Data-driven modeling and receding optimization control of diesel engine combustion process

被引：0
|
作者：
Hu, Yun-Feng [1 ,2 ]
Ding, Yi-Tong [2 ]
Zhao, Zhi-Xin [3 ]
Jiang, Bing-Jing [2 ]
Gao, Jin-Wu [1 ,2 ]
机构：
[1] State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun,130022, China
[2] College of Communication Engineering, Jilin University, Changchun,130022, China
[3] School of Mathematics, Changchun Normal University, Changchun,130032, China
来源：
Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition) | 2021年 / 51卷 / 01期
关键词：
24;
D O I：
10.13229/j.cnki.jdxbgxb20190906
中图分类号：
学科分类号：
摘要：
引用
收藏
页码：49 / 62
相关论文
共 50 条
  • [31] Data-Driven Predictive Control of Idle Speed Control for SI Engine
    Liang, Yu
    Xie, Xiaohua
    Hu, Yunfeng
    Chen, Hong
    [J]. 2015 27TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2015, : 4535 - 4540
  • [32] Coherent flamelet modeling of diesel engine combustion
    Musculus, MP
    Rutland, CJ
    [J]. COMBUSTION SCIENCE AND TECHNOLOGY, 1995, 104 (4-6) : 295 - 337
  • [33] CFD-based Data-driven Modeling of Reactivity and Stratification Dynamics for RCCI Engine Control
    Irdmousa, Behrouz Khoshbakht
    Naber, Jeffrey Donald
    Shahbakhti, Mahdi
    [J]. IFAC PAPERSONLINE, 2023, 56 (02): : 8272 - 8277
  • [34] Observational data-driven modeling and optimization of manufacturing processes
    Sadati, Najibesadat
    Chinnam, Ratna Babu
    Nezhad, Milad Zafar
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2018, 93 : 456 - 464
  • [35] Thermodynamic Analysis of Diesel Engine Combustion Process
    Jelic, Maro
    [J]. STROJARSTVO, 2010, 52 (06): : 615 - 620
  • [36] Data-driven robust receding horizon fault estimation
    Wan, Yiming
    Keviczky, Tamas
    Verhaegen, Michel
    Gustafsson, Fredrik
    [J]. AUTOMATICA, 2016, 71 : 210 - 221
  • [37] Exergy diagnosis of the combustion process in a Diesel engine
    Agudelo, Andres
    Agudelo, John
    Benjumea, Pedro
    [J]. REVISTA FACULTAD DE INGENIERIA-UNIVERSIDAD DE ANTIOQUIA, 2008, (45): : 41 - 53
  • [38] Formulating data-driven surrogate models for process optimization
    Misener, Ruth
    Biegler, Lorenz
    [J]. COMPUTERS & CHEMICAL ENGINEERING, 2023, 179
  • [39] Data-Driven Process Modeling and Optimization Aided by Material and Energy Balances: The Case of a Batch Polymerization Process
    Bardooli, Ahmed
    Dong, Yachao
    Georgakis, Christos
    [J]. IFAC PAPERSONLINE, 2021, 54 (03): : 1 - 6
  • [40] Data-driven optimization for process systems engineering applications
    van de Berg, Damien
    Savage, Thomas
    Petsagkourakis, Panagiotis
    Zhang, Dongda
    Shah, Nilay
    del Rio-Chanona, Ehecatl Antonio
    [J]. CHEMICAL ENGINEERING SCIENCE, 2022, 248
12345