动机中，电子控制单元（ECU）管理Spark Advance（SA）以设置最佳燃烧阶段。SA最佳值通常通过校准来确定通过在监测制动和指示平均有效压力（BMEP，IMEP）和制动比油耗（BSFC）的同时改变点火角度，在试验台上执行此程序。优化过程将BMEP，IMEP和BSFC平均值与控制设置（SA）相关联。但是，由于循环之间的变化，SA对燃烧的影响不确定，其影响是不确定的：均值分析需要许多发动机循环才能显着改善在给定控制设置下获得的性能。本文提出了一种新颖的方法进行SA优化，目的是提高性能分析的鲁棒性，同时减少测试时间。如果缸内压力信号可用，则该方法既可以在校准阶段使用，也可以在车载应用中使用：这将使优化在整个发动机寿命中保持有效。在给定的运行条件下，IMEP可以视为单个燃烧参数的函数，以50％质量分数燃烧（50％MFB）表示。由于周期之间的差异，在以恒定SA进行的稳态测试过程中会获得许多不同的MFB50和IMEP值，但是这些值是通过唯一关系关联的。 IMEP-MFB50平面上的分布形成抛物线，因此可以通过选择SA值来保持顶点周围的散射来进行优化。不幸的是，分布形状受热损失的影响很小（即bySA）：必须考虑到这种影响，以避免过度进行标定。然后通过PID（比例整数微分）控制器控制SA，由基于先前考虑因素定义的误差：一个贡献与MFB50-IMEP分布有关，第二个贡献与净累积热量释放（CHR_（net））-IMEP分布有关。后者能够考虑到热量损失。首先，该方法已通过从不同SI发动机收集的缸内压力数据进行了测试；然后，它已通过可编程燃烧分析仪实时实施：系统执行逐周期燃烧分析，评估计算目标SA所需的燃烧参数，然后由ECU进行驱动。该方法被证明是有效的，将每个操作条件下校准所需的发动机循环数减少到少于1000个。

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