Energy Storage Battery Parameters Identification Algorithms of a Solar Powered Communication/Remote-Sensing UAV

Chen, Jian; Du, Nan; Liao, Zirui; Cao, Yi; Han, Yu; Zheng, Yongjun; Yu, Tan

doi:10.1016/j.ifacol.2019.12.378

Cited by 1 publication

(1 citation statement)

References 7 publications

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“…A realistic planning of the UAV's flight trajectory according to the location of the user terminal is also necessary since the channel conditions between the ground user and the UAV will directly affect the communication energy consumption between the user terminal and the UAV. Mobile users' terminal equipment has limited energy and processing power, which makes it difficult to adequately meet their application needs [2][3]. In order to relieve the burden on user terminals' limited resources, mobile edge computing (MEC) places servers on the edge side close to users [4].…”

Section: Introductionmentioning

confidence: 99%

UAV-based edge computing system used in energy-saving offloading method

Abdulazeez,

Shaker

2023

J. Phys.: Conf. Ser.

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This paper proposes an offloading strategy based on unmanned aerial vehicle (UAV) managed computer resources to provide dependable communication and intensive processing power in complicated terrain. In order to reduce compute and offload user terminal energy consumption, a UAV-assisted edge computing model is built, taking into account the computing requirements of user terminals, the delay restrictions of computing jobs, and the energy limits of UAVs. The trajectory can be used to reduce the user terminal’s energy usage in the allotted amount of time. The simulation results demonstrate that the suggested approach is appropriate for various channel circumstances, allowing the user terminal to accomplish the work while outperforming existing benchmark systems in terms of energy usage. Optimizing the flight trajectory of the UAV will have a substantial impact when the signal-to-noise ratio SNR=20dB. The results demonstrate that, at T=5s, the UAV’s flying trajectory optimization strategy reduces energy consumption by 56.26%.

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Section: Introductionmentioning

confidence: 99%