Speed detection of battery-free nodes based on RF Wireless Power Transfer

In the Internet of Things (IoT) era, Wireless Sensor Networks (WSNs) are rapidly increasing in terms of relevance and pervasiveness thanks to their notable real-time monitoring performance across several fields, including industrial, domestic, military, biomedical, commercial, environmental, and other sectors. A highly attractive implementation of WSNs is asset tracking with accurate data regarding the location and transportation conditions of goods, equipment, and the like. One highly promising application of WSNs along these lines is the remote speed monitoring of goods, ideally with battery-free sensor nodes that do not require any maintenance. This, however, represents a major challenge in power supply management. The goal of this paper is to investigate Radio Frequency (RF) Wireless Power Transfer (WPT) architecture to power a battery-free measurement system with time-domain readouts, for the speed detection of a moving sensor tag within a Wireless Sensor Network infrastructure. The performance characteristics and key features of a System-on-Chip (SoC) specifically designed to power a node through RF WPT will be discussed. The aim is to provide a strategy and a model to estimate the speed of a specific battery-free sensor that is powered by a transmitting hot-spot. Specific tests and experimental results are provided.

An RF Wireless Power Transfer system to power battery-free devices for asset tracking

Catherine Dehollain, Roberto La Rosa

Internet of Things (IoT) and Wireless Sensor Networks (WSN) infrastructures are becoming more and more available and diffused. One major outcome is the development of new services that help to make everyday life easier and better. One of those to which this paper reserves special attention is asset tracking which refers to the method of tracking physical assets. This service is very well based on IoT infrastructure and, due to the enormous number of objects to be traced, desperately needs the availability of inexpensive tags with sensing capabilities, that can be conveniently monitored from a long distance and require no maintenance. For this, engineers are called to face very challenging issues. One of these is how to power a maintenance-free tag that consequently must be battery-free. This paper deals with the investigation of a system based on radio frequency (RF) Wireless Power Transfer (WPT) that powers a battery-free tag for asset tracking, in which the major challenge is that the WPT deals with dynamic objects at different speeds. The performances and key features of a system on chip (SoC) specifically designed to power a tag by means of RF WPT will be investigated. The aim is to provide a strategy and a model to design the infrastructure by providing the number of hot-spots needed to perform successfully the identification of an asset. Validation of the model has been done by means of specific tests and experimental results are provided.

IEEE2019

Advanced Monitoring Systems Based on Battery-Less Asset Tracking Modules Energized through RF Wireless Power Transfer

Catherine Dehollain, Roberto La Rosa

Asset tracking involving accurate location and transportation data is highly suited to wireless sensor networks (WSNs) featuring battery-less nodes that can be deployed in virtually any environment and require little or no maintenance. In response to the growing demand for advanced battery-less sensor tag solutions, this article presents a system for identifying and monitoring the speeds of assets in a WSN with battery-less tags that receive all their operating energy through radio frequency (RF) wireless power transfer (WPT) architecture, and a unique measurement approach to generate time-domain speed readouts. The assessment includes performance characteristics and key features of a system on chip (SoC) purposely designed to power a node through RF WPT. The result is an innovative solution for RF to DC conversion able to address the principal difficulties associated with maximum power conversion efficiency (PCE) with sensitivity and vice versa, a strategy, and a design optimization model to indicate the number of readers required for reliable asset identification and speed measurement. Model validation is performed through specific tests. Experimental results demonstrating the viability of the proposed advanced monitoring system are provided.

2020

Strategies, Techniques and Systems for powering low-maintenance and battery-free devices through Energy Harvesting and Wireless Power Transfer

Roberto La Rosa

The purpose of this research has a background in the market for Internet of Things (IoT)devices and wireless sensor networks. The Market Forecast predicts the connection of a trillion"things" by 2025. The global smart sensor market size trend grows from USD 36.6 billion in2020 to USD 87.6 billion by 2025, at a CAGR of 19.0 %. The energy harvesting systems market is worth USD 440.39 million in 2019 with a forecast to reach USD 817.2 million by 2025, at a CAGR of 10.91 %, over the forecast period(2020-2025). In this scenario, to power a trillion node IoT infrastructure would require trillions of batteries which poses maintenance problems and related non-negligible management costs. Indeed, for every trillion nodes installed, 274million batteries would need to be replaced every day, even in the best-case scenario where it is possible to assume that batteries reach their 10-year life expectancy. In this context, this thesis aims to show innovative systems, strategies, techniques, and circuits for powering low-maintenance,energy-autonomous, and battery-free devices. The principal intention is to contribute to the research effort of Wireless Sensor Node (WSN) that is sustainable and needs minimal or no maintenance. More, in particular, it shows how RF wireless power transfer (WPT) with its pervasiveness is, in some practical use cases, a very convenient way to remotely supply wireless nodes, especially when installed in locations difficult to reach. In terms of systems and circuits, this work presents a state-of-the-art, ultra-low-power 2.5µW highly integrated mixed-signal system on chip (SoC), for multi-source energy harvesting(EH) and RF wireless power transfer. The SoC implements an architecture that integrates a high-performance nano-power management, a wide-bandwidth (350 MHz - 2.4 GHz)RF to DCconverter, with low power sensitivity (-22 dBm at 868 MHz) and maximum Power Conversion Efficiency (PCE) (55% at the minimum input power). For the PCE optimization over several operating conditions, the system integrates an innovative ultra-low-power Maximum Power Point Tracking (MMPT) system. The IC integrates an accurate Amplitude-Shift-Keyingand Frequency-Shift-Keying (ASK/FSK) demodulator and digital circuitry to allow over the air configuration of the SoC while powered by an RF power source. The integration of an ultra-low-power asynchronous finite state machine and a programmable logic allow the implementation of several features that render the system versatile and able to deal with different energy sources and use cases with minimal external components. The SoC is fabricated in a0.13µmCMOS technology in a core area of 2.7mm2.vAs for the strategies and techniques, this thesis discusses several innovative methods that aim both to postpone the maintenance interventions of battery-powered nodes over time, and when possible, to cancel the maintenance of the nodes by eliminating the battery. Therefore, it is shown how to power a WSN through energy harvesting and RF wireless power transfer by discussing system architectures and experimental results in detail. One of the presented strategies highlights that the main issue to solve in battery-suppliedWSN is how to reduce or better null standby power consumption. Indeed, while on standby, power management circuits are permanently active and consume unnecessary energy. This work presents an innovative technique based on RF wireless power transfer to null standby power consumption.

EPFL2022

Strategies, Techniques and Systems for powering low-maintenance and battery-free devices through Energy Harvesting and Wireless Power Transfer

Roberto La Rosa

EPFL2022