Review of engine control-oriented combustion models

2021 ◽  
pp. 146808742199295
Author(s):  
Jian Tang ◽  
Guoming G Zhu ◽  
Yifan Men

As requirements for continuously improving internal combustion engine fuel economy with satisfactory emissions, model-based control strategies are often used to optimize the combustion process. To apply advanced control techniques for closed-loop engine combustion control, control-oriented engine combustion models are necessary and they are physics-based, accurate enough for model-based control, computationally low cost, and capable of real-time simulations. In addition, control-oriented combustion model with adequate fidelity may need to adapt to physical system and environment changes over time to maintain model-based control performance, such as model-reference (guided) control, where the control-oriented combustion model runs in real-time to generate an error signal between physical system and reference-model output for feedback control. This paper provides a review of existing control-oriented engine combustion models, along with their associated applications. Three main groups of control-oriented combustion models are reviewed from simple to sophisticated physics-based dynamic models, including mean-value, Wiebe function-based, and reaction-based models. The fundamental principle of each model group is reviewed briefly and its applications are also addressed. At the macro level, a control-oriented engine model can be used for crank angle-based and/or cycle-based control. As the engine control hardware performance continuous improving with reduced cost, model-reference (guided) combustion control shall become reality since now it is feasible to run a physics-based control-oriented engine combustion model inside an engine control module. On the other hand, each model group, even for the simple mean-value model, has its own applicable scenarios.

2017 ◽  
Vol 20 (2) ◽  
pp. 167-180 ◽  
Author(s):  
Yudai Yamasaki ◽  
Ryosuke Ikemura ◽  
Motoki Takahashi ◽  
Fumiya Shimizu ◽  
Shigehiko Kaneko

Engine systems must continuously increase their thermal efficiencies and lower their emissions in real operation. To meet these demands, engine systems are increasingly improving their transient performance through control technology. Conventional engine control systems depend on control maps obtained from huge numbers of experiments, which is necessarily limited by the available number of man-hours. These time-consuming control maps are now being replaced by control inputs derived from on-board models. By calculating optimized control inputs in real time using various information, model-based control increases the robustness of advanced combustion technologies such as premixed charge compression ignition and homogeneous charge compression ignition, which use auto-ignition and combustion of air–fuel mixtures. Models also incur relatively low computational loads because the specifications of the engine control unit are lower than those of current smartphones. This article develops a simple diesel combustion model with model-based control of the multiple fuel injections. The model employs the discretized cycle concept based on fundamental thermodynamic equations and comprises simple fuel injection and chemical reaction models. Our control concept aims mainly to decrease the fuel consumption by increasing the thermal efficiency and reduce the combustion noise in real-world operation. The model predicts the peak in-cylinder gas pressure and its timing that minimize the combustion noise and maximize the thermal efficiency, respectively. In an experimental validation of the model, the computed and measured in-cylinder pressures were well matched at each phase under various parameter settings. In addition, the calculation time of the model is sufficiently short for on-board applications. In future, the proposed model will be extended to the design and installation of controllers for engine systems. The control concept and associated problems of this task are also described in this article.


Materials ◽  
2005 ◽  
Author(s):  
Ajit R. Nalla ◽  
James L. Glancey

To improve process controllability during VARTM, a new resin injection line was designed and tested. The injection line, which consists of multiple segments each independently operated, allows for the control of resin flow to different locations within the mold. Simulation of different injection line configurations for various mold geometries is studied. Performance of a prototype line is quantified with a laboratory size mold used to demonstrate the potential value and benefits of this approach. Specific performance metrics, including resin flow front controllability, total injection time and void formation are used to compare this new approach to conventional VARTM injection methods. Computer-based closed loop controller strategies are designed that use point sensor feedback of resin location. In addition, an adaptive control algorithm that uses a finite element model to provide real-time updates of the injection line configuration is presented. Experimental validation of two different control strategies is presented, and demonstrates that real-time, model-based control is possible in VARTM.


Author(s):  
V. Panov

This paper describes the development of a distributed network system for real-time model based control of industrial gas turbine engines. Distributed control systems contribute toward improvements in performance, testability, control system maintainability and overall life-cycle cost. The goal of this programme was to offer a modular platform for improved model based control system. Hence, another important aspect of this programme was real-time implementation of non-linear aero-thermal gas turbine models on a dedicated hardware platform. Two typical applications of real-time engine models, namely hardware-in-the-loop simulations and on-line co-simulations, have been considered in this programme. Hardware-in-the-loop platform has been proposed as a transitional architecture, which should lead towards a fully distributed on-line model based control system. Distributed control system architecture offers the possibility of integrating a real-time on-line engine model embedded within a dedicated hardware platform. Real-time executing models use engine operating conditions to generate expected values for measured and non-measured engine parameters. These virtual measurements can be used for the development of model based control methods, which can contribute towards improvements in engine stability, performance and life management. As an illustration of model based control concept, the example of gas turbine transient over-temperature protection is presented in this study.


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