Parameter Optimization and Combustion Performance Prediction of Diesel Engine-Based Wiebe Model

被引：0
|
作者：
Zhang F. [1 ]
Ma Q. [1 ]
Wang Z. [2 ]
Cao R. [2 ]
Li C. [2 ]
Pei Y. [1 ]
机构：
[1] State Key Laboratory of Engines(Tianjin University), Tianjin
[2] China North Engine Research Institute, Tianjin
来源：
Tianjin Daxue Xuebao (Ziran Kexue yu Gongcheng Jishu Ban)/Journal of Tianjin University Science and Technology | 2024年 / 57卷 / 05期
关键词：
diesel engine; Levenberg-Marquardt(LM) algorithm; neural network; random forest(RF) algorithm; Wiebe combustion model;
D O I：
10.11784/tdxbz202209006
中图分类号：
学科分类号：
摘要：
In this study，based on the experimental performance study of a single-cylinder diesel engine，a predictable Wiebe combustion model was proposed，including the selection of single and double Wiebe combustion models and machine learning algorithms. Herein，combustion parameters and engine performances of single-cylinder engine under different boundary conditions were also predicted. First，the single or double Wiebe model was selected based on how well the algebraic Wiebe equation fitted. Then，six Wiebe parameters were determined by further fitting the Wiebe equation with the Levenberg-Marquardt(LM)algorithm to model the heat release rate. Finally，using error back-propagation neural network(BP-NN)and random forest(RF)algorithms，two Wiebe combustion prediction models with greater applicability than Wiebe equation were developed，and combustion characteristics under different boundary conditions were investigated for single-cylinder engine. Results show that when the linear fitting accuracy of the algebraic Wiebe equation is less than or equal to 0.990 00 with a complex heat release rate curve，the double Wiebe equation is selected to obtain high-precision Wiebe combustion parameters. In contrast，the single Wiebe equation can be used. The values of fitting accuracy R2 of the heat release rate on the double Wiebe equation at 1 200 and 2 200 r/min are greater than 0.990 00，and the values of sum of squared errors are less than 0.01. Moreover，the heat release rate reconstructed by Wiebe parameters agrees with the experiment. The heat release rate fitting algorithm based on the LM algorithm can well reflect the combustion characteristics of diesel engines under different operating conditions. Furthermore，the BP-NN combustion prediction model shows higher accuracy in the first Wiebe shape factor(m1)and first Wiebe combustion initial phase(φ01)，while the RF algorithm exhibits higher accuracy in the first Wiebe combustion proportion(α)and combustion end phase(φend). Therefore，selecting an appropriate prediction model for different combustion parameters considerably improves the prediction accuracy. © 2024 Tianjin University. All rights reserved.
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页码：473 / 481
页数：8
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