Portable power management systems must optimise power interfacing, storage and routing, to meet application specific functionality requirements. Two key aspects are reliability and efficiency. For reliable operation, it is required that powering on/off the system must occur in a planned manner. For efficient operation, it is desired that the system is powered for an optimal amount of time. maximizing its useful operational outcome per unit of energy consumed. This can be achieved by optimizing energy usage based on the anticipated energy income and power demand of duty-cycled power consumers. Both battery and supercapacitor storage can be employed to meet energy and power density demand, on both sides, and to enable fast transition from cold-starting to active power management. A simplified model is used to calculate the reliability of a simple solar-powered microsystem. The modelling of dynamically configurable interfacing and storage may enable a new generation of power management, providing reliable power from irregular and small energy sources.

As industrial and commercial demand for thin, small-footprint energy storage devices increases (e.g., for wearable electronics, wireless sensor networks, etc.), it is essential to develop theoretical descriptions for those devices in order to make effective design choices. Of particular interest are porous interdigitated electrodes, which can function as supercapacitors but which are nontrivial to analyze due to their unique geometry. In this paper, we develop a purely mathematical model to determine the dependence of a cell's capacitance and/or resistance on electrode height, width, and spacing, and electrolyte layer height. We then extend this model to incorporate effects from the porous nature of the electrodes, and show that in many cases of interest, the system can be described using a simple equivalent circuit. (C) 2017 The Electrochemical Society. All rights reserved.

We utilize particle swarm optimization to reduce the size of the energy management components in an energy harvesting system, allowing us to eliminate the need for voltage regulators or DC-DC converters without affecting system performance. Prior literature on optimal power management in microelectronics [1, 2] has relied on engineering estimates or exhaustive parameter searches to optimize system design. No prior literature has considered the optimal design of a device with only passive components [3]. By using particle swarm optimization, we demonstrate a 55% reduction in device size relative to conventional engineering calculations of an optimal device design.

We demonstrate a wireless sensor node (WSN) that operates purely on harvested ambient indoor light energy and regulates its duty cycle via voltage-triggered sensing and transmission. The extremely low-power light found in indoor environments can be considered at first sight as unsuitable for high-power load demands characteristic of radios [1], but by leveraging spectrum-tailored solar cells, trickle charging a high-power energy reservoir, and implementing triggered duty cycling, we show that these power demands can be consistently met. All energy harvesting and storage components are fabricated in our labs.

Flexibility, lightness and printability make organic solar cells (OSC) strong candidates to power low consumption devices such as envisioned for the Internet of Things. Such devices may be placed indoors, where light levels are well below typical outdoors level. Here, we demonstrate that maximizing the efficiency of OSC for indoor operation requires specific device optimization. In particular, minimizing the dark current of the solar cells is critical to enhance their efficiency under indoor light. Cells optimized for sunlight reach 6.2% power conversion efficiency (PCE). However when measured under simulated indoor light conditions, the PCE is to 5.2%. Cells optimized for indoor operation yield 7.6% of PCE under indoor conditions. As a proof-of-concept, the solar cells are combined with fully printed super-capacitors to form a photo-rechargeable system. Such a system with a 0.475cm2 indoor-optimized solar cell achieved a total energy conversion and storage efficiency (ECSE) of 1.57% under 1-sun, providing 26mJ of energy and 4.1mW of maximum power. Under simulated indoor light the system yielded an ECSE of 2.9%, while delivering 13.3mJ and 2.8mW. Those energy and power levels would be sufficient to power low-consumption electronic devices with low duty cycles.

Manufacture and performance of a composite carbon-based supercapacitor that employs a gel polymer ionic liquid electrolyte to achieve stable, long cycle life, high-current draw energy storage is discussed in this paper. This supercapacitor when cycled galvanostatically can achieve a discharge capacitance of 43.0 mF per square centimeter of substrate by leveraging the strengths of a composite electrode composition. The printed manufacturing process takes place in ambient conditions at room temperature enabling high-current, rechargeable energy storage to be built onto many substrates. Single-cell discharge power densities have reached 404 μW/cm2 which could enable many technologies when paired with a MEMS energy harvester.

Over the last 10 years, the Structural Health Monitoring (SHM) field has struggled to replace human-based inspections of structures with autonomous sensor networks and classification algorithms. The goal of the SHM community has been to endow structures with an artificial nervous system similar to that of living organisms. This paper proposes a new paradigm which leverages the human nervous system in concert with distributed sensor networks and computational resources. We propose using emerging haptic technology to create a harmonious collaboration between humans, SHM sensor networks, and statistical classification. The neuroscience community has demonstrated haptic-based methods for replacing lost sensations. However, this project explores the possibility of giving humans a new sense – one which reflects the health of a structure. The generation of this sense is achieved through a vibro-haptic human-machine interface. The testbed is composed of a surrogate three-story structure which can be modified to exhibit non-linear dynamic responses on any combination of its three floors. With the use of a vibro-haptic interface, we will study the ability of human users to determine the characteristics of non-linear response. Establishing this intimate connection between humans and structures is the first step in creating a new SHM paradigm that combines human intelligence with distributed measurement capabilities.