PFI:AIR-TT: DeepBeam: Wirelessly chargeable portable batteries through energy beamforming

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This PFI: AIR Technology Translation project focuses on translating a distributed wireless radio-frequency (RF) charging concept to a network-assisted battery replenishment system for small form-factor sensors and devices. This will result in the ability to charge small devices, such as cell phones, wirelessly, which will untether them from the constraints of cables and power sockets. The project, called DeepBeam, will ensure such IOT devices operate continuously, with minimum user involvement and battery-related maintenance downtimes, and enable an energy management network for the tens of billions of Internet of Things (IOT) devices that will be pervasively deployed over the next decade. Many safety-critical sensing and monitoring tasks increasingly rely on sensors in homes, industries and public areas, which make DeepBeam's innovation in wireless energy delivery an important area of investment. The project will result in a proof of concept network of multiple energy transmitters (ETs) and a high-efficiency energy harvesting circuit. DeepBeam will incorporate the following unique features: (i) a software controller that optimally schedules wireless charging operations among the energy transmitters, and (ii) a circuit that can harvest energy in both the unlicensed and the cellular frequency bands. DeepBeam's design features provide the following advantages: 40-45% energy harvesting efficiency, charging radius of several tens of meters, and unconstrained charging in any spatial direction when compared to the leading competing wireless charging solutions in this market space.  The project addresses the following technology gaps as it translates from research discovery toward commercial application: (i) Designing a beamforming algorithm based on channel estimation techniques to eliminate the need for continuous feedback from that device, so that the energy beams from multiple source points can be properly oriented with constructive energy interference at the target, (ii) Developing and fabricating an energy harvesting circuit that interfaces with off-the-shelf sensors and is also capable of aggregating the received energy over multiple spectrum bands, (iii) Devising a scheduling algorithm in the software controller that will decide the selection of the target receivers and the active duration of the charging beams based on the changing network needs. In addition, the personnel involved in this project, one post doctoral researcher and one graduate student, will receive innovation and technology translation experiences through jointly filed patents, writing invention disclosure documents and participating in commercialization activities. The PFI team is strongly connected to the Northeastern Venture Mentoring Network (VMN) and the university's Center for Entrepreneurship Education that contribute mentoring support towards the technology translation goals of the project.