scholarly journals A novel safety assurance method based on the compound equivalent modeling and iterate reduce particle‐adaptive Kalman filtering for the unmanned aerial vehicle lithium ion batteries

2020 ◽  
Vol 8 (5) ◽  
pp. 1484-1500 ◽  
Author(s):  
Shunli Wang ◽  
Carlos Fernandez ◽  
Yongcun Fan ◽  
Juqiang Feng ◽  
Chunmei Yu ◽  
...  
Keyword(s):  
Lithium Ion Batteries ◽  
Unmanned Aerial Vehicle ◽  
Kalman Filtering ◽  
Lithium Ion ◽  
Safety Assurance ◽  
Aerial Vehicle

Comparison of lithium ion Batteries, hydrogen fueled combustion Engines, and a hydrogen fuel cell in powering a small Unmanned Aerial Vehicle

2020 ◽  
Vol 207 ◽  
pp. 112514 ◽  
Author(s):  
Christopher Depcik ◽  
Truman Cassady ◽  
Bradley Collicott ◽  
Sindhu Preetham Burugupally ◽  
Xianglin Li ◽  
...  
Keyword(s):  
Fuel Cell ◽  
Lithium Ion Batteries ◽  
Unmanned Aerial Vehicle ◽  
Lithium Ion ◽  
Combustion Engines ◽  
Hydrogen Fuel Cell ◽  
Hydrogen Fuel ◽  
Aerial Vehicle

The Methods of Information Acquisition and Information Fusion of the Photoelectric Sensor-Based Quadrotor Unmanned Aerial Vehicle

2020 ◽  
Vol 15 (1) ◽  
pp. 82-91
Author(s):  
Fen Hang ◽  
Xiangyang Hao
Keyword(s):  
Kalman Filter ◽  
Unmanned Aerial Vehicle ◽  
Kalman Filtering ◽  
Information Fusion ◽  
Information Acquisition ◽  
Reference System ◽  
Fusion Technology ◽  
Photoelectric Sensor ◽  
Aerial Vehicle ◽  
Sensor Information

When quadrotor unmanned aerial vehicle (UAV) is performing various tasks, even a small angular error will affect the evaluation of the entire motion trajectory. The multiple photoelectric sensor information fusion technology and the ARM microprocessor platform are used to form an attitude reference system for UAV. First, the hardware design of the small quadrotor UAV attitude reference system based on an ARM is introduced. The design framework and information acquisition module are expounded. In terms of the software of the system, the photoelectric sensor is used to receive different kinds of information, and the dynamic loading component is adopted as the solution to the interface diversification problems. Based on the attitude reference system, the collected information needs to be fused. The Kalman filtering is taken as the research object. Combined with the multiple photoelectric sensor information fusion technology, the Kalman filtering method is improved in the data preprocessing, and the low-pass filtering is added. Therefore, the abnormal data is filtered, and the estimated values are converged in a short time. Then, the data fusion is performed by the joint Kalman filter, least-squares fusion, and extended Kalman filter, respectively. During the experimental process, the system is proved to have good robustness, that is, in the case of individual sensor failure, the attitude acquisition section still obtains accurate attitude information of the UAV. The attitude reference system of UAV is realized. With the help of multi-sensor/information fusion technology, the attitude of the UAV is better handled, and its flight stability is improved.

A Simaplied Adaptive Kalman Filtering Algorithm

2014 ◽  
Vol 1037 ◽  
pp. 378-382
Author(s):  
Lei Bo ◽  
Xin Yan Zhu
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Unmanned Aerial Vehicle ◽  
Kalman Filtering ◽  
Likelihood Estimation ◽  
Simplified Model ◽  
Filtering Algorithm ◽  
Aerial Vehicle ◽  
Kalman Filtering Algorithm ◽  
The Moment

The adaptive Kalman filtering algorithm was adopted in the online estimate of navigation state of unmanned aerial vehicle (UAV) as the simplified model often used. At the moment, the alogorithms those usually applied in this territory are not perfect. Analysed the adaptive Kalman filtering based on Maximum-Likelihood Estimation and Sage-Husa Kalman filtering, take advantage the characteristics of residue, choose the estimation windows, a simplified adaptive Kalman filtering algorithm was gived.

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