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首页> 外文会议>Proceedings of the 2009 spring technical conference of the ASME Internal Combustion Engine Division >A STATISTICAL APPROACH TO SPARK ADVANCE MAPPING
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A STATISTICAL APPROACH TO SPARK ADVANCE MAPPING

机译：火花提前映射的统计方法

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Engines performance and efficiency are largely influenced by the combustion phasing. Operating conditions and control settings influence the combustion development over the crankshaft angle: the most effective control parameter used by Electronic Control Units (ECU) to optimize the combustion process for Spark Ignition (SI) engines is Spark Advance (SA).rnSA mapping is a time-consuming process, usually carried out with the engine running in steady state on the test bench, changing SA values while monitoring Brake and Indicated Mean Effective Pressure (BMEP, IMEP) and Brake Specific Fuel Consumption (BSFC). Mean values of IMEP and BSFC for a test carried out with a given SA setting are considered as the parameters to optimize. However, the effect of SA on IMEP and BSFC 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. Finally other elements, such as engine or components ageing, and disturbances like Air-to-Fuel Ratio (AFR) or air, water and oil temperature variations, could affect the tests results: this facet can be very significant for racing engines testing.rnThis paper presents a novel approach to SA mapping, with the objective of improving the performance analysis robustness, while reducing the test time. The methodology is based on the observation that, for a given running condition, IMEP can be considered a function of the combustion phasing, represented by the 50% Mass Fraction Burned (MFB50) parameter. Due to cycle-to-cycle variation, many different MFB50 and IMEP values are obtained during a steady state test carried out with constant SA. While MFB50 and IMEP absolute values are influenced by disturbance factors, the relationship between them holds, and it can be synthesized by means of the angular coefficient of the tangent line to the MFB50-IMEP distribution. The angular coefficient variations as a function of SA can be used to feed a SA controller, able to maintain the optimal combustion phasing. Similarly, knock detection is approached by evaluating two indexes: the distribution of a typical knock-rnsensitive parameter (MAPO, Maximum Amplitude of Pressure Oscillations) is related to that of CHR_(NET) (net Cumulative Heat Release), determining a robust knock index. A knock limiter controller can then be added, in order to restrict the SA range to safe values.rnThe methodology can be implemented in real-time combustion controllers: the algorithms have been applied offline to sampled data, showing the feasibility of fast and robust automatic mapping procedures.
机译：发动机的性能和效率在很大程度上受到燃烧定相的影响。运行条件和控制设置会影响曲轴角度上的燃烧发展：电子控制单元（ECU）用于优化火花点火（SI）发动机燃烧过程的最有效控制参数是火花提前（SA）.rnSA映射是耗时的过程，通常是在发动机在试验台上稳定运行的情况下进行的，更改SA值，同时监视制动和指示的平均有效压力（BMEP，IMEP）和制动比油耗（BSFC）。在给定的SA设置下执行的测试的IMEP和BSFC平均值被视为要优化的参数。但是，由于周期之间的差异，SA对IMEP和BSFC的影响不确定，因为：平均值分析需要许多发动机周期才能显着改善在给定控制设置下获得的性能。最后，其他因素（例如发动机或组件的老化，以及空燃比（AFR）或空气，水和油的温度变化等干扰）可能会影响测试结果：这一方面对于赛车发动机测试可能非常重要。本文提出了一种新的SA映射方法，旨在提高性能分析的鲁棒性，同时减少测试时间。该方法基于以下观察结果：对于给定的运行条件，可以将IMEP视为燃烧阶段的函数，以50％质量分数燃烧（MFB50）参数表示。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。尽管MFB50和IMEP绝对值受干扰因素影响，但它们之间的关系仍然成立，并且可以通过与MFB50-IMEP分布的切线的角度系数进行合成。角度系数随SA的变化可用于向SA控制器供电，从而能够维持最佳的燃烧相位。类似地，通过评估两个指标来实现爆震检测：典型的爆震敏感参数（MAPO，最大压力振荡幅值）的分布与CHR_（NET）（净累积热量释放）的分布有关，确定稳健的爆震指数。然后可以添加爆震限制器控制器，以将SA范围限制为安全值。rn该方法可以在实时燃烧控制器中实现：该算法已离线应用于采样数据，显示了快速而强大的自动控制的可行性映射程序。

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