A new transient performance adaptation method for an aero gas turbine engine

Kim, Sangjo; Kim, Kui-Soon; Son, Changmin

doi:10.1016/j.energy.2019.116752

Cited by 26 publications

(8 citation statements)

References 15 publications

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“…As suggested by Kim et al [33], in the case of a temperature sensor located in a high temperature region, several thick structures are used to increase its life. A time delay error occurs for the measured temperature due to conduction of the structures.…”

Section: Measured Temperature Treatmentmentioning

confidence: 99%

“…A time delay error occurs for the measured temperature due to conduction of the structures. Kim et al [33] excluded the time delay error from the measured temperature by the lumped system analysis. The temperature sensor can be de ned as a solid body in a lumped system.…”

Section: Measured Temperature Treatmentmentioning

confidence: 99%

“…A time delay in the measured temperature occurs because of heat conduction in the structures. Kim et al [33] separated actual uid temperature from measured temperature at the gas turbine outlet through lumped system analysis under dynamic operating conditions. They performed physics-based model adaptation using the separated uid temperature to increase prediction accuracy.…”

Section: Introductionmentioning

confidence: 99%

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A data-driven modeling method for an aero gas turbine engine system based on the transient data

Kim

2022

Preprint

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Accurate performance prediction models in gas turbines are essential for diagnosis. In this paper, a data-driven modeling method is newly proposed for an aero gas turbine engine system with high prediction accuracy during dynamic operation by considering the time delay included in the measured temperature from a sensor. Modeling and analysis are performed using an aero gas turbine engine with rapid thrust change. The accuracy of the data-driven model trained using the measured temperature and the flow temperature calculated through physical relations is compared. The flow temperature is calculated from the measured temperature based on lumped system analysis. In data learning, the low-pressure shaft speed and low-pressure turbine total temperature are defined as input parameters, whilst engine net thrust, and fuel mass flow rate are defined as output ones. The results show that using the measured temperature for training without conversion adversely affects the accuracy of the data-driven model. The flow temperature converted from the measured values is reasonable in terms of thermodynamic cycle matching of the engine. It is confirmed that the accuracy of the data-driven model is significantly improved when the actual flow temperature is used for model training.

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Section: Measured Temperature Treatmentmentioning

confidence: 99%

Section: Measured Temperature Treatmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A data-driven modeling method for an aero gas turbine engine system based on the transient data

Kim

2022

Preprint

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“…Therefore, traditional modelling is not suitable when components' characteristic maps are missing. Some research improved traditional modelling method, where components' maps are obtained by introducing corrected factor or adaptive factor [6][7][8][9][10][11][12]. The characteristics of components can be obtained by this method, but only part of the actual operational data is considered for correction, and it is not directly related to the actual operational data.…”

Section: Introductionmentioning

confidence: 99%

A dual-driven approach for modelling heavy-duty gas turbine based on operational data and intelligent genetic algorithm

Jin¹,

Guan²,

He³

et al. 2022

Preprint

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In order to build an accurate model of heavy-duty gas turbine, a dual-driven approach is proposed based on operational data and intelligent genetic programming considering rotational speed, inlet/outlet temperature, pressure and generation power. The input-output thermodynamic characteristics of the compressor are obtained by genetic programming and net generation power of gas turbine is expressed by polynomial fitting formula equation, whose coefficients are obtained by least square method. Results show that all the models to calculate temperature ratio, pressure ratio and air mass flow ratio of compressor have a good accuracy, which of temperature ratio can reach 0.01. The accuracy of model to calculate generation power value can reach 0.04. This method for holistic modelling can be applied to other kinds of heavy-duty gas turbine.

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“…this correction includes the model parameter specification, which best fits the collected experimental data from engine testing and operation. Among them, the automatic adaption available for building a self-adjusting ACS engine is the most efficient way [5,[10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Development of Turboshaft Engine Adaptive Dynamic Model: Analysis of Estimation Errors

Yepifanov

Bondarenko

2022

Transactions on Aerospace Research

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One of the most perspective directions of aircraft engine development is related to implementing adaptive automatic electronic control systems (ACS). The significant elements of these systems are algorithms of matching of mathematical models to actual performances of the engine. These adaptive models are used directly in control algorithms and are a combination of static and dynamic sub-models. This work considers the dynamic sub-models formation using the Least Square method (LSM) on a base of the engine parameters that are measured in-flight. While implementing this function in the (ACS), the problem of checking the sufficiency of the used information for ensuring the required precision of the model arises. We must do this checking a priori (to determine a set of operation modes, the shape of the engine test impact and volume of recorded information) and a posteriori. Equations of the engine models are considered. Relations are derived that determine the precision of parameters of these models’ estimation depending on the precision of measurement, the composition of the engine power ratings, and durability of observations, at a stepwise change of fuel flow. We present these relations in non-dimensional coordinates that make them universal and ready for application to any turboshaft engine.

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A new transient performance adaptation method for an aero gas turbine engine

Cited by 26 publications

References 15 publications

A data-driven modeling method for an aero gas turbine engine system based on the transient data

A data-driven modeling method for an aero gas turbine engine system based on the transient data

A dual-driven approach for modelling heavy-duty gas turbine based on operational data and intelligent genetic algorithm

Development of Turboshaft Engine Adaptive Dynamic Model: Analysis of Estimation Errors

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