Application of Bond Graph approach in dynamic modelling of industrial gas turbine

Montazeri-Gh, Morteza; Fashandi, Seyed Alireza Miran

doi:10.1051/meca/2017024

Cited by 18 publications

(41 citation statements)

References 19 publications

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“…The SGT 600, an industrial gas turbine of medium size with two shafts is investigated in this article. This setup can be utilized in mechanical-drive and power generation applications [38]. Known as one of the most reliable gas turbine in its power range, the SGT 600 comprises an axial compressor that possesses 10 stages, of which the first two include variable inlet guide vanes.…”

Section: Description Of Gas Turbine and Its Start-up Processmentioning

confidence: 99%

“…To prevent surging, the studied engine benefits from two bleed valves that can open at start to guarantee the stability and integrity for the engine. Table 1 lists the engine properties at design point [38]. In addition, the examined gas turbine includes two specific components: (1) gas generator (referred to as GG), and (2) power turbine (referred to as PT).…”

Section: Description Of Gas Turbine and Its Start-up Processmentioning

confidence: 99%

“…The bond graph model of gas turbine used in this study is developed and described by the authors of this study in Refs. [38,52,53]. For a better understanding of gas turbine modeling procedure using bond graph, the reader is encouraged to read the mentioned references.…”

Section: Modeling the Industrial Gas Turbinementioning

confidence: 99%

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Modeling and Control of the Starter Motor and Start-Up Phase for Gas Turbines

2019

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Improving the performance of industrial gas turbines has always been at the focus of attention of researchers and manufacturers. Nowadays, the operating environment of gas turbines has been transformed significantly respect to the very fast growth of renewable electricity generation where gas turbines should provide a safe, reliable, fast, and flexible transient operation to support their renewable partners. So, having a reliable tools to predict the transient behavior of the gas turbine is becoming more and more important. Regarding the response time and flexibility, improving the turbine performance during the start-up phase is an important issue that should be taken into account by the turbine manufacturers. To analyze the turbine performance during the start-up phase and to implement novel ideas so as to improve its performance, modeling, and simulation of an industrial gas turbine during cold start-up phase is investigated this article using an integrated modular approach. During this phase, a complex mechatronic system comprised of an asynchronous AC motor (electric starter), static frequency converter drive, and gas turbine exists. The start-up phase happens in this manner: first, the clutch transfers the torque generated by the electric starter to the gas turbine so that the turbine reaches a specific speed (cranking stage). Next, the turbine spends some time at this speed (purging stage), after which the turbine speed decreases, sparking stage begins, and the turbine enters the warm start-up phase. It is, however, possible that the start-up process fails at an intermediate stage. Such unsuccessful start-ups can be caused by turbine vibrations, the increase in the gradients of exhaust gases, or issues with fuel spray nozzles. If, for any reason, the turbine cannot reach the self-sustained speed and the speed falls below a certain threshold, the clutch engages once again with the turbine shaft and the start-up process is repeated. Consequently, when modeling the start-up phase, we face discontinuities in performance and a system with variable structure owing to the existence of clutch. Modeling the start-up phase, which happens to exist in many different fields including electric and mechanical application, brings about problems in numerical solutions (such as algebraic loop). Accordingly, this study attempts to benefit from the bond graph approach (as a powerful physical modeling approach) to model such a mechatronic system. The results confirm the effectiveness of the proposed approach in detailed performance prediction of the gas turbine in start-up phase.

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Section: Description Of Gas Turbine and Its Start-up Processmentioning

confidence: 99%

Section: Description Of Gas Turbine and Its Start-up Processmentioning

confidence: 99%

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Modeling and Control of the Starter Motor and Start-Up Phase for Gas Turbines

2019

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“…As mentioned earlier, the model of the JQ was developed using a bond graph in previous studies by the authors. Full details about the modeling procedure can be found in References [14][15][16]. The main assumptions used in the modeling approach are as follows:…”

Section: Jetquad Modelingmentioning

confidence: 99%

“…This strategy is to satisfy all jet engine control modes simultaneously to protect the engine from malfunctions and physical limitations. The modeling and simulation of the JQ was presented and discussed in detail in References [14][15][16]. The bond graph as a graphical representation tool for physical dynamic systems was utilized to model and simulate the dynamic behavior of the JQ.…”

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confidence: 99%

Control Requirements for Future Gas Turbine-Powered Unmanned Drones: JetQuads

2018

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The next generation of aerial robots will be utilized extensively in real-world applications for different purposes: Delivery, entertainment, inspection, health and safety, photography, search and rescue operations, fire detection, and use in hazardous and unreachable environments. Thus, dynamic modeling and control of drones will play a vital role in the growth phase of this cutting-edge technology. This paper presents a systematic approach for control mode identification of JetQuads (gas turbine-powered quads) that should be satisfied simultaneously to achieve a safe and optimal operation of the JetQuad. Using bond graphs as a powerful mechatronic tool, a modular model of a JetQuad including the gas turbine, electric starter, and the main body was developed and validated against publicly available data. Two practical scenarios for thrust variation as a function of time were defined to investigate the compatibility and robustness of the JetQuad. The simulation results of these scenarios confirmed the necessity of designing a compatibility control loop, a stability control loop, and physical limitation control loops for the safe and errorless operation of the system. A control structure with its associated control algorithm is also proposed to deal with future challenges in JetQuad control problems.

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