Model-in-the-Loop Simulation for Model Predictive Controlled High-Pressure Direct Injection Dual-Fuel Engine Combustion Control

Given the intricate combustion process and the multitude of control parameters inherent to the high-pressure direct injection (HPDI) diesel/natural gas dual-fuel engine, achieving precise combustion control represents a significant challenge. It is imperative to develop a high-precision engine model and integrate it with advanced control algorithms to achieve an optimal combustion strategy. In this study, a system-level engine plant model with high accuracy and real-time performance was developed using a modular modeling method through the calibration of experimental data and the simplification of model calculations. In this model, the relative error of the model simulation is controlled to be less than 5%, and the real-time factor (RTF) is less than 1. The multi-stage combustion process was parameterized by performing piecewise linear fitting of the heat release rate curve, and the relationship between injection parameters and combustion parameters was established using multiple regression analysis. On this basis, a model predictive control (MPC) algorithm was designed and verified in the constructed model-in-the-loop (MiL) platform. The results demonstrate that the designed MPC algorithm can accurately track the combustion phasing CA50 and the indicated mean effective pressure (IMEP) targets with a maximum error of 0.0624° and 0.046% within 6 and 8 cycles while ensuring the stability of the control process. The MiL platform not only meets the current combustion control requirements but also provides a general basis for the development of subsequent engine multi-control strategies and cooperative control optimization.

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Institutions

Publication Details

Journal
Designs
Published
2025-02-18
DOI
https://doi.org/10.3390/designs9010024
Citations
2
Primary Topic
Advanced Combustion Engine Technologies
Type
article
Field-Weighted Citation Impact
1.44

Funders

Controls
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article

Model-in-the-Loop Simulation for Model Predictive Controlled High-Pressure Direct Injection Dual-Fuel Engine Combustion Control

Xiuyun Shuai, Wei Cui, He Li, Wenbin Yu et al.
2 citations
Designs
Advanced Combustion Engine Technologies
1.44
article

Model-in-the-Loop Simulation for Model Predictive Controlled High-Pressure Direct Injection Dual-Fuel Engine Combustion Control

Xiuyun Shuai, Wei Cui, He Li, Wenbin Yu, Qingxin Wang, Feiyang Zhao, Hongyu Liu
article en
2 citations

Abstract

Given the intricate combustion process and the multitude of control parameters inherent to the high-pressure direct injection (HPDI) diesel/natural gas dual-fuel engine, achieving precise combustion control represents a significant challenge. It is imperative to develop a high-precision engine model and integrate it with advanced control algorithms to achieve an optimal combustion strategy. In this study, a system-level engine plant model with high accuracy and real-time performance was developed using a modular modeling method through the calibration of experimental data and the simplification of model calculations. In this model, the relative error of the model simulation is controlled to be less than 5%, and the real-time factor (RTF) is less than 1. The multi-stage combustion process was parameterized by performing piecewise linear fitting of the heat release rate curve, and the relationship between injection parameters and combustion parameters was established using multiple regression analysis. On this basis, a model predictive control (MPC) algorithm was designed and verified in the constructed model-in-the-loop (MiL) platform. The results demonstrate that the designed MPC algorithm can accurately track the combustion phasing CA50 and the indicated mean effective pressure (IMEP) targets with a maximum error of 0.0624° and 0.046% within 6 and 8 cycles while ensuring the stability of the control process. The MiL platform not only meets the current combustion control requirements but also provides a general basis for the development of subsequent engine multi-control strategies and cooperative control optimization.

DesignsVol. 9(1)
Shandong University (CN)
Natural Science Foundation of Shandong Province, AVL List, State Key Laboratory of Engines
Openalex Percentile: Top 23%
Advanced Combustion Engine Technologies
1.44
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