Node Placement and Distributed Magnetic Beamforming Optimization for Wireless Power Transfer

Abstract

Abstract-In multiple-input single-output (MISO) wireless power transfer (WPT) via magnetic resonant coupling, multiple transmitters are deployed to enhance the efficiency of power transfer to a single receiver by jointly adapting their source currents/voltages so as to constructively combine the induced magnetic fields at the receiver, a technique known as magnetic beamforming. In practice, since the transmitters (power chargers) are usually at fixed locations and the receiver (e.g. mobile phone) is desired to be freely located in a target region for wireless charging, its received power can fluctuate significantly over locations even with adaptive magnetic beamforming applied. To achieve uniform power coverage, the transmitters need to be optimally placed in the region such that a minimum charging power can be achieved for the receiver regardless of its location, which motivates this paper. First, we derive the optimal magnetic beamforming solution in closed-form for a distributed MISO WPT system with fixed locations of the transmitters and receiver to maximize the deliverable power to the receiver subject to a given sum-power constraint at all transmitters. By applying adaptive magnetic beamforming based on this optimal solution, we then jointly optimize the locations of all transmitters to maximize the minimum power deliverable to the receiver over a given one-dimensional (1D) region. Although the formulated problem is non-convex, we propose an iterative algorithm for solving it efficiently. Extensive simulation results are provided which show the significant performance gains by the proposed design with optimized transmitter locations and magnetic beamforming as compared to other benchmark schemes with nonadaptive and/or heuristic transmitter current allocation and node placement. Last, we extend the node placement problem to the case of two-dimensional (2D) region, and propose efficient designs for this case.

Communications and Signals Design for Wireless Power Transmission

“…Furthermore, compared to inductive coupling, WPT via magnetic resonant coupling has a relatively loose requirement on coil alignment. Leveraging this technique, a team from MIT has demonstrated lighting up a 60W light-bulb over 2 meters with about 40% efficiency [15], which has since spurred numerous research interests on this topic [2], [17]- [29]. Today, several interface standards have been developed for the two near-field WPT technologies, including Qi (pronounced as "Chee", coming from the Chinese word meaning "natural energy") by the Wireless Power Consortium [30], and AirFuel by the AirFuel Alliance (a merge of the former Alliance for the Wireless Power and Power Matters Alliance) [31].…”

Joint node deployment and wireless energy transfer scheduling for immortal sensor networks

“…As sensor nodes are generally designed for long term monitoring, their battery should be much larger than their energy consumption power, i.e., B c i . Consequently, the − − static, single [21] − data routing mobile [25] Chargers − static, multi [22] Chargers − data routing static, multi requirement of α i + c i x i ≤ B generally holds for all i, j.…”

“…It can be seen that, most of the literatures ( [7], [9], [21]) considered the WET problems where the WSN deployment is given, whereas the work in [25] considers the deployment of the WET chargers to cover a certain region. In fact, the deployment of the sensor nodes, which relates to the total received energy and the per-node energy consumption, is also important to network lifetime.…”

Magnetically Coupled Resonance WPT: Review of Compensation Topologies, Resonator Structures with Misalignment, and EMI Diagnostics

“…Most of the presented CPT systems are designed for low-power applications, including USB devices, lamps, and small robots [8,[65][66][67][68][69][70][71][72][73], where the transmitting distance is limited to the millimeter range. High efficiency is provided by MCR WPT for a longer transferring distance [23,34,[74][75][76][77][78][79][80][81][82].…”