Movers and Shakers: Kinetic Energy Harvesting for the Internet of Things

Numerous energy harvesting wireless devices that will serve as building blocks for the Internet of Things (IoT) are currently under development. However, there is still only limited understanding of the properties of various energy sources and their impact on energy harvesting adaptive algorithms. Hence, we focus on characterizing the kinetic (motion) energy that can be harvested by a wireless node with an IoT form factor and on developing energy allocation algorithms for such nodes. In this paper, we describe methods for estimating harvested energy from acceleration traces. To characterize the energy availability associated with specific human activities (e.g., relaxing, walking, cycling), we analyze a motion dataset with over 40 participants. Based on acceleration measurements that we collected for over 200 hours, we study energy generation processes associated with day-long human routines. We also briefly summarize our experiments with moving objects. We develop energy allocation algorithms that take into account practical IoT node design considerations, and evaluate the algorithms using the collected measurements. Our observations provide insights into the design of motion energy harvesters, IoT nodes, and energy harvesting adaptive algorithms.Comment: 15 pages, 11 figure

Energy harvesting from human and machine motion for wireless electronic devices

Published versio

Human-powered inertial energy harvesters: the effect of orientation, location and activity on the obtainable electrical power

Human-powered inertial energy harvesting is an emerging technology that can power electronic devices using electrical energy scavenged from human motion. Traditional energy harvesters generate energy only from a single axis, and are referred to one degree-of-freedom (1-DOF) energy harvesters. In this thesis, a two degree-of-freedom (2-DOF) energy harvester consisting of two orthogonal 1-DOF energy harvesters is studied. This research theoretically and experimentally investigates the effect of orientation, location and activity on the obtainable power from 2-DOF human-powered inertial energy harvesters.An on-body measurement study has been conducted to collect acceleration data from five key locations on the body during both walking and running. The collected data have been analyzed to evaluate the harvestable power along different orientations of both 1-DOF and 2-DOF inertial energy harvesters. The results show that the orientation of 1-DOF generators on the body greatly affects the output power. 2-DOF generators can maintain a more constant power output with rotation, thus are more reliable than 1-DOF generators. For 1-DOF generators, and for each location and activity, only 6% of the tested orientations harvest over 90% of the maximum power. For 2-DOF generators, this is increased to 32%, showing a considerable improvement.To validate the analytical results, 1-DOF mechanical- and magnetic-spring electromagnetic generators have been designed and prototyped. A novel design has been proposed to linearise magnetic springs for low frequency use. Experimental validation shows that the design exhibits a linearity of 2% across a ±25 mm displacement range, presenting a significant improvement over the state-of-the-art. A 2-DOF inertial generator that consists of two orthogonal 1-DOF mechanical-spring generators has been tested at three locations around the knee while running. At each location, the 2-DOF generator has been rotated to four different angles. The results show that 2-DOF generators can generate over 81% of the maximum power in all orientations. For 1-DOF generators, it is only 35%

Power Processing for Electrostatic Microgenerators

Microgenerators are electro-mechanical devices which harvest energy from local environmental from such sources as light, heat and vibrations. These devices are used to extend the life-time of wireless sensor network nodes. Vibration-based microgenerators for biomedical applications are investigated in this thesis. In order to optimise the microgenerator system design, a combined electro-mechanical system simulation model of the complete system is required. In this work, a simulation toolkit (known as ICES) has been developed utilising SPICE. The objective is to accurately model end-to-end microgenerator systems. Case-study simulations of electromagnetic and electrostatic microgenerator systems are presented to verify the operation of the toolkit models. Custom semiconductor devices, previously designed for microgenerator use, have also been modelled so that system design and optimisation of complete microgenerator can be accomplished. An analytical framework has been developed to estimate the maximum system effectiveness of an electrostatic microgenerator operating in constant-charge and constant-voltage modes. The calculated system effectiveness values are plotted with respect to microgenerator sizes for different input excitations. Trends in effectiveness are identified and discussed in detail. It was found that when the electrostatic transducer is interfaced with power processing circuit, the parasitic elements of the circuit are reducing the energy generation ability of the transducer by sharing the charge during separation of the capacitor plates. Also, found that in constant-voltage mode the electrostatic microgenerator has a better effectiveness over a large operating range than constant-charge devices. The ICES toolkit was used to perform time-domain simulation of a range of operating points and the simulation results provide verification of the analytical results

Maximum Effectiveness of Electrostatic Energy Harvesters When Coupled to Interface Circuits

Accepted versio

Energy Harvesting Networked Nodes: Measurements, Algorithms, and Prototyping

Recent advances in ultra-low-power wireless communications and in energy harvesting will soon enable energetically self-sustainable wireless devices. Networks of such devices will serve as building blocks for different Internet of Things (IoT) applications, such as searching for an object on a network of objects and continuous monitoring of object configurations. Yet, numerous challenges need to be addressed for the IoT vision to be fully realized. This thesis considers several challenges related to ultra-low-power energy harvesting networked nodes: energy source characterization, algorithm design, and node design and prototyping. Additionally, the thesis contributes to engineering education, specifically to project-based learning. We summarize our contributions to light and kinetic (motion) energy characterization for energy harvesting nodes. To characterize light energy, we conducted a first-of-its kind 16 month-long indoor light energy measurements campaign. To characterize energy of motion, we collected over 200 hours of human and object motion traces. We also analyzed traces previously collected in a study with over 40 participants. We summarize our insights, including light and motion energy budgets, variability, and influencing factors. These insights are useful for designing energy harvesting nodes and energy harvesting adaptive algorithms. We shared with the community our light energy traces, which can be used as energy inputs to system and algorithm simulators and emulators. We also discuss resource allocation problems we considered for energy harvesting nodes. Inspired by the needs of tracking and monitoring IoT applications, we formulated and studied resource allocation problems aimed at allocating the nodes' time-varying resources in a uniform way with respect to time. We mainly considered deterministic energy profile and stochastic environmental energy models, and focused on single node and link scenarios. We formulated optimization problems using utility maximization and lexicographic maximization frameworks, and introduced algorithms for solving the formulated problems. For several settings, we provided low-complexity solution algorithms. We also examined many simple policies. We demonstrated, analytically and via simulations, that in many settings simple policies perform well. We also summarize our design and prototyping efforts for a new class of ultra-low-power nodes - Energy Harvesting Active Networked Tags (EnHANTs). Future EnHANTs will be wireless nodes that can be attached to commonplace objects (books, furniture, clothing). We describe the EnHANTs prototypes and the EnHANTs testbed that we developed, in collaboration with other research groups, over the last 4 years in 6 integration phases. The prototypes harvest energy of the indoor light, communicate with each other via ultra-low-power transceivers, form small multihop networks, and adapt their communications and networking to their energy harvesting states. The EnHANTs testbed can expose the prototypes to light conditions based on real-world light energy traces. Using the testbed and our light energy traces, we evaluated some of our energy harvesting adaptive policies. Our insights into node design and performance evaluations may apply beyond EnHANTs to networks of various energy harvesting nodes. Finally, we present our contributions to engineering education. Over the last 4 years, we engaged high school, undergraduate, and M.S. students in more than 100 research projects within the EnHANTs project. We summarize our approaches to facilitating student learning, and discuss the results of evaluation surveys that demonstrate the effectiveness of our approaches

Functional modelling and prototyping of electronic integrated kinetic energy harvesters

The aim of developing infinite-life autonomous wireless electronics, powered by the energy of the surrounding environment, drives the research efforts in the field of Energy Harvesting. Electromagnetic and piezoelectric techniques are deemed to be the most attractive technologies for vibrational devices. In the thesis, both these technologies are investigated taking into account the entire energy conversion chain. In the context of the collaboration with the STMicroelectronics, the project of a self-powered Bluetooth step counter embedded in a training shoe has been carried out. A cylindrical device 27 × 16mm including the transducer, the interface circuit, the step-counter electronics and the protective shell, has been developed. Environmental energy extraction occurs exploiting the vibration of a permanent magnet in response to the impact of the shoe on the ground. A self-powered electrical interface performs maximum power transfer through optimal resistive load emulation and load decoupling. The device provides 360 μJ to the load, the 90% of the maximum recoverable energy. The energy requirement is four time less than the provided and the effectiveness of the proposed device is demonstrated also considering the foot-steps variability and the performance spread due to prototypes manufacturing. In the context of the collaboration with the G2Elab of Grenoble and STMicroelectronics, the project of a piezoelectric energy arvester has been carried out. With the aim of exploiting environmental vibrations, an uni-morph piezoelectric cantilever beam 60×25×0.5mm with a proof mass at the free-end has been designed. Numerical results show that electrical interfaces based on SECE and sSSHI techniques allows increasing performance up to the 125% and the 115% of that in case of STD interface. Due to the better performance in terms of harvested power and in terms of electric load decoupling, a self-powered SECE interface has been prototyped. In response to 2 m/s2 56,2 Hz sinusoidal input, experimental power recovery of 0.56mW is achieved demonstrating that the device is compliant with standard low-power electronics requirements