Project-based Learning within a Large-Scale Interdisciplinary Research Effort

The modern engineering landscape increasingly requires a range of skills to successfully integrate complex systems. Project-based learning is used to help students build professional skills. However, it is typically applied to small teams and small efforts. This paper describes an experience in engaging a large number of students in research projects within a multi-year interdisciplinary research effort. The projects expose the students to various disciplines in Computer Science (embedded systems, algorithm design, networking), Electrical Engineering (circuit design, wireless communications, hardware prototyping), and Applied Physics (thin-film battery design, solar cell fabrication). While a student project is usually focused on one discipline area, it requires interaction with at least two other areas. Over 5 years, 180 semester-long projects have been completed. The students were a diverse group of high school, undergraduate, and M.S. Computer Science, Computer Engineering, and Electrical Engineering students. Some of the approaches that were taken to facilitate student learning are real-world system development constraints, regular cross-group meetings, and extensive involvement of Ph.D. students in student mentorship and knowledge transfer. To assess the approaches, a survey was conducted among the participating students. The results demonstrate the effectiveness of the approaches. For example, 70% of the students surveyed indicated that working on their research project improved their ability to function on multidisciplinary teams more than coursework, internships, or any other activity

Development of Graphene Nano-Platelet Ink for High Voltage Flexible Dye Sensitized Solar Cells with Cobalt Complex Electrolytes

Graphene nanoparticles have been subject to intensive investigation as a replacement for platinum as the catalyst in dye sensitized solar cells (DSCs), but few of these investigations examine the application for flexible cells with deposition processes suitable for industrial fabrication. This work introduces a transparent water based graphene ink that can be dried rapidly at less than 110 ºC making it particularly suitable for roll to roll deposition on plastic substrates. This ink has application as a catalyst for dye sensitized solar cells utilizing cobalt complex electrolytes with efficiency of over 6 % and a Voc of 0.89 V at 1 sun demonstrated. A flexible DSC with a printed catalyst and cobalt redox mediator is reported, with efficiency of over 6.0 % and Voc of 0.6 V at 800 lux

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

Robust Power Allocation for Energy-Efficient Location-Aware Networks

In wireless location-aware networks, mobile nodes (agents) typically obtain their positions using the range measurements to the nodes with known positions. Transmit power allocation not only affects network lifetime and throughput, but also determines localization accuracy. In this paper, we present an optimization framework for robust power allocation in network localization with imperfect knowledge of network parameters. In particular, we formulate power allocation problems to minimize localization errors for a given power budget and show that such formulations can be solved via conic programming. Moreover, we design a distributed power allocation algorithm that allows parallel computation among agents. The simulation results show that the proposed schemes significantly outperform uniform power allocation, and the robust schemes outperform their non-robust counterparts when the network parameters are subject to uncertainty.National Natural Science Foundation (China) (Project 61201261)National Basic Research Program of China (973 Program) (61101131)University Grants Committee (Hong Kong, China) (GRF Grant Project 419509)National Science Foundation (U.S.) (Grant ECCS-0901034)United States. Office of Naval Research (Grant N00014-11-1-0397)Massachusetts Institute of Technology. Institute for Soldier Nanotechnologie

On-Demand Energy Harvesting Techniques - A System Level Perspective

In recent years, energy harvesting has been generating great interests among researchers, scientists and engineers alike. One of the major reasons for this increased interest sterns from the desire to have autonomous perpetual power supplies for remote monitoring sensor nodes utilizing some of the already available and otherwise wasted energy in the environment in a very innovative and useful way (and at the same time, maintaining a green environment). Scientists and engineers are constantly looking for ways of obtaining continuous and uninterrupted data from several points of interests especially remote or dangerous locations, using sensors coupled with RF transceivers, without the need of ever replacing or recharging the batteries that power these devices. This is now made possible through energy harvesting technologies which serve as suitable power supply substitutes, in many cases, for low power devices. With the proliferation of wireless energy in the environment through different radio frequency bands as well as natural sources like solar, wind and heat energy, it has become a desirable thing to take advantage of their availability by harvesting and converting them to useful electrical energy forms. The energy so harnessed or harvested could then be utilized in sensor nodes. Now, since these energy sources fluctuate from time to time, and from place to place, there is the need to have a form of energy accumulation, conversion, conditioning and storage. The stored energy would then be reconverted and used by the sensors nodes and/or RF transceivers when needed. The process through which this is done is referred to as energy management. In this research work, many types of energy harvesting transducers were explored including – solar, thermal, electromagnetic and piezo/vibration. A proof of concept approach for an on-demand electromagnetic power generator is then presented towards the end. While most, if not all, of the energy harvesting techniques discussed needed some time to accumulate enough charge to operate their respective systems, the on-demand energy harvester makes energy available as at and when needed. In summary, a system level design is presented with suggested future research works

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

Multi-purpose Electromagnetic Energy Harvesting System

This thesis proposes a multi-purpose electromagnetic energy harvesting system that harnesses mechanical energy from diverse types of mechanical motion sources and converts it into low power electrical energy. The harvested electrical energy is either used to supply power to low-power electronic devices or stored in an internal storage battery for later use. The proposed energy harvester can be i) mounted on a human’s knee, elbow, or hip, ii) hand-cranked, as well as iii) installed on any enclosure with fixed and movable parts (e.g., doors and/or windows). When mounted on a knee or hip, the device is actuated only during the so-called negative energy cycle of the motion and does not disturb the motion in the forward direction. The key building blocks of the proposed multi-purpose electromagnetic energy harvesting system is a new brushless AC electromagnetic generator, an adaptive motion translation mechanism and a smart power management system. The brushless AC generator consists of a new structure with a detachable rotor arrangement comprising mainly Neodymium rare-earth magnets mounted on an adjustable height rotor shaft and a stator made up of top and bottom flanges and a single continuous coil arrangement on a non-magnetic spool worn on a center magnetic stator core. The stator and rotor arrangement is carefully designed to allow for variable air gap so that the initial amount of torque required to move the rotor is adjustable and the amount of the generated output voltage can be controlled. Finite-element modeling magnetics (FEMM) simulation tool was used for the optimization of the new brushless generator, selecting the different generator materials, and determining the placement of the key components to achieve an efficient and truly adjustable system to the variation of frequencies and torque conditions. Furthermore, a gearbox was used as a mechanical up conversion mechanism to multiply the relatively low human motion to up to 5000 RPM at a walk pace of about one step per second. For this purpose, a three-stage spur gear system was designed using a roller-clutch at the front end to only allow motion during the negative cycle. The gearbox, when assembled together with the generator, works together with the adjustable height rotor to create the desired effect – adaptive, multi-purpose energy harvesting system. The power management design was optimized to maximum energy harvesting at rated RPM. When an external load is detected, the harvested power is routed to the external load, else, the power is routed to the internal storage battery for later use. The completed system generates between 2.5 watts and 7.5 watts of electrical power at an overall system efficiency of up to 84%