A multi-input energy harvesting system with independent energy harvesting block and power management block

In the conventional approach widely used for multi-input energy harvesting (MIEH), energy harvesting, energy combining, and power conversion are performed integrally in an inductor sharing block through time multiplexing operations, which is not suitable for hot-pluggable systems. In the MIEH system proposed in this paper, an energy harvesting block (EHB) and a power management block (PMB) are independent of each other to increase the modularity of the system. Therefore, the EHB can be optimized to extract maximum power from energy sources, and the PMB can be focused on combining input energies and converting power effectively. This paper mainly focuses on the design and implementation of the EHB. For light, vibration, and thermal energy, the measured peak power efficiencies of the EHB implemented using a 0.35 μm CMOS process are 95.2%, 92.5%, and 95.5%, respectively. To confirm the functionality and effectiveness of the proposed MIEH system, a PMB composed of simple charge pump circuits and a power management unit has also been implemented and verified with the designed EHB.

Low-Voltage DC-DC Converter for IoT and On-Chip Energy Harvester Applications

The power saving issue and clean energy harvesting for wireless and cost-affordable electronics (e.g., IoT applications, sensor nodes or medical implants), have recently become attractive research topics. With this in mind, the paper addresses one of the most important parts of the energy conversion system chain – the power management unit. The core of such a unit will be formed by an inductorless, low-voltage DC-DC converter based on the cross-coupled dynamic-threshold charge pump topology. The charge pump utilizes a power-efficient ON/OFF regulation feedback loop, specially designed for strict low-voltage start-up conditions by a driver booster. Taken together, they serve as the masters to control the charge pump output (up to 600 mV), depending on the voltage value produced by a renewable energy source available in the environment. The low-power feature is also ensured by a careful design of the hysteresis-based bulk-driven comparator and fully integrated switched-capacitor voltage divider, omitting the static power consumption. The presented converter can also employ the on-chip RF-based energy harvester for use in a wireless power transfer system.

Efficient power management unit for IIOT edge computing applications

Applications of Industrial Internet of Things (IIoT) are comprehended in mass domains, and this reflects the prominence of IoT. However, the main con of IoT applications is that it requires continuous power to be drawn by various components to operate all the time. Energy harvesting provides a potential solution to this problem in many applications; however, this continual energy usage remains main IoT con. The energy generated by ambient sources is inadequate to run system application, and a need for better Power Management Unit (PMU) persists. This research paper proposes a PMU framework for energy efficiency in edge computing application with three layers of IoT architecture. Design-build on this deployment, constitutes sleep and awake scheduling, with calculative idle intervals. The transitions of states exercise an energy-efficient solution for the entire system. The design is tested on ZYBO Zynq-7000 (XC7Z010-1CLG400C) ARM/FPGA SoC board for development and evaluation. Simulation results demonstrate the task scheduling of our proposed architecture and energy consumption details. In brief, the proposed design proves to be a beneficial option, in particular, surpassing kin designs for industrial automation.

A multi-level optimization technique for electricity consumption management and pricing in residential neighborhoods

With the introduction of new technologies, concepts and approaches in power transmission, distribution and utilization such as Smart Grids (SG), Advanced Metering Infrastructures (AMI), Distributed Energy Resources (DER) and Demand Side Management (DSM), new capabilities have emerged that enable efficient use and management of power consumption. These capabilities are applicable at micro level in households and building complexes as well as at macro level for utility providers in form of resource and revenue management initiatives. On the other hand, integration of Information Technology (IT) and instrumentation has brought Building Management Systems (BMS) to our homes and has made it possible for the ordinary users to take advantage of more complex and sophisticated energy and cost management features as an integral part of their BMS. The idea of combining capabilities and advantages offered by SG, AMI, DER, DSM and BMS is the backbone of this thesis and has resulted in developing a unique, two-level optimization method for effective deployment of DSM at households and residential neighborhoods. The work consists of an optimization algorithm for households to maximize utilization of DER as the lower level of the envisioned two-level optimization technique while using a customized Game Theoretic optimization for optimizing revenue of utility providers for residential neighborhood as the upper level. This work will also introduce a power management unit, called Load Moderation Center (LMC), to host the developed optimization algorithms as an integrated part of BMS. LMC, upon successful completion, will be able to automatically plan consumption, effectively utilize available sources including grid, renewable energies and storages, and eliminate the need for residences to manually program their BMS for different market scenarios.

A multi-level optimization technique for electricity consumption management and pricing in residential neighborhoods

With the introduction of new technologies, concepts and approaches in power transmission, distribution and utilization such as Smart Grids (SG), Advanced Metering Infrastructures (AMI), Distributed Energy Resources (DER) and Demand Side Management (DSM), new capabilities have emerged that enable efficient use and management of power consumption. These capabilities are applicable at micro level in households and building complexes as well as at macro level for utility providers in form of resource and revenue management initiatives. On the other hand, integration of Information Technology (IT) and instrumentation has brought Building Management Systems (BMS) to our homes and has made it possible for the ordinary users to take advantage of more complex and sophisticated energy and cost management features as an integral part of their BMS. The idea of combining capabilities and advantages offered by SG, AMI, DER, DSM and BMS is the backbone of this thesis and has resulted in developing a unique, two-level optimization method for effective deployment of DSM at households and residential neighborhoods. The work consists of an optimization algorithm for households to maximize utilization of DER as the lower level of the envisioned two-level optimization technique while using a customized Game Theoretic optimization for optimizing revenue of utility providers for residential neighborhood as the upper level. This work will also introduce a power management unit, called Load Moderation Center (LMC), to host the developed optimization algorithms as an integrated part of BMS. LMC, upon successful completion, will be able to automatically plan consumption, effectively utilize available sources including grid, renewable energies and storages, and eliminate the need for residences to manually program their BMS for different market scenarios.

Autonomous Wireless System for Robust and Efficient Inductive Power Transmission to Multi-Node Implants

A number of recent and current efforts in brain machine interfaces are developing millimetre-sized wireless implants that achieve scalability in the number of recording channels by deploying a distributed ‘swarm’ of devices. This trend poses two key challenges for the wireless power transfer: (1) the system as a whole needs to provide sufficient power to all devices regardless of their position and orientation; (2) each device needs to maintain a stable supply voltage autonomously. This work proposes two novel strategies towards addressing these challenges: a scalable resonator array to enhance inductive networks; and a self-regulated power management circuit for use in each independent mm-scale wireless device. The proposed passive 2-tier resonant array is shown to achieve an 11.9% average power transfer efficiency, with ultra-low variability of 1.77% across the network.The self-regulated power management unit then monitors and autonomously adjusts the supply voltage of each device to lie in the range between 1.7 V-1.9 V, providing both low-voltage and over-voltage protection.