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Cylinder Pressure-based Virtual Sensor for Gas State Estimation During Compression Stroke

机译：基于气缸压力的虚拟传感器，用于压缩冲程期间的气体状态估计

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The gas state during the compression stroke can vary depending on the operating conditions and cycle-to-cycle variations. In this research, determination of polytropic exponent, trapped mass, and gas temperature are addressed. A golden section search method is applied to cyclic polytropic exponent estimation, and then a statistical filter is employed for cyclic estimation to filter out the estimation noise. A novel iterative-?p-method is finally presented for the determination of the trapped mass and gas temperature simultaneously during the compression stroke. A sequence of trapped mass estimates and a sequence of gas temperature estimates can be obtained along crank angle position. Experimental validations carried out on a gasoline engine demonstrate the effectiveness of the presented methods.
机译：压缩冲程期间的气体状态可能会根据运行条件和周期变化而变化。在这项研究中，解决了多方指数，截留质量和气体温度的确定问题。将黄金分割搜索方法应用于循环多方指数估计，然后将统计滤波器用于循环估计以滤除估计噪声。最后，提出了一种新颖的迭代-Δp方法，用于同时确定压缩冲程期间的捕集质量和气体温度。沿着曲柄角位置可以获得一系列的捕获质量估计值和一系列的气体温度估计值。在汽油发动机上进行的实验验证证明了所提出方法的有效性。

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