Real time estimation of VTOL vehicle weight using standard on-board sensors

Abstract

This paper presents an effective method for real time computation of the gross weight of vertical take-off and landing aircraft (specifically, a tiltrotor). Accurate in-flight estimation of gross weight allows computing fatigue life of vehicle’s components and optimizing inspection or replacement of vehicle’s life-limited parts, in order to reduce operating cost and enhance safety. Several techniques for determining gross weight are available in the literature, which mainly rely on hover performance charts, neural networks, and model based augmented state observers. The method presented in this paper estimates gross weight by solving forces balance equation when vehicle is trimmed in straight and level flight. In this condition, the balance equation depends on few variables, measured by standard on-board avionic sensors. The key innovation of proposed approach is the exploitation of system identification to tune the estimation algorithm parameters, by performing, just once, a calibration flight campaign in which vehicle’s weight is known. After calibration campaign is completed, the proposed method applies very simple relations to estimate the weight every time the vehicle is trimmed in straight and level flight, whatever its configuration is (helicopter or aircraft). Since the weight varies slowly and most of the mission usually takes place in straight and level flight, this approach guarantees a reliable weight estimation during about the whole mission; moreover, it does not require any a priori knowledge of vehicle parameters neither huge dataset for algorithms training. Monte Carlo analysis, employing the FlightLab ERICA tiltrotor model for flight data generation, was used to assess the estimation method performance. Obtained results are very promising in terms of accuracy, precision and robustness to sensors errors.