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|Title:||Theoretical analysis and optimization of the performance of a hybrid engine||Authors:||Ho, Xiu Ting||Keywords:||Engineering::Mechanical engineering::Energy conservation||Issue Date:||2020||Publisher:||Nanyang Technological University||Project:||A196||Abstract:||Analyzing the amount of fuel in the hybrid engine and battery cells helps to optimize the overall performance of the drone. Research has shown that different combinations of the amount in fuel level and battery cells will result in various outputs. This paper aims to determine the mathematical optimization of the flight time after collecting all the possible combination outcomes. Building codes with all the assumptions and constraints, the State of Charge (SoC) curve and the available fuel curve demonstrates the relationship between both the hybrid engine and battery cells, and the flight time. In this context, the hybrid engine begins to charge the battery pack when the energy level reaches below a certain value. When the hybrid engine begins to operate, the available fuel curve decreases accordingly. This code also demonstrates that when the load demands a higher power to supply and yet battery cells alone could not support, the hybrid engine automatically provides power to the load. Based on the literature review done on hybrid engine and battery pack, configurations in the entire system of the drone and the internal configuration in battery pack will contribute to a huge difference in the outcome. It is proven that with a lower power load, the drone can fly thrice the amount of flight time as compared to the drone which requires a higher power load. This result indicates that a lower power load has an impact on the total overall flight time. Hence, it is recommended to have a smaller power load in order to save energy consumption of the battery pack and hybrid engine. A future simulation is also advised to be carried out for a parallel hybrid system as a comparison with the series hybrid system. This is to determine which configuration gives the best optimization in terms of endurance. Translating the code to simulation is also another factor to improve effectiveness and visualization||URI:||https://hdl.handle.net/10356/138777||Fulltext Permission:||restricted||Fulltext Availability:||With Fulltext|
|Appears in Collections:||MAE Student Reports (FYP/IA/PA/PI)|
Updated on Jan 31, 2023
Updated on Jan 31, 2023
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