Han Runzhe, Bohn Christian, Bauer Georg
College of Optical, Mechanical and Electrical Engineering, Zhejiang A&F University, Hangzhou 311300, China.
Institut für Elektrische Informationstechnik, Technische Universität Clausthal, 38678 Clausthal-Zellerfeld, Germany.
Sensors (Basel). 2024 Aug 13;24(16):5237. doi: 10.3390/s24165237.
The engine in-cylinder pressure is a very important parameter for the optimization of internal combustion engines. This paper proposes an alternative recursive Kalman filter-based engine cylinder pressure reconstruction approach using sensor-fused engine speed. In the proposed approach, the fused engine speed is first obtained using the centralized sensor fusion technique, which synthesizes the information from the engine vibration sensor and engine flywheel angular speed sensor. Afterwards, with the fused speed, the engine cylinder pressure signal can be reconstructed by inverse filtering of the engine structural vibration signal. The cylinder pressure reconstruction results of the proposed approach are validated by two combustion indicators, which are pressure peak Pmax and peak location Ploc. Meanwhile, the reconstruction results are compared with the results obtained by the cylinder pressure reconstruction approach using the calculated engine speed. The results of sensor fusion can indicate that the fused speed is smoother when the vibration signal is trusted more. Furthermore, the cylinder pressure reconstruction results can display the relationship between the sensor-fused speed and the cylinder pressure reconstruction accuracy, and with more belief in the vibration signal, the reconstructed results will become better.
发动机缸内压力是内燃机优化的一个非常重要的参数。本文提出了一种基于递归卡尔曼滤波器的替代方法，用于利用传感器融合的发动机转速重建发动机缸内压力。在所提出的方法中，首先使用集中式传感器融合技术获得融合后的发动机转速，该技术综合了来自发动机振动传感器和发动机飞轮角速度传感器的信息。然后，利用融合后的转速，通过对发动机结构振动信号进行逆滤波来重建发动机缸内压力信号。所提出方法的缸内压力重建结果通过两个燃烧指标进行验证，即压力峰值Pmax和峰值位置Ploc。同时，将重建结果与使用计算得到的发动机转速进行缸内压力重建方法所获得结果进行比较。传感器融合结果表明，当对振动信号的信任度更高时，融合后的转速更平滑。此外，缸内压力重建结果可以显示传感器融合转速与缸内压力重建精度之间的关系，并且对振动信号的信任度越高，重建结果就越好。
