This paper presents the use of a genetic algorithm to optimize the size and cruise speed of a solar-powered unmanned aerial vehicle named Xihe. A conceptual aerodynamic configuration design is conducted first to obtain the initial size of the aircraft and the performance parameters. The optimization process then searches for optimal solutions for minimum energy operation. To minimize the number of decision variables, the aspect ratio of the wing and the fuselage design are fixed during optimization. The mass of the Xihe aircraft is then parameterized as a function of two performance parameters: wing reference area and cruise speed. With the parameterization results, a fitness function that links the optimization problem and the genetic algorithm is then established. The genetic algorithm searches for the optimal results for minimum energy operation. This optimization process reduces the referenced wing area of the Xihe aircraft from 5:63 m 2 in the conceptual design to 4:91 m 2 , which allows the reduction of the solar cell panel by 12.79%, reducing the costs. Optimization reduces the mass of the aircraft from 24.96 to 22.47 kg: a 9.98% reduction. The cost of the complex materials used would be less than originally required, and the cruise speed would increase from 10.93 to 11:23 m=s (the cruise speed for minimum power consumption).
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