Flight Path Planning of Solar-Powered UAV for Sustainable Communication Relay

Padilla, Giancarlo Eder Guerra; Kim, Kun-Jung; Park, Seok-Hwan; Yu, Kee-Ho

doi:10.1109/lra.2020.3014635

Cited by 16 publications

(12 citation statements)

References 18 publications

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“…In this particular case, the switch S5 is be forced to operate with a duty cycle of d5min, causing the PV to work away from the maximum power point, which can be accepted for a short time until the SC voltage is increased to be higher than VA. The output voltage during this mode can be calculated based on (6). During this mode, the voltage of the SC changes significantly from Vsc min up to Vsc max .…”

Section: Operation Principle During the Sito Modementioning

confidence: 99%

“…Typical waveforms and current paths of the converter under this mode are shown in Figures 8 and 9. The output voltage during this mode can be driven by applying voltage balance on L2, same as in ( 5) and (6).…”

Section: Operation Principle Of the Siso Modesmentioning

confidence: 99%

“…Alternative propulsion based on environmentally friendly energy sources is rapidly growing to minimize carbon dioxide emissions. Accordingly, the applications of electric UAVs powered by electric power sources are expected to have more expansions, especially for the photovoltaic (PV)-powered UAVs that became widely popular due to their increased flight endurance [5][6][7]. Advanced applications of electric UAVs in advanced remote sensing techniques using synthetic aperture radar (SAR) as a payload [8,9] introduce more challenges for the design of UAVs power system, which is required to supply the high-power pulses consumed by these payloads whilst being restricted by the weight/volume limits imposed on UAVs' subsystems.…”

Section: Introductionmentioning

confidence: 99%

“…V batt (6) where d 3 is the duty cycle of the switch S3, which, for a particular d 5 and bus voltage, is dependent only on the battery voltage.…”

mentioning

confidence: 99%

See 3 more Smart Citations

A Novel Multiport DC-DC Converter for Enhancing the Design and Performance of Battery–Supercapacitor Hybrid Energy Storage Systems for Unmanned Aerial Vehicles

2022

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This paper proposes an integrated multiport non-isolated DC–DC converter system for integrating battery–supercapacitor hybrid energy storage with photovoltaics for solar-powered unmanned aerial vehicles applications. Compared to the traditional topologies used, the proposed converter allows a size reduction of at least 20% of the supercapacitor by maximizing the utilization of the rated energy capacity. In addition, by proposing to use a phase-shifted carrier modulation technique, the inductors’ current ripple is reduced, which enables a further reduction in the inductor size. These improvements in capability and performance of the proposed topology are experimentally validated on a 500 W PV/battery–supercapacitor integrated power system prototype.

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Section: Operation Principle During the Sito Modementioning

confidence: 99%

Section: Operation Principle Of the Siso Modesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…V batt (6) where d 3 is the duty cycle of the switch S3, which, for a particular d 5 and bus voltage, is dependent only on the battery voltage.…”

mentioning

confidence: 99%

See 2 more Smart Citations

A Novel Multiport DC-DC Converter for Enhancing the Design and Performance of Battery–Supercapacitor Hybrid Energy Storage Systems for Unmanned Aerial Vehicles

2022

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“…In [17], through optimizing the trajectory, the transmit power of the UAV and the mobile device, the outage probability of the UAV relay network in the disaster area was minimized. In [18], a UAV platform was developed to compensate the communication loss during a natural disaster, with the aim to obtain the optimal flight paths in high-rise urban and urban microcell environment. In [19], UAV-assisted networks was studied in disaster area, and the proposed power control optimization problem was solved via relaxing the non-convex problem.…”

Section: Introductionmentioning

confidence: 99%

QoE Optimization for Live Video Streaming in UAV-to-UAV Communications via Deep Reinforcement Learning

binti

Liu

Deng

et al. 2022

IEEE Trans. Veh. Technol.

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A challenge for rescue teams when fighting against wildfire in remote areas is the lack of information, such as the size and images of fire areas. As such, live streaming from Unmanned Aerial Vehicles (UAVs), capturing videos of dynamic fire areas, is crucial for firefighter commanders in any location to monitor the fire situation with quick response. The 5G network is a promising wireless technology to support such scenarios. In this paper, we consider a UAV-to-UAV (U2U) communication scenario, where a UAV at a high altitude acts as a mobile base station (UAV-BS) to stream videos from other flying UAV-users (UAV-UEs) through the uplink. Due to the mobility of the UAV-BS and UAV-UEs, it is important to determine the optimal movements and transmission powers for UAV-BSs and UAV-UEs in realtime, so as to maximize the data rate of video transmission with smoothness and low latency, while mitigating the interference according to the dynamics in fire areas and wireless channel conditions. In this paper, we co-design the video resolution, the movement, and the power control of UAV-BS and UAV-UEs to maximize the Quality of Experience (QoE) of real-time video streaming. We applied the Deep Q-Network (DQN) and Actor-Critic (AC) to maximize the QoE of video transmission from all UAV-UEs to a single UAV-BS to learn the dynamic fire areas and communication environment. Simulation results show the effectiveness of our proposed algorithm in terms of the QoE, delay and video smoothness compared to the Greedy algorithm.

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Optimizing UAV Path for Disaster Management in Smart Cities Using Metaheuristic Algorithms

Qadir

Zafar

Moosavi

et al. 2022

Studies in Computational Intelligence

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Flight Path Planning of Solar-Powered UAV for Sustainable Communication Relay

Cited by 16 publications

References 18 publications

A Novel Multiport DC-DC Converter for Enhancing the Design and Performance of Battery–Supercapacitor Hybrid Energy Storage Systems for Unmanned Aerial Vehicles

A Novel Multiport DC-DC Converter for Enhancing the Design and Performance of Battery–Supercapacitor Hybrid Energy Storage Systems for Unmanned Aerial Vehicles

QoE Optimization for Live Video Streaming in UAV-to-UAV Communications via Deep Reinforcement Learning

Optimizing UAV Path for Disaster Management in Smart Cities Using Metaheuristic Algorithms

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