Onboard Aircraft Weight and Balance Estimator for Fuel Optimization

Abstract

Traditional aircraft loading relies on manual weight estimations that introduce safety risks and fuel inefficiencies due to inaccurate weight and balance calculations. To address these critical operational challenges, this study develops an onboard aircraft weight and balance estimator designed to provide real-time weight detection and center of gravity analysis for aviation fuel optimization. The theoretical framework integrates embedded load-measurement principles with agile system development, connecting a microcontroller-based weight sensor directly to a cloud database and a web-based pilot dashboard. Using an agile software prototyping design, the system was developed at the Faculty of Information Sciences and Engineering, Management and Science University, by integrating cost-effective load cell sensors with an Arduino microcontroller and a Firebase database. The prototype was subsequently tested by a sample of 30 participants, including active pilots and airline staff, who evaluated the accuracy of weight readings, database inputs, and loadsheet export features. The evaluation results demonstrated that the load cell sensors achieved a high weight estimation accuracy of 95% with a minor calibration deviation of 0.2 kilograms. Furthermore, the Firebase Realtime Database successfully synchronized weight data and generated flight loadsheets with a transmission success rate of 90 % and a low latency of 2 seconds. However, the automatic fuel estimation module showed a non-significant correlation with manual flight planning systems on complex route structures [correlation coefficient = 0.0617, p > 0.05], representing a limitation in dynamic path profiles. The originality of this work lies in the development of a cost-effective, open-source hardware and cloud database architecture that automates general aviation weight estimation and loadsheet generation. Practically, this system provides general aviation operators with a reliable tool to reduce flight preparation times, prevent loading accidents, and optimize fuel loading through precise real-time loadsheets.