Micro Gas Turbine Engine: A Review

Nascimento, Marco A. R.; OliveiraRodrigues, Lucilene de; Santos, Eraldo Cruz dos; Gomes, E. E. B.; Dias, FagnerLuis Goulart; Velásques, Elkin Iván Gutiérrez; Carrillo, Rubén A. M.

doi:10.5772/54444

Cited by 65 publications

(48 citation statements)

References 4 publications

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“…Although higher efficiencies of 25% for EFGT have been reported [30], for the relevant size within this study, we expect an electrical efficiency below 20% [13,15,22,30]. Actually, there is no exact definition for EFGT classes with respect to the plant size, so we defined microscale, based on other researches, as being up to 200 kW el [31][32][33][34]. An overview of existing research on EFGT is given in Table 2.…”

Section: Introductionmentioning

confidence: 91%

Determination of Optimized Parameters for the Flexible Operation of a Biomass-Fueled, Microscale Externally Fired Gas Turbine (EFGT)

et al. 2016

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Biomass as a source of renewable energy is a promising solution for current problems in energy supply. Olive waste is considered as an interesting option, especially for Mediterranean countries. Within this paper, a microscale externally fired gas turbine (EFGT) technology is presented as a decentralized power plant, within the range of 15 kW th , based on olive residues. It was modeled by Aspen Plus 8.6 software to provide a sufficient technical study for such a plant. Optimized parameters for pressure ratio and turbine air-mass flow have been mapped for several loads to provide information for process control. For all cases, mechanical output, efficiency curves, and back-work ratio have been calculated. Using this information, typical plant sizes and an example of power production are discussed. Additionally, achievable energy production from olive waste is estimated on the basis of this data. The results of this study show that such a plant has an electrical efficiency of 5%-17%. This variation is due to the examination being performed under several combustion temperatures, actual load, heat exchanger temperatures, and heat transfer efficiency. A cost estimation of the discussed system showed an estimated capital cost of 33,800 to 65,300 € for a 15 kW th system.

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Section: Introductionmentioning

confidence: 91%

Determination of Optimized Parameters for the Flexible Operation of a Biomass-Fueled, Microscale Externally Fired Gas Turbine (EFGT)

et al. 2016

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“…There were some additional parameters for modeling alternative drivetrain HDT that are provided in Table A2 in Appendix A. Gas turbine power to electricity efficiency % 30% 28%-33% [185] Indicated thermal efficiency of CNG engine % 38.5 35%-50% [156] Indicated thermal efficiency of diesel engine % 47% 45%-55% [156] Electric generator efficiency % 95% 90%-99%…”

Section: Input Parametersmentioning

confidence: 99%

“…Therefore, it was assumed the baseline price and the uncertainty bounds of the battery pack to be 150 $/kWh and 50-250 $/kWh respectively. H2 tank $/kg 400 300-500 [8], [204] CNG tank $/kg 110 90-120 [203] Diesel tank $/kg 6 4-7 [194] Fuel cell system $/kW 70 30-90 [205] Electric motor $/kW 13 8-19 [8], [206] Gas turbine $/kW 400 300-500 [185] Diesel engine $/Liter 700 650-750 [203] CNG engine $/Liter 840 800-900 [203] Transmission (combustion) 8,550 4 8,000-9,000 [8] Transmission (electric) 2,000 5 1,800-2,200 [8] Diesel after-treatment system per liter of engine 450 425-475 [194] CNG after-treatment system per liter of engine 225 200-250 [194] Catenary components 6,500 6,000-7,000 [8] 1-Assuming uniform distribution of the uncertainties for the Monte Carlo analysis 2-Assuming a short haul glider with a day cab is 10% less expensive than the long [203] 3-Averaging between two studies 4-For all drivetrains with combustion engine as the main propulsion system 5-For all drivetrains with electric motor as the main propulsion system Table 3-7 illustrates the cost of various fuels that were assumed in this study. This study considered fuel costs based on their retail prices, which mostly obtained from Fulton and Miller's study [203].…”

Section: Cost Estimationmentioning

confidence: 99%

Comparing alternative heavy-duty drivetrains based on GHG emissions, ownership and abatement costs: Simulations of freight routes in British Columbia

Lajevardi

Axsen

Crawford

2019

Transportation Research Part D: Transport and Environment

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Heavy-duty trucks (HDTs) are vital in delivering products to the consumers around the world and help maintain the quality of life. However, they are heavily depending on fossil diesel use, which causing global climate change as well as local air pollutions. Although they represent a small percentage of vehicle population, they emit more than 30% of GHGs in road transportation or 5% of global greenhouse gas (GHG) emissions. Furthermore, GHG emissions from this sector are expected to steadily grow due to economic growth, globalization, industrialization, online shopping, and fast delivery expectations. This study was focused on the Canadian province of British Columbia (BC) as a case study where HDTs are responsible for more than 4% of total provincial GHGs. BC, along with many regions around the world, has been committed to reduce its GHG emissions by 80% below 2007 levels by 2050. The goal of this study was to evaluate the potential of meeting this objective for BC HDTs using alternative drivetrain technologies. First, a component-level model was developed in Matlab to compute on-road energy consumption and CO2 emissions of compressed natural gas and diesel HDTs based on their physical parameters (e.g. mass) over several selected drive cycles. Results of the first contribution indicated a compressed natural gas (CNG) drivetrain emits 13-15% fewer GHG than a comparable diesel. Road grades of several main BC routes were included in the drive cycle simulations, which is an important factor that can increase the fuel consumption and CO2 emission by as much as 24% relative to a flat route assumption. In the second contribution, the physical energy consumption model was extended to compare 16 diverse drivetrain technologies, including a pure battery electric. The comparison metrics were also extended to well-to-wheel GHG emissions, total ownership costs (TOC) (including infrastructure), and abatement costs (based on incremental TOC cost over GHG emissions reduction), and cargo capacity impacts. The 16 considered drivetrains were distinguished by their fuel types, combustion technology, drivetrain architecture, and connection to the electricity grid (e.g. catenary vs fast charging stations). Next, the activity data of 1,616 HDTs operating in BC with sparse recording intervals was used to select 6 representative freight routes with different ranges of 120-950 km split into short and long haul routes. A combination of filtering and interpolation techniques was used to develop 1-Hz drive cycles compatible with the level of plug-in hybrid adoption. It was found infrastructure density increases the probability of meeting the 2050 target on both short and long haul HDTs. However, the increase in the probability is much higher for the short haul segment. Among various infrastructure roll-out scenarios, rapid deployment of hydrogen fueling stations was found to have the highest positive impact on GHG emissions reduction for both short and long haul markets. Both battery electric and hydrogen fuel cell drivetrains can succeed in...

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“…Micro gas turbine engine (MGTE) is a gas turbine engine with thrust less than 100 daN. It has the advantages of low cost, high performance, small size, and easy maintenance and storage [1,2]. It can be used as the alternative power plants of micro air vehicles, unmanned combat air vehicle (UCAV), distributed generation applications, reconnaissance plane, and other small weapons [3,4].…”

Section: Introductionmentioning

confidence: 99%

Research on Modeling of a Micro Variable-Pitch Turboprop Engine Based on Rig Test Data

2020

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Exact component characteristics are required for establishing an accurate component level aeroengine model. When component characteristics is lacking, the dynamic coefficient method based on test data, is suitable for establishing a single-input and single-output aeroengine model. When it is applied to build multiple-input, multiple-output aeroengine models, some parameters are assumed to be unchanged, which causes large error. An improved modeling method based on rig data is proposed to establish a double-input, double-output model for a micro variable-pitch turboprop engine. The input variables are fuel flow and pitch angle, and the output variables are rotational speeds of the core engine and the propeller. First, in order to gather modeling data, a test bench is designed and rig tests are carried out. Then, two conclusions are obtained by analyzing the rig data, based on which, the power turbine output is taken as the function of the core speed and the propeller speed. The established model has the property that the input variables can vary arbitrarily within the defined domain, without any restriction to the output variables. Simulation results showed that the model has a high dynamic and steady-state accuracy. The maximum error was less than 8%. The real-time performance was greatly improved, compared to the component level model. regulating mechanism is designed and a micro turboprop engine test platform is built.The mathematical model of the aeroengine plays an important role in the design and verification of the aeroengine control system, which can effectively reduce the development time, risk, and cost [8,9]. Micro gas turbine engines are widely used as low-cost solutions, therefore, fewer sensors are usually available than in standard gas turbines [8]. An accurate model can offer reference signals to the control system of micro engines. The modern aeroengine control systems adopt model-based ones, to fully utilize their performance. Modern aeroengine control methods such as performance seeking control, life extending control, and fault-tolerant control require an on-board engine model to track unmeasured parameters [10,11]. Aeroengine modeling methods can be divided into three categories-analytical methods based on operating principles (white box method), system identification methods based on test data (black box method), and gray box methods, which consider synthetic test data and operating principles.A component level model is built based on analytical methods, by using component characteristics and engine operating principles. It is the most common aeroengine modeling method. Fitzgerald et al. from Georgia Tech Institute built a component level model, based on the component characteristics of SPT5 [12,13]. The component characteristics are obtained via rig tests carried out in their own test platform. The model obtained by the analytical method has a high precision and can simulate both steady-state and dynamic engine outputs in the full envelope. However, this method requires accurate component ch...

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Micro Gas Turbine Engine: A Review

Cited by 65 publications

References 4 publications

Determination of Optimized Parameters for the Flexible Operation of a Biomass-Fueled, Microscale Externally Fired Gas Turbine (EFGT)

Determination of Optimized Parameters for the Flexible Operation of a Biomass-Fueled, Microscale Externally Fired Gas Turbine (EFGT)

Comparing alternative heavy-duty drivetrains based on GHG emissions, ownership and abatement costs: Simulations of freight routes in British Columbia

Research on Modeling of a Micro Variable-Pitch Turboprop Engine Based on Rig Test Data

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