Year: 2026
Type: article
Abstract: This study presents a systematic approach to optimising drone airframe geometry with a specific focus on enhancing flight dynamics for racing applications. The proposed method integrates an elitist multi-objective evolutionary algorithm with mathematical procedures of varying natures, encapsulated within an algorithmic system of a simulation platform. The framework combines implicit numerical methods with a custom implementation to seamlessly interact across multiple simulation environments. This approach ensures the mathematical model closely reflects real-world conditions, providing reliable optimisation outcomes. The preliminary findings suggest that optimised airframe geometries lead to notable advancements in thrust efficiency and overall performance. Symmetrical and non-symmetrical designs exhibit distinct benefits, highlighting the potential for significant improvements in trajectory precision and flight efficiency. These results emphasise the practical impact of shape design and dynamic optimisation in drone airframes, offering valuable insights for developing high-performance racing drones.
Source: The Aeronautical Journal
Institutions: Cranfield University, Universitat Politècnica de València
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,550
Funder: Agencia Estatal de Investigación
OpenAlex ID: W7140078674