Design of Low-Cost Energy Harvesting and Delivery Systems for Self-Powered Devices: Application to Authentication IC

This thesis investigates the development of low-cost energy harvesting and delivery systems for low-power low-duty-cycle devices. Initially, we begin by designing a power management scheme for on-demand power delivery. The baseline implementation is also used to identify critical challenges for low-power energy harvesting. We further propose a robust self-powered energy harvesting and delivery system (EHDS) design as a solution to achieve energy autonomy in standalone systems. The design demonstrates a complete ecosystem for low-overhead pulse-frequency modulated (PFM) harvesting while reducing harvesting window confinement and overall implementation footprint. Two transient-based models are developed for improved accuracy during design space exploration and optimization for both PFM power conversion and energy harvesting. Finally, a low-power authentication IC is demonstrated and projected designs for self-powered System-on-Chips (SoCs) are presented. The proposed designs are proto-typed in two test-chips in a 65nm CMOS process and measurement data showcase improved performance in terms of battery power, cold-start duration, passives (inductance and capacitance) needed, and end-to-end harvesting/conversion efficiency.Ph.D

Low-Power Integrated Circuits For Biomedical Applications

With thousands new cases of spinal cord injury reported everyday, many people suffer from paralysis and loss of sensation in both legs. Beside the healthcare costs, such a state severely deteriorates the patients' quality of life and may even lead to additional medical conditions. Therefore, there is a growing need for cyber-physical systems to restore the walking ability through bypassing the damaged spinal cord. This goal can be achieved by monitoring and processing patient's brain signals to enable brain-directed control of prosthetic legs. Among several existing methods to record brain signals, electrocorticography (ECoG) has gained popularity due to being robust to motion artifacts, having high spatial resolution and signal to noise ratio, being moderately invasive and the possibility of chronic implantation of recording grids with no or minor scar tissue formation. The latest property is of particular importance for the whole system to be a viable fully implantable solution. Furthermore, the implanted system has to operate independently with no or minimal need of external hardware (e.g. a bulky personal computer) to be individually and socially accepted. To implement a fully implantable system, low-power and miniaturized electronics are needed to reduced heat generation, increase battery life-time and be minimally intrusive. These requirements indicate that many of the system's components should be custom-designed to integrated as much functionality as possible in a given real estate. This thesis presents silicon tested prototypes of several building blocks for the envisioned system, namely, ultra low-power brain signal acquisition front-ends, a low-power and inductorless MedRadio transceiver, and a fast start-up crystal oscillator. Brain signal acquisition front-ends provide low noise amplification of weak ECoG biosignals. MedRadio transceiver enables communication between the implant and end effectors or base station (e.g. prosthetic legs or desktop computer). Crystal oscillator generates the reference signal for other system's components such as analog to digital converter. Novel techniques to improve important performance parameters (power consumption, low noise operation and interference resilience) have been introduced. Electrical, in-vitro and in-vivo experimental measurements have verified the functionality and performance of each design

IoT応用向け環境RF信号RFエネルギーハーベスティングシステムの研究

電気通信大学201

Optically Powered Highly Energy-efficient Sensor Networks

In optically powered networks, both, communication signals and power for remotely located sensor nodes, are transmitted over an optical fiber. Key features of optically powered networks are node operation without local power supplies or batteries as well as operation with negligible susceptibility to electro-magnetic interference and to lightning. In this book, different kinds of optically powered devices and networks are investigated, and selected applications are demonstrated

Optically Powered Highly Energy-efficient Sensor Networks

In optically powered networks, both, communication signals and power for remotely located sensor nodes, are transmitted over an optical fiber. Key features of optically powered networks are node operation without local power supplies or batteries as well as operation with negligible susceptibility to electro-magnetic interference and to lightning. In this book, different kinds of optically powered devices and networks are investigated, and selected applications are demonstrated

Energy-Efficient Wireless Connectivity and Wireless Charging For Internet-of-Things (IoT) Applications

During the recent years, the Internet-of-Things (IoT) has been rapidly evolving. It is indeed the future of communication that has transformed Things of the real world into smarter devices. To date, the world has deployed billions of “smart” connected things. Predictions say there will be 10’s of billions of connected devices by 2025 and in our lifetime we will experience life with a trillion-node network. However, battery lifespan exhibits a critical barrier to scaling IoT devices. Replacing batteries on a trillion-sensor scale is a logistically prohibitive feat. Self-powered IoT devices seems to be the right direction to stand up to that challenge. The main objective of this thesis is to develop solutions to achieve energy-efficient wireless-connectivity and wireless-charging for IoT applications. In the first part of the thesis, I introduce ultra-low power radios that are compatible with the Bluetooth Low-Energy (BLE) standard. BLE is considered as the preeminent protocol for short-range communications that support transmission ranges up to 10’s of meters. Number of low power BLE transmitter (TX) and receiver (RX) architectures have been designed, fabricated and tested in different planar CMOS and FinFET technologies. The low power operation is achieved by combining low power techniques in both the network and physical layers, namely: backchannel communication, duty-cycling, open-loop transmission/reception, PLL-less architectures, and mixer-first architectures. Further novel techniques have been proposed to further reduce the power the consumption of the radio design, including: a fast startup time and low startup energy crystal oscillators, an antenna-chip co-design approach for quadrature generation in the RF path, an ultra-low power discrete-time differentiator-based Gaussian Frequency Shift Keying (GFSK) demodulation scheme, an oversampling GFSK modulation/demodulation scheme for open loop transmission/reception and packet synchronization, and a cell-based design approach that allows automation in the design of BLE digital architectures. The implemented BLE TXs transmit fully-compliant BLE advertising packet that can be received by commercial smartphone. In the second part of the thesis, I introduce passive nonlinear resonant circuits to achieve wide-band RF energy harvesting and robust wireless power transfer circuits. Nonlinear resonant circuits modeled by the Duffing nonlinear differential equation exhibit interesting hysteresis characteristics in their frequency and amplitude responses that are exploited in designing self-adaptive wireless charging systems. In the magnetic-resonance wireless power transfer scenario, coupled nonlinear resonators are proposed to maintain the power transfer level and efficiency over a range of coupling factors without active feedback control circuitry. Coupling factor depends on the transmission distance, lateral, and angular misalignments between the charging pad and the device. Therefore, nonlinear resonance extends the efficient charging zones of a wireless charger without the requirement for a precise alignment.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169842/1/omaratty_1.pd

Ultra Low-power Wireless Sensor Node Design for ECG Sensing Applications

Ubiquitous computing, such as smart homes, smart cars, and smart grid, connects our world closely so that we can easily access to the world through such virtual infrastructural systems. The ultimate vision of this is Internet of Things (IoT) through which intelligent monitoring and management is feasible via networked sensors and actuators. In this system, devices transmit sensed information, and execute instructions distributed via sensor networks. A wireless sensor network (WSN) is such a network where many sensor nodes are interconnected such that a sensor node can transmit information via its adjacent sensor nodes when physical phenomenon is detected. Accordingly, the information can be delivered to the destination through this process. The concept of WSN is also applicable to biomedical applications, especially ECG sensing applications, in a form of a sensor network, so-called body sensor network (BSN), where affixed or implanted biosignal sensors gather bio-signals and transmit them to medical providers. The main challenge of BSN is energy constraint since implanted sensor nodes cannot be replaced easily, so they should prolong with a limited amount of battery energy or by energy harvesting. Thus, we will discuss several power saving techniques in this thesis.PhDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/137081/1/hesed_1.pd

Design techniques to enhance low-power wireless communication soc with reconfigurability and wake up radio

Nowadays, Internet of things applications are increasing, and each end-node has more demanding requirements such as energy efficiency and speed. The thesis proposes a heterogeneous elaboration unit for smart power applications, that consists of an ultra-low-power microcontroller coupled with a small (around 1k equivalent gates) soft-core of embedded FPGA. This digital system is implemented in 90-nm BCD technology of STMicroelectronics, and through the analysis presented in this thesis proves to have good performance in terms of power consumption and latency. The idea is to increase the system performance exploiting the embedded FPGA to managing smart power tasks. For the intended applications, a remarkable computational load is not required, it is just required the implementation of simple finite state machines, since they are event-driven applications. In this way, while the microcontroller deals with other system computations such as high-level communications, the eFPGA can efficiently manage smart power applications. An added value of the proposed elaboration unit is that a soft-core approach is applied to the whole digital system including the eFPGA, and hence, it is portable to different technologies. On the other hand, the configurability improvement has a straightforward drawback of about a 20–27% area overhead. The eFPGA usage to manage smart power applications, allows the system to reduce the required energy per task from about 400 to around 800 times compared to a processor implementation. The eFPGA utilization improves also the latency performance of the system reaching from 8 to 145 times less latency in terms of clock cycles. The thesis also introduces the architecture of a nano-watt wake-up radio integrated circuit implemented in 90-nm BCD technology of STMicroelectronics. The wake-up radio is an auxiliary always-on radio for medium-range applications that allows the IoT end-nodes to drastically reduce the power consumption during the node idle-listening communication phase

Ultra-low power IoT applications: from transducers to wireless protocols

This dissertation aims to explore Internet of Things (IoT) sensor nodes in various application scenarios with different design requirements. The research provides a comprehensive exploration of all the IoT layers composing an advanced device, from transducers to on-board processing, through low power hardware schemes and wireless protocols for wide area networks. Nowadays, spreading and massive utilization of wireless sensor nodes pushes research and industries to overcome the main limitations of such constrained devices, aiming to make them easily deployable at a lower cost. Significant challenges involve the battery lifetime that directly affects the device operativity and the wireless communication bandwidth. Factors that commonly contrast the system scalability and the energy per bit, as well as the maximum coverage. This thesis aims to serve as a reference and guideline document for future IoT projects, where results are structured following a conventional development pipeline. They usually consider communication standards and sensing as project requirements and low power operation as a necessity. A detailed overview of five leading IoT wireless protocols, together with custom solutions to overcome the throughput limitations and decrease the power consumption, are some of the topic discussed. Low power hardware engineering in multiple applications is also introduced, especially focusing on improving the trade-off between energy, functionality, and on-board processing capabilities. To enhance these features and to provide a bottom-top overview of an IoT sensor node, an innovative and low-cost transducer for structural health monitoring is presented. Lastly, the high-performance computing at the extreme edge of the IoT framework is addressed, with special attention to image processing algorithms running on state of the art RISC-V architecture. As a specific deployment scenario, an OpenCV-based stack, together with a convolutional neural network, is assessed on the octa-core PULP SoC