Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
One-to-Multiple Mobile Replenishment Path Planning with Overcharging Awareness
Wireless sensor networks (WSNs) have shown promising applications in various fields. Due to the limited capacity of battery power, energy replenishment is critical to wireless sensors. The advent of wireless power transfer (WPT) technology enables mobile charger vehicles (MCVs) to flexibly replenish rechargeable sensors within a certain distance. Since the power carried by MCVs is limited, it is essential to plan an efficient replenishment path for MCVs. Moreover, battery overcharging may cause safety issues and energy waste, which is overlooked by most existing studies. We explore the overcharging-aware mobile replenishment path planning under the one-to-multiple charging mode. We propose an algorithm driven by the reinforcement learning technique to find the optimal replenishment path of MCVs while avoiding overcharging or starving sensor nodes. Simulation results demonstrate that the proposed solution can significantly improve charging efficiency and energy utilization.
One-to-Multiple Mobile Replenishment Path Planning with Overcharging Awareness
Wireless sensor networks (WSNs) have shown promising applications in various fields. Due to the limited capacity of battery power, energy replenishment is critical to wireless sensors. The advent of wireless power transfer (WPT) technology enables mobile charger vehicles (MCVs) to flexibly replenish rechargeable sensors within a certain distance. Since the power carried by MCVs is limited, it is essential to plan an efficient replenishment path for MCVs. Moreover, battery overcharging may cause safety issues and energy waste, which is overlooked by most existing studies. We explore the overcharging-aware mobile replenishment path planning under the one-to-multiple charging mode. We propose an algorithm driven by the reinforcement learning technique to find the optimal replenishment path of MCVs while avoiding overcharging or starving sensor nodes. Simulation results demonstrate that the proposed solution can significantly improve charging efficiency and energy utilization.
One-to-Multiple Mobile Replenishment Path Planning with Overcharging Awareness
Guan, Xinjie (Autor:in) / Zhang, Hao (Autor:in) / Wan, Xili (Autor:in) / Bai, Guangwei (Autor:in) / Ye, Feng (Autor:in)
07.09.2021
257883 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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