Redirigiendo al acceso original de articulo en 20 segundos...
Inicio  /  Aerospace  /  Vol: 11 Par: 3 (2024)  /  Artículo
ARTÍCULO
TITULO

Online Learning-Based Surrogate Modeling of Stratospheric Airship Solar Array Output Power

Kangwen Sun    
Siyu Liu    
Huafei Du    
Haoquan Liang and Xiao Guo    

Resumen

The stratospheric airship is a type of aerostat that uses solar energy as its power source and can fly continuously for months or even years in near space. The rapid and accurate prediction of the output power of its solar array is the key to maintaining energy balance and extending flight time. This paper establishes an online learning model for predicting the output power of the solar array of stratospheric airships. The readings of radiometers arranged on the surface of the airship are used as features for training the model. The parameters of the model can be updated in real-time during the flight process without retraining the entire model. The effect of radiometer placement on the model accuracy was also analyzed. The results show that for the continuous flight of 40 days, the online learning model can achieve an accuracy of 88% after training with 10 days of flight data and the accuracy basically reaches its highest level after 20 days. In addition, placing the radiometers at the four corners of the array can achieve a higher prediction accuracy of 95%. The online model can also accurately identify and reflect the effect of module efficiency attenuation or damage and maintain high accuracy.

 Artículos similares

       
 
Wan Teng Tey, Tee Connie, Kan Yeep Choo and Michael Kah Ong Goh    
Traditional methods used to identify and monitor insect species are time-consuming, costly, and fully dependent on the observer?s ability. This paper presents a deep learning-based cicada species recognition system using acoustic signals to classify the ... ver más
Revista: Algorithms

 
Jianying Wang, Yuanpei Wu, Ming Liu, Ming Yang and Haizhao Liang    
Considering the high-efficient trajectory planning requirements for hypersonic vehicles, this paper proposes a real-time trajectory optimization method based on a deep neural network. First, the trajectory optimization model of the hypersonic vehicle ree... ver más
Revista: Aerospace

 
Valerie Bukas Marcus,Noor Azean Atan,Sanitah Mohd Yusof,Umi Mastura     Pág. pp. 100 - 115
Impact brought by COVID-19 changes the whole classroom culture from face to face to the extreme online learning and this includes a course that normally implements traditional face-to-face Service Learning. Educators are required to shift the learning in... ver más

 
Yufei Liu, Feng Zhou, Gang Qiao, Yunjiang Zhao, Guang Yang, Xinyu Liu and Yinheng Lu    
A deep learning-based cyclic shift keying spread spectrum (CSK-SS) underwater acoustic (UWA) communication system is proposed for improving the performance of the conventional system in low signal-to-noise ratio and multipath effects. The proposed deep l... ver más

 
Faiz Hasyim,Tjipto Prastowo,Budi Jatmiko     Pág. pp. 31 - 41
Covid-19 spurs teachers to carry out online learning. This study aimed to analyze the improvement of students' critical thinking skills through online learning based on Android-based PhET Simulation. This research was Quasi-Experimental using one group p... ver más