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Model-Based Estimation of Cylinder Pressure Sensor Offset using Least-Squares Methods

机译:基于模型的最小二乘法圆柱压力传感器偏移估计

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摘要

Two methods for estimating the sensor offset of a cylinder pressure transducer are developed. Both methods fit the pressure data during pre-combustion compression to a polytropic curve. The first method assumes a known polytropic exponent, and the other estimates the polytropic exponent. The first method results in a linear least-squares problem, and the second method results in a nonlinear least-squares problem. The nonlinear least-squares problem is solved by separating out the nonlinear dependence and solving the single-variable minimization problem. For this, a finite difference Newton method is applied. Using this method, the cost of solving the nonlinear least-squares problem is only slightly higher than solving the linear least-squares problem. Both methods show good statistical behavior. Estimation error variances are inversely proportional to the number of pressure samples used for the estimation. The method is computationally inexpensive, and well suited for real-time control applications
机译:开发了两种估计气缸压力传感器传感器偏移的方法。两种方法都将燃烧前压缩过程中的压力数据拟合为多变曲线。第一种方法假定一个已知的多方指数,而另一种方法估计该多方指数。第一种方法导致线性最小二乘问题,第二种方法导致非线性最小二乘问题。非线性最小二乘问题是通过分离非线性相关性并解决单变量最小化问题来解决的。为此,应用了有限差分牛顿法。使用这种方法,解决非线性最小二乘问题的成本仅略高于解决线性最小二乘问题的成本。两种方法均显示出良好的统计行为。估计误差方差与用于估计的压力样本数量成反比。该方法在计算上便宜,并且非常适合于实时控制应用

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