Gray-Box Modeling for Performance Control of an HCCI Engine With Blended Fuels

2014 ◽  
Vol 136 (10) ◽  
Author(s):  
M. Bidarvatan ◽  
M. Shahbakhti
Keyword(s):  
Real Time ◽  
Operating Conditions ◽  
Box Model ◽  
Average Error ◽  
Gas Temperature ◽  
Real Time Control ◽  
Neural Network Models ◽  
Time Model ◽  
Hcci Engine ◽  
Hcci Engines

High fidelity models that balance accuracy and computation load are essential for real-time model-based control of homogeneous charge compression ignition (HCCI) engines. Gray-box modeling offers an effective technique to obtain desirable HCCI control models. In this paper, a physical HCCI engine model is combined with two feed-forward artificial neural network models to form a serial architecture gray-box model. The resulting model can predict three major HCCI engine control outputs, including combustion phasing, indicated mean effective pressure (IMEP), and exhaust gas temperature (Texh). The gray-box model is trained and validated with the steady-state and transient experimental data for a large range of HCCI operating conditions. The results indicate that the gray-box model significantly improves the predictions from the physical model. For 234 HCCI conditions tested, the gray-box model predicts combustion phasing, IMEP, and Texh with an average error of less than 1 crank angle degree, 0.2 bar, and 6 °C, respectively. The gray-box model is computationally efficient and it can be used for real-time control application of HCCI engines.

Grey-Box Modeling for HCCI Engine Control

2013 ◽  
Author(s):  
M. Bidarvatan ◽  
M. Shahbakhti
Keyword(s):  
Real Time ◽  
Operating Conditions ◽  
Box Model ◽  
Average Error ◽  
Engine Control ◽  
Gas Temperature ◽  
Real Time Control ◽  
Time Model ◽  
Hcci Engine ◽  
Hcci Engines

High fidelity models that balance accuracy and computation load are essential for real-time model-based control of Homogeneous Charge Compression Ignition (HCCI) engines. Grey-box modeling offers an effective technique to obtain desirable HCCI control models. In this paper, a physical HCCI engine model is combined with two feed-forward artificial neural networks models to form a serial architecture grey-box model. The resulting model can predict three major HCCI engine control outputs including combustion phasing, Indicated Mean Effective Pressure (IMEP), and exhaust gas temperature (Texh). The grey-box model is trained and validated with the steady-state and transient experimental data for a large range of HCCI operating conditions. The results indicate the grey-box model significantly improves the predictions from the physical model. For 234 HCCI conditions tested, the grey-box model predicts combustion phasing, IMEP, and Texh with an average error less than 1 crank angle degree, 0.2 bar, and 6 °C respectively. The grey-box model is computationally efficient and it can be used for real-time control application of HCCI engines.

Technical and Engineering Decisions That Drive Choices for Predictive Analytics of Plant Data

2011 ◽  
Author(s):  
William Nieman
Keyword(s):  
Real Time ◽  
Predictive Analytics ◽  
Current Data ◽  
Operating Conditions ◽  
Maintenance Cost ◽  
Real Time Systems ◽  
Efficient Technology ◽  
Time Model ◽  
Trade Offs ◽  
Time Systems

Power generation has the goal of maximizing power output while minimizing operations and maintenance cost. The challenge for plant manager is to move closer to reliability limits while being confident the risks of any decision are understood. To attain their goals and meet this challenge they are coming to realize that they must have frequent, accurate assessment of equipment operating conditions, and a path to continued innovation-. At a typical plant, making this assessment involves the collection and effective analysis of reams of complex, interrelated production system data, including demand requirements, load, ambient temperature, as well as the dependent equipment data. Wind turbine health and performance data is available from periodic and real-time systems. To obtain the timeliest understanding of equipment health for all the key resources in a large plant or fleet, engineers increasingly turn to real-time, model-based solutions. Real-time systems are capable of creating actionable intelligence from large amounts and diverse sources of current data. They can automatically detect problems and provide the basis for diagnosis and prioritization effectively for many problems, and they can make periodic inspection methods much more efficient. Technology exists to facilitate prediction of when assets will fail, allowing engineers to target maintenance costs more effectively. But, it is critical to select the best predictive analytics for your plant. How do you make that choice correctly? Real-time condition monitoring and analysis tools need to be matched to engineering process capability. Tools are employed at the plant in lean, hectic environments; others are deployed from central monitoring centers charged with concentrating scarce resources to efficiently support plants. Applications must be flexible and simple to implement and use. Choices made in selection of new tools can be very important to future success of plant operations. So, these choices require solid understanding of the problems to be solved and the advantages and trade-offs of potential solutions. This choice of the best Predictive Analytic solution will be discussed in terms of key technology elements and key engineering elements.

Transfer Function Modelling of Urban Drainage Systems, and Potential Uses in Real-Time Control Applications

1994 ◽  
Vol 29 (1-2) ◽  
pp. 409-417 ◽  
Author(s):  
Andrea G. Capodaglio
Keyword(s):  
Transfer Function ◽  
Real Time ◽  
Sewage Treatment ◽  
Operating Conditions ◽  
Urban Drainage ◽  
Real Time Control ◽  
Control Applications ◽  
Time Control ◽  
Function Modelling ◽  
Transfer Function Modelling

According to the present state-of-the-art, sewerage systems, sewage treatment plants and their subsequent improvements are often planned and designed as totally separate entities, each subject to a specific set of performance objectives. As a result, sewage treatment efficiency is subject to considerable variability, depending both on general hydrologic conditions in the urban watershed (wet versus dry periods), and on specific “instantaneous” operating conditions. It has been postulated that the integration of urban drainage and wastewater treatment design and operation could allow minimization of the harmful effects of discharges from treatment plants, overflows and surface water runoff. This “ideal condition” can be achieved through the introduction of so-called “real-time control” technology in sewerage collection and treatment operations. To be a feasible goal, this technology poses the demand for more powerful simulation models of either aspect of the system - or, ideally, of a unified sewer-and-treatment plant model - than most of those currently available. This paper examines the requirements of rainfall/runoff transformation and sewer flow models with respect to real-time control applications, and focuses on the methodology of stochastic, transfer function modelling, reporting application examples. Modalities and limitations of the extraction of information from the models thus derived are also analyzed.

A Java software agent framework for hard real-time manufacturing control

2017 ◽  
Vol 65 (11) ◽  
Author(s):  
Sebastian Theiss ◽  
Klaus Kabitzsch
Keyword(s):  
Real Time ◽  
Domain Knowledge ◽  
Real Time Control ◽  
Time Model ◽  
Time Control ◽  
Future Challenges ◽  
Analytical Response ◽  
Communication Flow ◽  
Hard Real Time ◽  
Robust Control Systems

AbstractMultiagent systems (MAS) have widely been recognized as a suitable software engineering approach to design distributed, flexible, and robust control-systems, as are needed to cope with current and future challenges in manufacturing. Yet, applying MAS for real-time control has been subject to several concessions so far. This paper presents a real-time Java multiagent platform, which allows both agent execution and distributed interaction under hard real-time conditions. The paper covers the architecture and implementation of such a platform, the integration of a domain knowledge model into the communication flow, and finally an analytical response time model including interactions, to actually proove the real-time capability of a distributed MAS.

scholarly journals Design of Real-Time Control Based on DP and ECMS for PHEVs

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Wei Wang ◽  
Zhenjiang Cai ◽  
Shaofei Liu
Keyword(s):  
Real Time ◽  
Fuel Consumption ◽  
Mode Selection ◽  
Time Algorithm ◽  
Operating Conditions ◽  
Real Time Control ◽  
Time Control ◽  
Manual Adjustment ◽  
Equivalent Fuel ◽  
Equivalent Fuel Consumption

A real-time control is proposed for plug-in-hybrid electric vehicles (PHEVs) based on dynamic programming (DP) and equivalent fuel consumption minimization strategy (ECMS) in this study. Firstly, the resulting controls of mode selection and series mode are stored in tables through offline simulation of DP, and the parallel HEV mode uses ECMS-based real-time algorithm to reduce the application of maps and avoid manual adjustment of parameters. Secondly, the feedback energy management system (FMES) is built based on feedback from SoC, which takes into account the charge and discharge reaction (CDR) of the battery, and in order to make full use of the energy stored in the battery, the reference SoC is introduced. Finally, a comparative simulation on the proposed real-time controller is conducted against DP, the results show that the controller has a good performance, and the fuel consumption value of the real-time controller is close to the value using DP. The engine operating conditions are concentrated in the low fuel consumption area of the engine, and when the driving distance is known, the SoC can follow the reference SoC well to make full use of the energy stored in the battery.

Modelling and Simulation of Homogeneous Charge Compression Ignition Engine Fueled by Biodiesel

2018 ◽  
Author(s):  
Meshack Hawi ◽  
Mahmoud Ahmed ◽  
Shinichi Ookawara
Keyword(s):  
Heat Release ◽  
Compression Ratio ◽  
Homogeneous Charge Compression Ignition ◽  
Internal Combustion ◽  
Operating Conditions ◽  
Emission Characteristics ◽  
Compression Ignition ◽  
Hcci Engine ◽  
Hcci Engines ◽  
Homogeneous Charge

Homogeneous charge compression ignition (HCCI) is a combustion technology which has received increased attention of researchers in the combustion field for its potential in achieving low oxides of nitrogen (NOx) and soot emission in internal combustion (IC) engines. HCCI engines have advantages of higher thermal efficiency and reduced emissions in comparison to conventional internal combustion engines. In HCCI engines, ignition is controlled by the chemical kinetics, which leads to significant variation in ignition time with changes in the operating conditions. This variation limits the practical range of operation of the engine. Additionally, since HCCI engine operation combines the operating principles of both spark ignition (SI) and compression ignition (CI) engines, HCCI engine parameters such as compression ratio and injection timing may vary significantly depending on operating conditions, including the type of fuel used. As such, considerable research efforts have been focused on establishing optimal conditions for HCCI operation with both conventional and alternative fuels. In this study, numerical simulation is used to investigate the effect of compression ratio on combustion and emission characteristics of an HCCI engine fueled by pure biodiesel. Using a zero-dimensional (0-D) reactor model and a detailed reaction mechanism for biodiesel, the influence of compression ratio on the combustion and emission characteristics are studied in Chemkin-Pro. Simulation results are validated with available experimental data in terms of incylinder pressure and heat release rate to demonstrate the accuracy of the simulation model in predicting the performance of the actual engine. Analysis shows that an increase in compression ratio leads to advanced and higher peak incylinder pressure. The results also reveal that an increase in compression ratio produces advanced ignition and increased heat release rates for biodiesel combustion. Emission of NOx is observed to increase with increase in compression ratio while the effect of compression ratio on emissions of CO, CO2 and unburned hydrocarbon (UHC) is only marginal.

Preliminary Experimental Results of Integrated Gasification Fuel Cell Operation Using Hardware Simulation

2012 ◽  
Vol 134 (7) ◽  
Author(s):  
Alberto Traverso ◽  
David Tucker ◽  
Comas L. Haynes
Keyword(s):  
Fuel Cells ◽  
Fuel Cell ◽  
Real Time ◽  
Cell Model ◽  
Open Loop ◽  
Operating Conditions ◽  
Department Of Energy ◽  
Constant Speed ◽  
Time Model ◽  
Integrated Gasification

A newly developed integrated gasification fuel cell (IGFC) hybrid system concept has been tested using the Hybrid Performance (Hyper) project hardware-based simulation facility at the U.S. Department of Energy, National Energy Technology Laboratory. The cathode-loop hardware facility, previously connected to the real-time fuel cell model, was integrated with a real-time model of a gasifier of solid (biomass and fossil) fuel. The fuel cells are operated at the compressor delivery pressure, and they are fueled by an updraft atmospheric gasifier, through the syngas conditioning train for tar removal and syngas compression. The system was brought to steady state; then several perturbations in open loop (variable speed) and closed loop (constant speed) were performed in order to characterize the IGFC behavior. Coupled experiments and computations have shown the feasibility of relatively fast control of the plant as well as a possible mitigation strategy to reduce the thermal stress on the fuel cells as a consequence of load variation and change in gasifier operating conditions. Results also provided an insight into the different features of variable versus constant speed operation of the gas turbine section.

INTEGRAL CONTROL REQUIREMENTS FOR SEWERAGE SYSTEMS

1994 ◽  
Vol 30 (1) ◽  
pp. 131-138
Author(s):  
Andrea G. Capodaglio
Keyword(s):  
Real Time ◽  
Sewage Treatment ◽  
Operating Conditions ◽  
Ideal Condition ◽  
Real Time Control ◽  
Combined Sewer Overflows ◽  
Integral Control ◽  
Time Control ◽  
Combined Sewer ◽  
Harmful Effects

Sewerage systems and sewage treatment plants are often planned, designed and operated as totally separate entities. As a result, sewage treatment efficiency is subject to considerable variability, depending both on general hydrologic conditions in the urban watershed (wet versus dry periods), and on specific “instantaneous” operating conditions. It has been postulated that the integration of design and operation in urban drainage and wastewater treatment could allow minimization of the harmful effects of discharges from treatment plants, combined sewer overflows and surface runoff. This “ideal condition” can be achieved through the introduction of so-called “Real-Time Control” technology in sewerage collection and treatment operations. This paper examines the requirements of a hypothetical integrated sewer flow and sewage treatment model, the mathematical tools used to design and operate Real-Time Control systems, and the issues emerging from an integration of the conveyance and disposal aspects of the sewerage cycle.

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