PriMera Scientific Engineering (ISSN: 2834-2550)

Research Article

Volume 4 Issue 2

A Method for real-time Combustion Metrics Estimation using Wiebe Model in Diesel Engine

Yao Liu*

January 27, 2024

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Abstract

Combustion closed-loop control is an important technology for intelligent energy saving and emission reduction of internal combustion engines. The real-time feedback of combustion indicators plays an important role in the accuracy and rapidity of closed-loop control. However, the calculation of the combustion midpoint based on the complete heat release rate curve often consumes more computing resources. In order to speed up the calculation speed, this paper proposed a method that the Wiebe model combined with neural network prediction combustion metric. Firstly, we match the Wiebe basis function for different working conditions by analyzing the heat release rate curve. then the RLS-DE algorithm is developed to identify the heat release rate curve with high precision, and the BP neural network combined with the Wiebe model parameters is used to calculate CA50. Finally, in the HIL real-time simulation environment, the calculation accuracy and calculation speed of the algorithm are verified. The results show that the use of different Wiebe basis functions combined with the RLS-DE algorithm can fit the heat release rate curves under different working conditions with high precision, and the fitting error is within 5%. The CA50 prediction algorithm based on the parameters of the Wiebe model has a different calculation accuracy under different loads. The algorithm error is 6%-8% at low load, and the error is 2%-4% under high load conditions. It is developed in the cRIO-9047 real-time computing platform. The algorithm time-consuming is 8-12 us, which has high real-time performance and engineering application value.

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