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22 pages, 8002 KiB  
Article
Controlling Engine Load Distribution in LNG Ship Propulsion Systems to Optimize Gas Emissions and Fuel Consumption
by Siniša Martinić-Cezar, Zdeslav Jurić, Nur Assani and Nikola Račić
Energies 2025, 18(3), 485; https://doi.org/10.3390/en18030485 - 22 Jan 2025
Viewed by 435
Abstract
The increasing emphasis on environmental sustainability and stricter gas emissions regulations has made the optimization of fuel and emissions a crucial factor for marine propulsion systems. This paper investigates the potential to improve fuel efficiency and reduce emissions of LNG ship propulsion systems [...] Read more.
The increasing emphasis on environmental sustainability and stricter gas emissions regulations has made the optimization of fuel and emissions a crucial factor for marine propulsion systems. This paper investigates the potential to improve fuel efficiency and reduce emissions of LNG ship propulsion systems by using different load sharing strategies in Dual-Fuel Diesel-Electric (DFDE) propulsion systems. Using data collected from on-board cyclic measurements and an optimization model, the effects of different load sharing strategies for various types of fuel, such as HFO, MDO, and LNG, under different engine load conditions were investigated. The results of these strategies are compared with those of on-board power management systems (PMS), which evenly allocate power among the engines, irrespective of fuel usage and emission levels. The results show that load adjustments according to the optimization model can considerably increase fuel economy and contribute to the reduction of CO2 and NOx compared to standard practice at the equal load in different ship operating modes. Our approach introduces an innovative optimization concept that has been proven to improve fuel efficiency and reduce emissions beyond standard practices. This paper demonstrates the robustness of the model in balancing environmental and operational objectives and presents an effective approach for more sustainable and efficient ship operations. The results are in line with global sustainability efforts and provide valuable insights for future innovations in energy optimization and ship emission control. Full article
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<p>Example of an emission measurement while the engine is running on LNG.</p>
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<p>Fuel consumption data for three different types of fuel depending on the engine load.</p>
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<p>Exhaust gas analyzer “Testo 350 Maritime”, used for measurements on an LNG ship.</p>
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<p>CO<sub>2</sub> emissions for three types of fuel depending on the engine load.</p>
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<p>NO<sub>x</sub> emissions for three types of fuel depending on the engine load.</p>
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<p>Position of the sampling probes during recording under real operating conditions.</p>
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<p>Humidity measuring instrument “Testo 610”, used for measurements on an LNG ship.</p>
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<p>Optimization model flow chart.</p>
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<p>Optimization example for LNG at 8000 kW on two engines.</p>
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<p>Optimization example for LNG at 20,000 kW on four engines.</p>
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<p>Optimization example for HFO at 20,000 kW on four engines.</p>
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<p>Optimization example for MDO at 20,000 kW on four engines.</p>
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<p>Fuel consumption for the power range 24,000–26,000 kW.</p>
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<p>Share of CO<sub>2</sub> emissions for the power range 24,000–26,000 kW.</p>
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<p>Share of NO<sub>x</sub> emissions for the power range 24,000–26,000 kW.</p>
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<p>Percentage load distribution across the engines for the power range of 24,000–26,000 kW.</p>
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<p>Consumption based on the fuel weighting factors.</p>
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<p>CO<sub>2</sub> emissions based on the fuel weighting factors.</p>
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<p>NO<sub>x</sub> emissions based on the weighting factors.</p>
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26 pages, 7066 KiB  
Article
Comprehensive Thermodynamic Performance Evaluation of a Novel Dual-Shaft Solid Oxide Fuel Cell Hybrid Propulsion System
by Jinghui Xu, Xizhen Wang, Zepeng Wang, Kaiqiang Yang, Xueshun Li and Yongjun Zhao
Aerospace 2025, 12(1), 59; https://doi.org/10.3390/aerospace12010059 - 16 Jan 2025
Viewed by 477
Abstract
With the rapid growth of air travel, reducing carbon emissions in aviation is imperative. Electric aircraft play a key role in achieving sustainable aviation, especially for large civil aircraft, where reducing emissions, improving the fuel efficiency, and enabling flexible power regulation are essential. [...] Read more.
With the rapid growth of air travel, reducing carbon emissions in aviation is imperative. Electric aircraft play a key role in achieving sustainable aviation, especially for large civil aircraft, where reducing emissions, improving the fuel efficiency, and enabling flexible power regulation are essential. This study proposes a dual-shaft, separated-exhaust fuel cell hybrid aircraft propulsion system (HAPS), using a solid oxide fuel cell (SOFC) to replace the conventional turbine-driven compressor. The independent speed control of the high- and low-pressure spools is realized via a power distribution system. A thermodynamic model is developed, and performance evaluations, including parametric, exergy, and sensitivity analyses, are conducted. At the design point, the system delivers 36.304 kN thrust, 16.775 g/(kN·s) specific fuel consumption, 15.931 MW SOFC power, and 54.759% SOFC efficiency. The exergy analysis highlights the optimization of components like the heat exchanger and fan to reduce energy losses. The sensitivity analysis reveals that the spool speeds and fuel utilization significantly impact the performance. The findings provide valuable insights into optimizing control strategies and offer a novel, efficient, and low-carbon power solution for aviation, supporting the industry’s transition towards sustainability. Full article
(This article belongs to the Special Issue Aircraft Electric Power System: Design, Control, and Maintenance)
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<p>Schematic diagram of a geometrical structure for the hybrid propulsion system.</p>
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<p>Thermodynamic process diagram of the hybrid propulsion system.</p>
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<p>Validation of the SOFC model under different temperatures.</p>
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<p>Calculation procedure of the hybrid propulsion system.</p>
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<p>Performance parameter contours affected by Mach number and altitude.</p>
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<p>Performance parameter contours affected by SCR and OCR.</p>
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<p>Performance parameter contours affected by SCR and OCR.</p>
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<p>Reforming results affected by SCR and OCR.</p>
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<p>Effect of fuel efficiency at different SOFC operating temperatures.</p>
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<p>Effect of fuel efficiency at different engine pressure ratios.</p>
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<p>Effect of fuel efficiency at different high-pressure spool speeds.</p>
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<p>Sankey diagram for exergy mass flow.</p>
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<p>Sensitivity analysis results between control parameters and performance parameters.</p>
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<p>Sensitivity coefficients between performance parameters.</p>
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15 pages, 3416 KiB  
Article
Assessing the Potential of Hybrid Systems with Batteries, Fuel Cells and E-Fuels for Onboard Generation and Propulsion in Pleasure Vessels
by Gianluca Pasini, Filippo Bollentini, Federico Tocchi and Lorenzo Ferrari
Energies 2024, 17(24), 6416; https://doi.org/10.3390/en17246416 - 20 Dec 2024
Viewed by 594
Abstract
Electro-fuels (E-fuels) represent a potential solution for decarbonizing the maritime sector, including pleasure vessels. Due to their large energy requirements, direct electrification is not currently feasible. E-fuels, such as synthetic diesel, methanol, ammonia, methane and hydrogen, can be used in existing internal combustion [...] Read more.
Electro-fuels (E-fuels) represent a potential solution for decarbonizing the maritime sector, including pleasure vessels. Due to their large energy requirements, direct electrification is not currently feasible. E-fuels, such as synthetic diesel, methanol, ammonia, methane and hydrogen, can be used in existing internal combustion engines or fuel cells in hybrid configurations with lithium batteries to provide propulsion and onboard electricity. This study confirms that there is no clear winner in terms of efficiency (the power-to-power efficiency of all simulated cases ranges from 10% to 30%), and the choice will likely be driven by other factors such as fuel cost, onboard volume/mass requirements and distribution infrastructure. Pure hydrogen is not a practical option due to its large storage necessity, while methanol requires double the storage volume compared to current fossil fuel solutions. Synthetic diesel is the most straightforward option, as it can directly replace fossil diesel, and should be compared with biofuels. CO2 emissions from E-fuels strongly depend on the electricity source used for their synthesis. With Italy’s current electricity mix, E-fuels would have higher impacts than fossil diesel, with potential increases between +30% and +100% in net total CO2 emissions. However, as the penetration of renewable energy increases in electricity generation, associated E-fuel emissions will decrease: a turning point is around 150 gCO2/kWhel. Full article
(This article belongs to the Section D2: Electrochem: Batteries, Fuel Cells, Capacitors)
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<p>A comparison of volumetric (<b>a</b>) and gravimetric (<b>b</b>) energy densities of E-fuels [<a href="#B10-energies-17-06416" class="html-bibr">10</a>,<a href="#B36-energies-17-06416" class="html-bibr">36</a>,<a href="#B37-energies-17-06416" class="html-bibr">37</a>].</p>
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<p>Fast Fourier transform of electric load (<b>a</b>) and sum of absolute differences of electric load with different window sizes (<b>b</b>).</p>
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<p>Standard deviation (<b>a</b>) and the sum of absolute differences (<b>b</b>) of the power delivered by the fuel cell with different values of K<sub>P</sub> and K<sub>I</sub>.</p>
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<p>Set-point index (<b>a</b>) and maximum SoC (<b>b</b>) reached with different values of K<sub>P</sub> and K<sub>I</sub>.</p>
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<p>CAPEX (<b>a</b>) and diesel consumption (<b>b</b>) of electricity production system of the configuration diesel ICE.</p>
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<p>CAPEX (<b>a</b>) and methanol consumption (<b>b</b>) of electricity production system of the configuration methanol ICE.</p>
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<p>CAPEX (<b>a</b>) and methanol consumption (<b>b</b>) of electricity production system of the configuration diesel–methanol ICE-FC.</p>
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<p>CAPEX (<b>a</b>) and hydrogen consumption (<b>b</b>) of electricity production system of the configuration diesel–hydrogen ICE-FC.</p>
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<p>CAPEX (<b>a</b>) and hydrogen consumption (<b>b</b>) of electricity production system of the configuration hydrogen FC.</p>
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<p>Total volume comparison between configurations.</p>
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<p>CO<sub>2</sub> emissions comparison between configurations considering a carbon intensity of electricity used for the synthesis of E-fuels of 258 g/kWh<sub>e</sub> (solid bars) and 100 g/kWh<sub>e</sub> (dashed bars).</p>
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19 pages, 5454 KiB  
Article
Design and Modeling of a High-Peak-Power Distributed Electric Propulsion System for a Super-STOL UAV
by Jia Zong, Zhou Zhou, Jinhong Zhu, Zhuang Shao and Sanya Sun
Drones 2024, 8(12), 761; https://doi.org/10.3390/drones8120761 - 16 Dec 2024
Viewed by 794
Abstract
Electric short takeoff and landing (eSTOL) aircraft utilize the slipstream generated by distributed propellers to significantly increase the effective lift coefficient and reduce the takeoff and landing distances. By utilizing the blown lift, eSTOL UAVs can achieve similar takeoff and landing site requirements [...] Read more.
Electric short takeoff and landing (eSTOL) aircraft utilize the slipstream generated by distributed propellers to significantly increase the effective lift coefficient and reduce the takeoff and landing distances. By utilizing the blown lift, eSTOL UAVs can achieve similar takeoff and landing site requirements as electric vertical takeoff and landing (eVTOL) UAVs, while having lower takeoff and landing energy consumption and thrust requirements. This research proposes a high-peak-power distributed electric propulsion (DEP) system model and overload design method for eSTOL UAVs to further improve the power and thrust of the propulsion system. The model considers motor temperature factors with the throttle input, which is solved through three-round iterative calculations. The experimental and simulation results indicate that the maximum error of the high-peak-power propulsion unit model without considering temperature is 19.52%, and the maximum error when considering temperature is 1.2%. The propulsion unit ground test indicates that the main factors affecting peak power are the duration of peak power and the temperature limit of the motor. Finally, the effectiveness of the propulsion system model is verified through ground tests and UAV flight tests. Full article
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<p>DEP Tandem-Wing UAV model [<a href="#B19-drones-08-00761" class="html-bibr">19</a>].</p>
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<p>Propulsion Unit model with thrust input.</p>
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<p>Propulsion unit model with throttle input.</p>
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<p>Propulsion system model with throttle input.</p>
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<p>Overload design process.</p>
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<p>Propulsion unit test bench.</p>
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<p>The experimental data of APC 12X8 propeller.</p>
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<p>The experimental data and simulation data of the motor power.</p>
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<p>The influence of motor temperature on peak power.</p>
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<p>Motor temperature versus time at different power levels.</p>
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<p>The relationship between peak power, motor temperature limit, and duration of peak power.</p>
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<p>Propulsion system ground test.</p>
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<p>The schematic diagram of the propulsion test system.</p>
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<p>The experimental data and simulation data of the motor power and thrust.</p>
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<p>UAV short takeoff process [<a href="#B19-drones-08-00761" class="html-bibr">19</a>].</p>
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<p>UAV Cable Layout Diagram.</p>
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<p>The UAV power data. (The second high-power phase in the figure is the UAV climb flight test).</p>
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22 pages, 2678 KiB  
Review
A Comprehensive Review of Optimizing Multi-Energy Multi-Objective Distribution Systems with Electric Vehicle Charging Stations
by Mahesh Kumar, Aneel Kumar, Amir Mahmood Soomro, Mazhar Baloch, Sohaib Tahir Chaudhary and Muzamil Ahmed Shaikh
World Electr. Veh. J. 2024, 15(11), 523; https://doi.org/10.3390/wevj15110523 - 14 Nov 2024
Viewed by 1078
Abstract
Electric vehicles worldwide provide numerous key advantages in the energy sector. They are advantageous over fossil fuel vehicles in many aspects: for example, they consume no fuel, are economical, and only require charging the internal batteries, which power the motor for propulsion. Thus, [...] Read more.
Electric vehicles worldwide provide numerous key advantages in the energy sector. They are advantageous over fossil fuel vehicles in many aspects: for example, they consume no fuel, are economical, and only require charging the internal batteries, which power the motor for propulsion. Thus, due to their numerous advantages, research is necessary to improve the technological aspects that can enhance electric vehicles’ overall performance and efficiency. However, electric vehicle charging stations are the key hindrance to their adoption. Charging stations will affect grid stability and may lead to altering different parameters, e.g., power losses and voltage deviation when integrated randomly into the distribution system. The distributed generation, along with charging stations with the best location and size, can be a solution that mitigates the above concerns. Metaheuristic techniques can be used to find the optimal siting and sizing of distributed generations and electric vehicle charging stations. This review provides an exhaustive review of various methods and scientific research previously undertaken to optimize the placement and dimensions of electric vehicle charging stations and distributed generation. We summarize the previous work undertaken over the last five years on the multi-objective placement of distributed generations and electric vehicle charging stations. Key areas have focused on optimization techniques, technical parameters, IEEE networks, simulation tools, distributed generation types, and objective functions. Future development trends and current research have been extensively explored, along with potential future advancement and gaps in knowledge. Therefore, at the conclusion of this review, the optimization of electric vehicle charging stations and distributed generation presents both the practical and theoretical importance of implementing metaheuristic algorithms in real-world scenarios. In the same way, their practical integration will provide the transportation system with a robust and sustainable solution. Full article
(This article belongs to the Special Issue Fast-Charging Station for Electric Vehicles: Challenges and Issues)
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<p>Optimization techniques.</p>
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<p>Objective functions.</p>
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<p>Networks used previously.</p>
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<p>Energy sources used in the literature.</p>
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<p>Electric vehicle charging infrastructure [<a href="#B68-wevj-15-00523" class="html-bibr">68</a>].</p>
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<p>Electric vehicle levels, methods, and modes [<a href="#B67-wevj-15-00523" class="html-bibr">67</a>].</p>
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<p>Electric vehicle batteries [<a href="#B67-wevj-15-00523" class="html-bibr">67</a>].</p>
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<p>Converters in electric vehicles.</p>
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<p>Categorization of the optimization methods used for concurrent DG-EVCS-SCB allocation.</p>
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27 pages, 7276 KiB  
Article
Advanced Design of Naval Ship Propulsion Systems Utilizing Battery-Diesel Generator Hybrid Electric Propulsion Systems
by Youngnam Park and Heemoon Kim
J. Mar. Sci. Eng. 2024, 12(11), 2034; https://doi.org/10.3390/jmse12112034 - 10 Nov 2024
Viewed by 1413
Abstract
As advanced sensors and weapons require high power, naval vessels have increasingly adopted electric propulsion systems. This study aims to enhance the efficiency and operability of electric propulsion systems over traditional mechanical propulsion systems by analyzing the operational profiles of modern naval vessels. [...] Read more.
As advanced sensors and weapons require high power, naval vessels have increasingly adopted electric propulsion systems. This study aims to enhance the efficiency and operability of electric propulsion systems over traditional mechanical propulsion systems by analyzing the operational profiles of modern naval vessels. Consequently, a battery-integrated generator-based electric propulsion system was selected. Considering the purpose of the vessel, a specification selection procedure was developed, leading to the design of a hybrid electric propulsion system (comprising one battery and four generators). The power management control technique of the proposed propulsion system sets the operating modes (depending on the specific fuel oil consumption of the generators) to minimize fuel consumption based on the operating load. Additionally, load distribution control rules for the generators were designed to reduce energy consumption based on the load and battery state of charge. MATLAB/Simulink was used to evaluate the proposed system, with simulation results demonstrating that it maintained the same propulsion performance as existing systems while achieving a 12-ton (22%) reduction in fuel consumption. This improvement results in cost savings and reduced carbon dioxide emissions. These findings suggest that an efficient load-sharing controller can be implemented for various vessels equipped with electric propulsion systems, tailored to their operational profiles. Full article
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<p>Design process of the proposed battery-DG hybrid electric propulsion system.</p>
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<p>Map of voyage segments.</p>
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<p>Combined propulsion and power loads on the operation modes according to load profile.</p>
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<p>Configuration of battery-DG hybrid system using PMS.</p>
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<p>Block diagram of the operation sequence for the proposed hybrid system.</p>
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<p>Overall configuration of the proposed hybrid electric propulsion system.</p>
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<p>Model of the proposed hybrid electric propulsion system.</p>
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<p>Simulation results for Generator #1.</p>
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<p>Simulation results for Generator #2.</p>
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<p>Simulation results for Generator #3.</p>
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<p>Simulation results for Generator #4.</p>
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<p>Comparation of total fuel oil consumption (FOC).</p>
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27 pages, 1862 KiB  
Article
Paving the Way for Sustainable UAVs Using Distributed Propulsion and Solar-Powered Systems
by Esteban Valencia, Cristian Cruzatty, Edwin Amaguaña and Edgar Cando
Drones 2024, 8(10), 604; https://doi.org/10.3390/drones8100604 - 21 Oct 2024
Viewed by 1247
Abstract
Hybrid systems offer optimal solutions for unmanned aerial platforms, showcasing their technological development in parallel and series configurations and providing alternatives for future aircraft concepts. However, the limited energetic benefit of these configurations is primarily due to their weight, constituting one of the [...] Read more.
Hybrid systems offer optimal solutions for unmanned aerial platforms, showcasing their technological development in parallel and series configurations and providing alternatives for future aircraft concepts. However, the limited energetic benefit of these configurations is primarily due to their weight, constituting one of the main constraints. Solar PV technology can provide an interesting enhancement to the autonomy of these systems. However, to create efficient propulsion architectures tailored for specific missions, a flexible framework is required. This work presents a methodology to assess hybrid solar-powered UAVs in distributed propulsion configurations through a two-level modeling scheme. The first stage consists of determining operational and design constraints through parametric models that estimate the baseline energetic requirements of flight. The second phase executes a nonlinear optimization algorithm tuned to find optimal propulsion configurations in terms of the degree of hybridization, number of propellers, different wing loadings, and the setup of electric distributed propulsion (eDP) considering fuel consumption as a key metric. The results of the study indicate that solar-hybrid configurations can theoretically achieve fuel savings of up to 80% compared to conventional configurations. This leads to a significant reduction in emissions during long-endurance flights where current battery technology is not yet capable of providing sustained flight. Full article
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<p>Hybrid conceptual configurations and efficiencies.</p>
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<p>Hybrid synergistic opportunities.</p>
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<p>Info-graphics of current ICE technologies for hybrid propulsion systems.</p>
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<p>Energy capacity of batteries and fuels [<a href="#B36-drones-08-00604" class="html-bibr">36</a>,<a href="#B42-drones-08-00604" class="html-bibr">42</a>].</p>
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<p>Evolution of solar PV efficiency for different technologies.</p>
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<p>Propulsion system schematic design for hybrid systems.</p>
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<p>Sizing algorithm.</p>
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<p>Mission design.</p>
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<p>Solar irradiation diagram.</p>
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<p>Aircraft aerodynamics and mission conditions: resulting curves.</p>
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<p>Parallel-hybrid DoH influence on fuel consumption.</p>
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<p>Parallel-hybrid DoH influence on fuel consumption.</p>
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<p>Parallel-hybrid SFC fraction of different configurations.</p>
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<p>Solar electric generation at 500 m.a.s.l.</p>
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<p>Energy distribution.</p>
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<p>Energy distribution.</p>
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<p>Series-solar DoH influence on fuel consumption.</p>
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<p>Series-solar DoH influence on fuel consumption.</p>
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<p>Series-solar SFC fraction of different configurations.</p>
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<p>Parallel-solar DoH influence on fuel consumption.</p>
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<p>Parallel-solar SFC fraction of different configurations.</p>
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<p>Parallel-solar SFC fraction and mission endurance.</p>
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19 pages, 4589 KiB  
Article
A Novel Robust Hybrid Control Strategy for a Quadrotor Trajectory Tracking Aided with Bioinspired Neural Dynamics
by Jianqi Li, Xin Li, Jianquan Lu, Binfang Cao and Jian Sun
Appl. Sci. 2024, 14(20), 9592; https://doi.org/10.3390/app14209592 - 21 Oct 2024
Cited by 1 | Viewed by 1048
Abstract
This paper introduces a novel hybrid control strategy for quadrotor UAVs inspired by neural dynamics. Our approach effectively addresses two common issues: the velocity jump problem in traditional backstepping control and the control signal chattering in conventional sliding mode control. The proposed system [...] Read more.
This paper introduces a novel hybrid control strategy for quadrotor UAVs inspired by neural dynamics. Our approach effectively addresses two common issues: the velocity jump problem in traditional backstepping control and the control signal chattering in conventional sliding mode control. The proposed system combines an outer-loop bioinspired backstepping controller with an inner-loop bioinspired sliding mode controller, ensuring smooth trajectory tracking even under external disturbances. We rigorously analyzed the system’s stability using Lyapunov stability theory. To validate our algorithm’s effectiveness, we conducted trajectory tracking experiments in both disturbance-free and step-disturbance conditions, comparing it with the traditional backstepping control, conventional sliding mode control, and saturated sliding mode control. The results demonstrate that our algorithm not only tracks trajectories more effectively but also significantly outperforms these methods in suppressing velocity jumps and signal chattering. Full article
(This article belongs to the Special Issue Data-Driven Control System: Methods and Applications)
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<p>Quadrotor unmanned aerial vehicle (UAV) coordinates in body fixed and inertial frame.</p>
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<p>Coordinate conversion for quadrotor unmanned aerial vehicle (UAV).</p>
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<p>Control system framework for UAV based on the bioinspired hybrid control strategy.</p>
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<p>Trajectory tracking performance. CB, traditional backstepping [<a href="#B12-applsci-14-09592" class="html-bibr">12</a>]; SMC, traditional sliding mode [<a href="#B33-applsci-14-09592" class="html-bibr">33</a>]; SAT, sliding mode with saturation [<a href="#B19-applsci-14-09592" class="html-bibr">19</a>]; BB, bioinspired backstepping; BSMC, bioinspired sliding mode. (<b>a</b>) The three-axis spatial coordinates of the UAV in the absence of disturbances. (<b>b</b>) The three-axis position information of the UAV with respect to time in the absence of disturbances.</p>
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<p>Acceleration commands. Blue, traditional backstepping and sliding mode with saturation; Red, traditional backstepping and bioinspired sliding mode; Yellow, bioinspired backstepping and bioinspired sliding mode.</p>
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<p>Thrust and torque commands. (<b>a</b>) Blue, traditional sliding mode; Red, bioinspired sliding mode. (<b>b</b>) Blue, sliding mode with saturation; Red, bioinspired sliding mode.</p>
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<p>Step-wise ascending disturbance signal.</p>
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<p>Trajectory tracking performance with disturbance. CB, traditional backstepping [<a href="#B35-applsci-14-09592" class="html-bibr">35</a>]; SMC, traditional sliding mode [<a href="#B36-applsci-14-09592" class="html-bibr">36</a>]; SAT, sliding mode with saturation [<a href="#B19-applsci-14-09592" class="html-bibr">19</a>]; BB, bioinspired backstepping; BSMC, bioinspired sliding mode. (<b>a</b>) The three-axis spatial coordinates of the UAV under disturbance conditions (<b>b</b>) The three-axis position information of the UAV with respect to time under disturbance conditions.</p>
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<p>Acceleration commands with disturbance. Blue, traditional backstepping and sliding mode with saturation; Red, traditional backstepping and bioinspired sliding mode; Yellow, bioinspired backstepping and bioinspired sliding mode.</p>
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<p>Thrust and torque commands with disturbance. (<b>a</b>) Blue, traditional sliding mode; Red, bioinspired sliding mode. (<b>b</b>) Blue, sliding mode with saturation; Red, bioinspired sliding mode.</p>
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17 pages, 1698 KiB  
Article
Comparison of Effects of Partial Discharge Echo in Various High-Voltage Insulation Systems
by Marek Florkowski
Energies 2024, 17(20), 5114; https://doi.org/10.3390/en17205114 - 15 Oct 2024
Viewed by 919
Abstract
In this article, an extension of a conventional partial discharge (PD) approach called partial discharge echo (PDE), which is applied to different classes of electrical insulation systems of power devices, is presented. Currently, high-voltage (HV) electrical insulation is attributed not only to transmission [...] Read more.
In this article, an extension of a conventional partial discharge (PD) approach called partial discharge echo (PDE), which is applied to different classes of electrical insulation systems of power devices, is presented. Currently, high-voltage (HV) electrical insulation is attributed not only to transmission and distribution grids but also to the industrial environment and emerging segments such as transportation electrification, i.e., electric vehicles, more-electric aircraft, and propulsion in maritime vehicles. This novel PDE methodology extends the conventional and established PD-based assessment, which is perceived to be one of the crucial indicators of HV electrical insulation integrity. PD echo may provide additional insight into the surface conditions and charge transport phenomena in a non-invasive way. It offers new diagnostic attributes that expand the evaluation of insulation conditions that are not possible by conventional PD measurements. The effects of partial discharge echo in various segments of insulation systems (such as cross-linked polyethylene [XLPE] power cable sections that contain defects and a twisted-pair helical coil that represents motor-winding insulation) are shown in this paper. The aim is to demonstrate the echo response on representative electrical insulating materials; for example, polyethylene, insulating paper, and Nomex. Comparisons of the PD echo decay times among various insulation systems are depicted, reflecting dielectric surface phenomena. The presented approach offers extended quantitative assessments of the conditions of HV electrical insulation, including its detection, measurement methodology, and interpretation. Full article
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<p>Chopped sequence formation based on the superposition of the base waveform and the delay time for PD echo excitation. <span class="html-italic">T</span>—base waveform period; <span class="html-italic">t<sub>ep</sub></span>—duration of the epoch; <span class="html-italic">t<sub>d</sub></span>—delay time duration. Definitions of partial discharge echo attributes: <span class="html-italic">τ<sub>e</sub></span>—echo decay time constant; <span class="html-italic">t<sub>e_dur</sub></span>—duration of the echo clusters up to the last discharge event within the delay time; <span class="html-italic">Q<sub>max</sub></span> and <span class="html-italic">Q<sub>emax</sub></span>—max discharge magnitude within the base waveform and in the echo part, respectively; <span class="html-italic">T</span><sub>0</sub>—transition point.</p>
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<p>Test objects used in PD echo experiments: (<b>a</b>) embedded void geometry; (<b>b</b>) section of XLPE power cable containing a defect; (<b>c</b>) twisted-pair helical coil (representing motor-winding insulation). The zoomed-in view shows the contact spot between adjacent wires containing an air gap.</p>
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<p>Setup and instrumentation for PD echo detection and acquisition based on chopped sequence in various test objects (TO): <span class="html-italic">f<sub>V</sub></span>—HV excitation frequency; <span class="html-italic">f<sub>S</sub></span>—acquisition synchronization frequency; <span class="html-italic">C<sub>c</sub></span>—coupling capacitor; <span class="html-italic">CT</span>—wide-band current transformer; FPA—filter and preamplifier; <span class="html-italic">Z<sub>m</sub></span>—measuring impedance; <span class="html-italic">Z</span><sub>1</sub>, <span class="html-italic">Z</span><sub>2</sub>—compensated divider; <span class="html-italic">Z</span>—filtering and protection impedance.</p>
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<p>Visualization of chopped sequence and PD acquisition window positioning. Relationship between base waveform frequency <span class="html-italic">f<sub>V</sub></span> (50 Hz) and corresponding acquisition frequency <span class="html-italic">f<sub>S</sub></span>. For a fill factor of <span class="html-italic">ff</span> = 1:2 and <span class="html-italic">ff</span> = 1:16, <span class="html-italic">f<sub>s</sub></span> yielded 25 and 3.125 Hz, respectively.</p>
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<p>Measurement results of partial discharge echo in various specimens: (<b>a</b>) polyethylene (PE) at 16 kV [<a href="#B58-energies-17-05114" class="html-bibr">58</a>]; (<b>b</b>) insulating paper (PK) at 16 kV; (<b>c</b>) Nomex at 16 kV; (<b>d</b>) XLPE power cable at 18 kV; (<b>e</b>) XLPE power cable for <span class="html-italic">ff</span> = 1:16 and <span class="html-italic">t<sub>d</sub></span> = 320 ms; (<b>f</b>) helical coil representing motor-winding at 650 V; all measurements except (<b>e</b>) are for <span class="html-italic">ff</span> = 1:2 and <span class="html-italic">t<sub>d</sub></span> = 20 ms.</p>
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<p>Approximation of PD echo envelope using an exponential function to evaluate the time constant of the echo <span class="html-italic">τ<sub>e</sub></span> for the following specimens: (<b>a</b>) polyethylene (PE) [<a href="#B58-energies-17-05114" class="html-bibr">58</a>]; (<b>b</b>) insulating paper (PK); (<b>c</b>) Nomex; (<b>d</b>) XLPE power cable; (<b>e</b>) helical coil representing motor-winding (all measurements for <span class="html-italic">ff</span> = 1:2 and <span class="html-italic">t<sub>d</sub></span> = 20 ms).</p>
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22 pages, 7282 KiB  
Article
High-Precision Forward Modeling of Controlled Source Electromagnetic Method Based on Weighted Average Extrapolation Method
by Zhi Yang, Jingtian Tang, Xiangyu Huang, Minsheng Yang, Yishu Sun and Xiao Xiao
Electronics 2024, 13(19), 3827; https://doi.org/10.3390/electronics13193827 - 27 Sep 2024
Viewed by 604
Abstract
To achieve high-precision calculation of the electromagnetic field of layered media and to ensure that the apparent resistivity calculation and sensitivity are not affected by numerical errors, this paper implements high-precision calculation of the layered electromagnetic field based on the weighted average (WA) [...] Read more.
To achieve high-precision calculation of the electromagnetic field of layered media and to ensure that the apparent resistivity calculation and sensitivity are not affected by numerical errors, this paper implements high-precision calculation of the layered electromagnetic field based on the weighted average (WA) extrapolation method. Firstly, the 1D electromagnetic field expression of an arbitrary attitude field source is obtained by using the magnetic vector potential; then, the WA extrapolation technique is introduced to achieve the high-precision and fast solution of the Hankel transform, and the effects of the number of Gaussian points and the number of integration intervals on the accuracy are investigated. The theoretical model test shows that, compared with the open-source Dipole1D, the algorithm proposed in this paper has wider adaptability, and can achieve high-precision calculation of electric and magnetic dipole sources with higher efficiency. Compared with the epsilon algorithm studied by previous researchers, the WA extrapolation method proposed in this article can improve the convergence rate by approximately 20% under the same conditions. It can obtain high-precision numerical solutions with less integration time. The relative accuracy can reach the order 1010, and its computational efficiency is significantly better than the existing epsilon algorithm. Finally, we used two cases of marine controlled source electromagnetic method to show the application. The sensitivity and Poynting vectors are calculated, which provides a technical tool for a deep understanding of physical mechanisms in layered media. Full article
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<p>Schematic diagram of layered model.</p>
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<p>Schematic diagram of the layered model.</p>
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<p>Horizontal electric dipole (r = 1000 m) electromagnetic field component comparison results. (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mi>E</mi> <mi>x</mi> </msub> </mrow> </semantics></math> component; (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mi>E</mi> <mi>y</mi> </msub> </mrow> </semantics></math> component; (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mi>E</mi> <mi>z</mi> </msub> </mrow> </semantics></math> component; (<b>d</b>) <math display="inline"><semantics> <mrow> <msub> <mi>H</mi> <mi>x</mi> </msub> </mrow> </semantics></math> component; (<b>e</b>) <math display="inline"><semantics> <mrow> <msub> <mi>H</mi> <mi mathvariant="normal">y</mi> </msub> </mrow> </semantics></math> component; (<b>f</b>) <math display="inline"><semantics> <mrow> <msub> <mi>H</mi> <mi>z</mi> </msub> </mrow> </semantics></math> component.</p>
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<p>Relative error of electric dipole at r = 100 m. (<b>a</b>) E<sub>x</sub> accuracy; (<b>b</b>) H<sub>z</sub> accuracy.</p>
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<p>Relative error of electric dipole at r = 1000 m. (<b>a</b>) E<sub>x</sub> accuracy; (<b>b</b>) H<sub>z</sub> accuracy.</p>
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<p>Comparison of acceleration effects of extrapolation methods for electric dipole sources. (<b>a</b>) E<sub>x</sub> component accuracy; (<b>b</b>) H<sub>z</sub> component accuracy.</p>
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<p>Relative error between the numerical integration solution and the analytical solution for the five components E<sub>x</sub>, E<sub>y</sub>, H<sub>x</sub>, H<sub>y</sub>, H<sub>z</sub> generated by the VMD.</p>
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<p>Analysis of vertical magnetic dipole accuracy at r = 100 m. (<b>a</b>) E<sub>x</sub> accuracy; (<b>b</b>) H<sub>z</sub> accuracy.</p>
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<p>Analysis of vertical magnetic dipole accuracy at r = 1000 m. (<b>a</b>) E<sub>x</sub> accuracy; (<b>b</b>) H<sub>z</sub> accuracy.</p>
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<p>Comparison of acceleration effects of magnetic dipole source extrapolation. (<b>a</b>) E<sub>x</sub> accuracy; (<b>b</b>) H<sub>z</sub> accuracy.</p>
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<p>Sensitivity distribution at different depths (<math display="inline"><semantics> <mo>∗</mo> </semantics></math> represents the position of the transmission source, <math display="inline"><semantics> <mo>⊳</mo> </semantics></math> represents the position of the receiver).</p>
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<p>Sensitivity distribution at different depths (<math display="inline"><semantics> <mo>∗</mo> </semantics></math> represents the position of the transmission source, <math display="inline"><semantics> <mo>⊳</mo> </semantics></math> represents the position of the receiver).</p>
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<p>K-model energy flow density.</p>
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21 pages, 6192 KiB  
Article
Optimizing the Landing Stability of Blended-Wing-Body Aircraft with Distributed Electric Boundary-Layer Ingestion Propulsors through a Novel Thrust Control Configuration
by Mingxing Yu, Zhi Tao, Haiwang Li and Peng Tang
Appl. Sci. 2024, 14(18), 8546; https://doi.org/10.3390/app14188546 - 23 Sep 2024
Viewed by 1345
Abstract
The imperative for energy conservation and environmental protection has led to the development of innovative aircraft designs. This study explored a novel thrust control configuration for blended-wing-body (BWB) aircraft with distributed electric boundary-layer ingestion (BLI) propulsors, addressing the issues of sagging and altitude [...] Read more.
The imperative for energy conservation and environmental protection has led to the development of innovative aircraft designs. This study explored a novel thrust control configuration for blended-wing-body (BWB) aircraft with distributed electric boundary-layer ingestion (BLI) propulsors, addressing the issues of sagging and altitude loss during landing. The research focused on a small-scale BWB demonstrator equipped with six BLI fans, each with a 90 mm diameter. Various thrust control configurations were evaluated to achieve significant thrust reduction while maintaining lift, including dual-layer sleeve, separate flap-type, single-stage linkage flap-type, and dual-stage linkage flap-type configurations. The separate flap-type configuration was tested through ground experiments. Control experiments were conducted under three different experimental conditions as follows: deflection of the upper cascades only, deflection of the lower cascades only, and symmetrical deflection of both cascades. For each condition, the deflection angles tested were 0°, 10°, 20°, 30°, 40°, 50°, and 60°. The thrust reductions observed for these three conditions were 0%, 37.5%, and 27.5% of the maximum thrust, respectively, without additional changes in the pitch moment. A combined thrust adjustment method maintaining a zero pitch moment demonstrated a linear thrust reduction to 20% of its initial value. The experiment concluded that the novel thrust control configuration effectively adjusted thrust without altering the BLI fans’ rotation speed, solving the coupled lift–thrust problem and enhancing BWB landing stability. Full article
(This article belongs to the Section Aerospace Science and Engineering)
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<p>Sagging problem of BWB aircraft caused by short lever arms.</p>
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<p>Schematic of BWB aircraft with distributed electric BLI propulsors.</p>
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<p>Schematic diagram of a dual-layer sleeve thrust control configuration: (<b>a</b>) normal thrust and (<b>b</b>) reverse thrust.</p>
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<p>Components and motion of a dual-layer sleeve thrust control configuration.</p>
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<p>Schematic diagram of a separate flap-type thrust control configuration.</p>
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<p>Components and motion of a separate flap-type thrust control configuration: (<b>a</b>) normal thrust and (<b>b</b>) reverse thrust.</p>
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<p>Schematic diagram of a single-stage linkage flap-type thrust control configuration.</p>
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<p>Components and motion of a single-stage linkage flap-type thrust control configuration.</p>
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<p>Schematic diagram of a dual-stage linkage flap-type thrust control configuration.</p>
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<p>Components and motion of a dual-stage linkage flap-type thrust control configuration.</p>
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<p>Schematic diagram of BWB aircraft with novel thrust control configuration.</p>
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<p>Force model of BWB aircraft.</p>
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<p>Schematic diagram of the experimental setup for BWB aircraft with novel thrust control configuration.</p>
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<p><span class="html-italic">C<sub>L</sub></span> variation with deflection angles in symmetrical cascade deflection.</p>
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<p><span class="html-italic">C<sub>M</sub></span> variation with deflection angles in symmetrical cascade deflection.</p>
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<p><span class="html-italic">T</span> variation with deflection angles in symmetrical cascade deflection.</p>
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<p><span class="html-italic">C<sub>L</sub></span> variation with deflection angles in upper cascade deflection.</p>
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<p><span class="html-italic">C<sub>M</sub></span> variation with deflection angles in upper cascade deflection.</p>
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<p><span class="html-italic">T</span> variation with deflection angles in upper cascade deflection.</p>
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<p><span class="html-italic">C<sub>L</sub></span> variation with deflection angles in lower cascade deflection.</p>
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<p>C<sub>M</sub> variation with deflection angles in lower cascade deflection.</p>
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<p><span class="html-italic">T</span> variation with deflection angles in lower cascade deflection.</p>
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<p>Deflection angle combinations for zero pitch moment (<span class="html-italic">C<sub>M</sub></span> = 0) in both cascades.</p>
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<p>Variation in <span class="html-italic">C<sub>L</sub></span> and <span class="html-italic">T</span> with deflection angles under constant-pitch-moment conditions.</p>
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19 pages, 9851 KiB  
Article
Study on the Improvement of Theoretical and Electric Field Simulation Methods for the Accurate Prediction of FEEP Thruster Performance
by Jeongsik Shin, Kyun Ho Lee, Jungwon Kuk and Han Seo Ko
Aerospace 2024, 11(9), 716; https://doi.org/10.3390/aerospace11090716 - 2 Sep 2024
Viewed by 1071
Abstract
In this study, we investigate and propose an improved theoretical method to more accurately predict the performance of a field-emission electric propulsion (FEEP) thruster with its complex configuration. We identify critical flaws in the previous theoretical methods and derive corrected equations. Additionally, we [...] Read more.
In this study, we investigate and propose an improved theoretical method to more accurately predict the performance of a field-emission electric propulsion (FEEP) thruster with its complex configuration. We identify critical flaws in the previous theoretical methods and derive corrected equations. Additionally, we define and implement the overall half angle of the Taylor cone to account for variations in the Taylor cone’s half angle depending on the applied voltage. Next, we also establish an improved method of the electric filed simulation in a three-dimensional domain to accurately predict a trajectory of extracted ions and a resulting spatial beam distribution of the FEEP thruster by incorporating a configuration of the Taylor cone with the estimated overall half angle from the results of the present theoretical method. Through comparison with the experimental measurements, we found that the present improved methods for theoretical and electric field simulations can yield more accurate predictions than those of the previous methods, especially for higher V and Iem regimes, which correspond to the actual operating conditions of the FEEP thruster. Consequently, we anticipate that the proposed methods can enhance the reliability and efficiency of the design process by accurately predicting performance when developing the new FEEP thruster with its non-symmetric complex configuration to match specific thrust or spatial beam requirements. Full article
(This article belongs to the Special Issue Space Propulsion: Advances and Challenges (2nd Edition))
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<p>A schematic of the FEEP thruster.</p>
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<p>Force distribution on Taylor cone [<a href="#B14-aerospace-11-00716" class="html-bibr">14</a>] and formation of Taylor cone [<a href="#B15-aerospace-11-00716" class="html-bibr">15</a>].</p>
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<p>Diagrams of three emitter types of FEEP thrusters [<a href="#B16-aerospace-11-00716" class="html-bibr">16</a>].</p>
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<p>Schematics of Taylor cone configurations for different emitter tips. (<b>a</b>) A capillary emitter; (<b>b</b>) a needle emitter.</p>
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<p>Comparison of previous theoretical method with experiment [<a href="#B11-aerospace-11-00716" class="html-bibr">11</a>].</p>
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<p>A flowchart of the present improved theoretical method.</p>
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<p>Performance comparisons of the improved theoretical method for a needle emitter. (<b>a</b>) Predictions of <span class="html-italic">I<sub>em</sub></span> − <span class="html-italic">V</span> relation [<a href="#B11-aerospace-11-00716" class="html-bibr">11</a>]; (<b>b</b>) relative errors for predicted <span class="html-italic">I<sub>em</sub></span> − <span class="html-italic">V</span> relations; (<b>c</b>) predictions of <span class="html-italic">F</span> − <span class="html-italic">V</span> relation; (<b>d</b>) predictions of <span class="html-italic">I<sub>sp</sub></span> − <span class="html-italic">V</span> relation.</p>
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<p>Performance comparisons of the improved theoretical method for a needle emitter. (<b>a</b>) Predictions of <span class="html-italic">I<sub>em</sub></span> − <span class="html-italic">V</span> relation [<a href="#B11-aerospace-11-00716" class="html-bibr">11</a>]; (<b>b</b>) relative errors for predicted <span class="html-italic">I<sub>em</sub></span> − <span class="html-italic">V</span> relations; (<b>c</b>) predictions of <span class="html-italic">F</span> − <span class="html-italic">V</span> relation; (<b>d</b>) predictions of <span class="html-italic">I<sub>sp</sub></span> − <span class="html-italic">V</span> relation.</p>
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<p>Performance comparisons of the improved theoretical method for a porous emitter. (<b>a</b>) Predictions of <span class="html-italic">I<sub>em</sub></span> − <span class="html-italic">V</span> relation [<a href="#B11-aerospace-11-00716" class="html-bibr">11</a>,<a href="#B13-aerospace-11-00716" class="html-bibr">13</a>]; (<b>b</b>) relative errors for predicted <span class="html-italic">I<sub>em</sub></span> − <span class="html-italic">V</span> relations; (<b>c</b>) predictions of <span class="html-italic">F</span> − <span class="html-italic">V</span> relation; (<b>d</b>) predictions of <span class="html-italic">I<sub>sp</sub></span> − <span class="html-italic">V</span> relation.</p>
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<p>A flowchart of improved electric field simulation method.</p>
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<p>A 3-D configuration of the improved electric field simulation model.</p>
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<p>Electric field intensity results for a needle emitter using the present method. (<b>a</b>) Electric field intensity in the simulation region with an emitter and an extractor (<span class="html-italic">V</span> = 7 kV); (<b>b</b>) electric field intensity on Taylor cone and emitter surfaces (<span class="html-italic">V</span> = 7 kV); (<b>c</b>) average electric field intensity on Taylor cone surface (<span class="html-italic">V</span> = 0–12 kV).</p>
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<p>Performance comparisons of the improved electric field simulation method for a needle emitter. (<b>a</b>) Predictions of <span class="html-italic">I<sub>em</sub></span> − <span class="html-italic">V</span> relation [<a href="#B11-aerospace-11-00716" class="html-bibr">11</a>]; (<b>b</b>) predictions of <span class="html-italic">F</span> − <span class="html-italic">V</span> relation; (<b>c</b>) predictions of <span class="html-italic">I<sub>sp</sub></span> − <span class="html-italic">V</span> relation.</p>
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<p>Performance comparisons of the improved electric field simulation method for a needle emitter. (<b>a</b>) Predictions of <span class="html-italic">I<sub>em</sub></span> − <span class="html-italic">V</span> relation [<a href="#B11-aerospace-11-00716" class="html-bibr">11</a>]; (<b>b</b>) predictions of <span class="html-italic">F</span> − <span class="html-italic">V</span> relation; (<b>c</b>) predictions of <span class="html-italic">I<sub>sp</sub></span> − <span class="html-italic">V</span> relation.</p>
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<p>Performance comparisons of the improved electric field simulation method for a porous emitter. (<b>a</b>) Predictions of <span class="html-italic">I<sub>em</sub></span> − <span class="html-italic">V</span> relation [<a href="#B11-aerospace-11-00716" class="html-bibr">11</a>,<a href="#B13-aerospace-11-00716" class="html-bibr">13</a>]; (<b>b</b>) predictions of <span class="html-italic">F</span> − <span class="html-italic">V</span> relation; (<b>c</b>) predictions of <span class="html-italic">I<sub>sp</sub></span> − <span class="html-italic">V</span> relation.</p>
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<p>Performance comparisons of the improved electric field simulation method for a porous emitter. (<b>a</b>) Predictions of <span class="html-italic">I<sub>em</sub></span> − <span class="html-italic">V</span> relation [<a href="#B11-aerospace-11-00716" class="html-bibr">11</a>,<a href="#B13-aerospace-11-00716" class="html-bibr">13</a>]; (<b>b</b>) predictions of <span class="html-italic">F</span> − <span class="html-italic">V</span> relation; (<b>c</b>) predictions of <span class="html-italic">I<sub>sp</sub></span> − <span class="html-italic">V</span> relation.</p>
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30 pages, 8447 KiB  
Review
Aircraft Electrification: Insights from a Cross-Sectional Thematic and Bibliometric Analysis
by Raj Bridgelall
World Electr. Veh. J. 2024, 15(9), 384; https://doi.org/10.3390/wevj15090384 - 24 Aug 2024
Cited by 1 | Viewed by 1093
Abstract
Electrifying aircraft, a crucial advancement in the aviation industry, aims to cut pollutive emissions and boost energy efficiency. Traditional aircraft depend on fossil fuels, which contribute significantly to greenhouse gas emissions and environmental pollution. Despite progress in electric propulsion and energy storage technologies, [...] Read more.
Electrifying aircraft, a crucial advancement in the aviation industry, aims to cut pollutive emissions and boost energy efficiency. Traditional aircraft depend on fossil fuels, which contribute significantly to greenhouse gas emissions and environmental pollution. Despite progress in electric propulsion and energy storage technologies, challenges such as low energy density and integration issues persist. This paper provides a comprehensive thematic and bibliometric analysis to map the research landscape in aircraft electrification, identifying key research themes, influential contributors, and emerging trends. This study applies natural language processing to unstructured bibliographic data and cross-sectional statistical methods to analyze publications, citations, and keyword distributions across various categories related to aircraft electrification. The findings reveal significant growth in research output, particularly in energy management and multidisciplinary design analysis. Collaborative networks highlight key international partnerships, with the United States and China being key research hubs, while citation metrics highlight the impact of leading researchers and institutions in these countries. This study provides valuable insights for researchers, policymakers, and industry stakeholders, guiding future research directions and collaborations. Full article
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<p>The analytical workflow developed in this study.</p>
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<p>Bigram word cloud within categories.</p>
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<p>Bigram word frequency within categories.</p>
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<p>Author keyword cloud within categories.</p>
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<p>Top five author keywords within categories.</p>
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<p>(<b>a</b>) Term co-occurrence and clusters, and (<b>b</b>) highlighted example of “composite material”.</p>
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<p>Number of terms as a function of their minimum number of occurrences in the corpus.</p>
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<p>Publications by (<b>a</b>) year, (<b>b</b>) category, (<b>c</b>) author count distribution, and (<b>d</b>) category.</p>
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<p>Publications by top 10 (<b>a</b>) lead authors, (<b>b</b>) countries, (<b>c</b>) affiliations, and (<b>d</b>) journals.</p>
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<p>Citations (<b>a</b>) of top 10 lead authors, (<b>b</b>) of the lead author in top 10 countries, (<b>c</b>) of the lead author in top 10 affiliations, and (<b>d</b>) in category by year.</p>
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<p>Authorship collaborations across countries.</p>
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<p>Citations (<b>a</b>) by year, (<b>b</b>) per publication by year, (<b>c</b>) per publication by country, and (<b>d</b>) per publication by affiliation.</p>
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<p>(<b>a</b>) Citations in category, (<b>b</b>) citations per publication in category, (<b>c</b>) citations per publication in category, and (<b>d</b>) publications in category by top 10 countries.</p>
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21 pages, 6524 KiB  
Article
Optimization of Fuel Consumption by Controlling the Load Distribution between Engines in an LNG Ship Electric Propulsion Plant
by Siniša Martinić-Cezar, Zdeslav Jurić, Nur Assani and Branko Lalić
Energies 2024, 17(15), 3718; https://doi.org/10.3390/en17153718 - 28 Jul 2024
Cited by 1 | Viewed by 1490
Abstract
Due to growing environmental concerns and stringent emissions regulations, optimizing the fuel consumption of marine propulsion systems is crucial. This work deals with the potential in an LNG ship propulsion system to reduce fuel consumption through controlled load distribution between engines in Dual-Fuel [...] Read more.
Due to growing environmental concerns and stringent emissions regulations, optimizing the fuel consumption of marine propulsion systems is crucial. This work deals with the potential in an LNG ship propulsion system to reduce fuel consumption through controlled load distribution between engines in Dual-Fuel Diesel Electric (DFDE) plant. Based on cyclical data acquisition measured onboard and using an optimization model, this study evaluates different load distribution strategies between setups according to the optimization model results and automatic (equal) operation to determine their effectiveness in improving fuel efficiency. The analysis includes scenarios with different fuel types, including LNG, MDO and HFO, at different engine loads. The results indicate that load distribution adjustment based on the optimization model results significantly improves fuel efficiency compared to conventional methods of uniform load distribution controlled by power management systems in almost all load intervals. This research contributes to the maritime industry by demonstrating that strategic load management can achieve significant fuel savings and reduce environmental impact, which is in line with global sustainability goals. This work not only provides a framework for the implementation of more efficient energy management systems on LNG vessels, but also sets a benchmark for future innovations in maritime energy optimization as well as in the view of exhaust emission reduction. Full article
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<p>Power distribution diagram.</p>
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<p>Fuel consumption for three types of fuel.</p>
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<p>SFOC on HFO.</p>
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<p>SFOC on MDO.</p>
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<p>SFOC on LNG.</p>
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<p>Optimization model flow chart.</p>
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<p>Comparative analysis of HFO consumption for the power range 25,000–29,000 kW.</p>
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<p>Load distribution (%) by engines for the power range 25,000–29,000 kW.</p>
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<p>Load distribution between the engines and HFO consumption at 10,000 kW load demand.</p>
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<p>Load distribution between the engines and HFO consumption at 23,000 kW load demand.</p>
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<p>Comparative analysis of MDO consumption for the power range 25,000–29,000 kW.</p>
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<p>Load distribution (%) by engines for the power range 25,000–29,000 kW.</p>
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<p>Load distribution between the engines and MDO consumption at 10,000 kW load demand.</p>
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<p>Load distribution between the engines and MDO consumption at 23,000 kW load demand.</p>
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<p>Comparative analysis of LNG consumption for the power range 25,000–29,000 kW.</p>
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<p>Load distribution (%) by engines for the power range 25,000–29,000 kW.</p>
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<p>Load distribution between the engines and LNG consumption at 10,000 kW load demand.</p>
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<p>Load distribution between the engines and LNG consumption at 23,000 kW load demand.</p>
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23 pages, 3775 KiB  
Article
Advanced Scale-Propeller Design Using a MATLAB Optimization Code
by Stephen D. Prior and Daniel Newman-Sanders
Appl. Sci. 2024, 14(14), 6296; https://doi.org/10.3390/app14146296 - 19 Jul 2024
Viewed by 1493
Abstract
This study investigated the efficiency of scale-propellers, typically used on small drones. A scale-propeller is accepted as having a diameter of 7 to 21 inches. Recent special operations has demonstrated the utility of relatively small, low-cost first-person view (FPV) drones, which are attritable. [...] Read more.
This study investigated the efficiency of scale-propellers, typically used on small drones. A scale-propeller is accepted as having a diameter of 7 to 21 inches. Recent special operations has demonstrated the utility of relatively small, low-cost first-person view (FPV) drones, which are attritable. This investigation outlines the development of a MATLAB optimisation code, based on minimum induced loss propeller theory, which calculates the optimal chord and twist distribution for a chosen propeller operating in known flight conditions. The MATLAB code includes a minimum Reynolds number functionality, which provides the option to alter the chord distribution to ensure the entire propeller is operating above a set threshold value of Reynolds (>100,000), as this has been found to be a transition point between low and high section lift-to-drag ratios. Additional functions allow plotting of torque and thrust distributions along the blade. The results have been validated on experimental data taken from an APC ‘Thin Electric’ 10” × 7” propeller, where it was found that both the chord and twist distributions were accurately modelled. The MATLAB code resulted in a 16% increase in the maximum propulsive efficiency. Further work will investigate a direct interface to SolidWorks to aid rapid propeller manufacturing capability. Full article
Show Figures

Figure 1

Figure 1
<p>Propeller peak efficiency increase with pitch/diameter ratio (UUIC Database) [<a href="#B2-applsci-14-06296" class="html-bibr">2</a>]. Note: This data has been extracted and transformed by the authors to produce this graph.</p>
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<p>Example of a small Y6 drone (HALO), winner of the DARPA UAVForge challenge 2012.</p>
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<p>NACA0012 airfoil profile (JavaFoil, 2024) [<a href="#B27-applsci-14-06296" class="html-bibr">27</a>].</p>
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<p>NACA3414 airfoil profile (JavaFoil, 2024) [<a href="#B27-applsci-14-06296" class="html-bibr">27</a>].</p>
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<p>Example efficiency curve of an APC 10” × 7” Thin Electric propeller [<a href="#B2-applsci-14-06296" class="html-bibr">2</a>].</p>
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<p>Typical maximum section lift/drag ratios versus Reynolds numbers [<a href="#B13-applsci-14-06296" class="html-bibr">13</a>]. Note the transition at approximately 100,000 Re for smooth airfoils.</p>
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<p>Optimal chord distribution for a propeller with design inputs of: 20-inch diameter, a design advance ratio of 0.59, two-blades, a shaft power of 3 kW, zero angle of attack, standard density of 1.225 kg/m<sup>3</sup> and a lift-to-drag ratio of 20.</p>
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<p>Computation time for MATLAB program with varying number of blade elements. The processor of the system used for this computation is an Intel (R) Core (TM) i3-6006U CPU @ 2.00 GHz, 1992 MHz.</p>
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<p>Radial thrust distribution along a propeller blade with design inputs of: 20-inch diameter, a design advance ratio of 0.59, 2-blades, a shaft power of 3 kW, zero angle of attack, standard density of 1.225 kg/m<sup>3</sup> and a lift-to-drag ratio of 20.</p>
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<p>Radial Reynolds number distribution along a 10-inch and 20-inch propeller blade with design inputs of: velocity of 10 m/s, 2000 RPM, two blades and a hub radius of 0.15.</p>
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<p>Flow chart of MATLAB program which outputs optimal propeller geometry.</p>
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<p>Pop-up window from MATLAB code, in which user can provide required inputs.</p>
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<p>Plot of chord distribution for MATLAB program output and APC ’Thin Electric’ 10” × 7” propeller [<a href="#B2-applsci-14-06296" class="html-bibr">2</a>].</p>
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<p>Plot of twist distribution for MATLAB program output and APC ’Thin Electric’ 10” × 7” propeller [<a href="#B2-applsci-14-06296" class="html-bibr">2</a>].</p>
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<p>Plot of Reynolds number distribution for MATLAB program output and APC ’Thin Electric’ 10” × 7” propeller [<a href="#B2-applsci-14-06296" class="html-bibr">2</a>].</p>
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