Alex S. Weddell

Accurate Supercapacitor Modeling for Energy Harvesting Wireless Sensor Nodes

Supercapacitors are often used in energy harvesting wireless sensor nodes (EH-WSNs) to store harvested energy. Until now, research into the use of supercapacitors in EH-WSNs has considered them to be ideal or oversimplified, with non-ideal behavior attributed to substantial leakage currents. In this brief, we show that observations previously attributed to leakage are predominantly due to redistribution of charge inside the supercapacitor. We confirm this hypothesis through the development of a circuit-based model, which accurately represents non-ideal behavior. The model correlates well with practical validations representing the operation of an EH-WSN and allows behavior to be simulated over long periods.

A survey of multi-source energy harvesting systems

Energy harvesting allows low-power embedded devices to be powered from naturally-ocurring or unwanted environmental energy (e.g. light, vibration, or temperature difference). While a number of systems incorporating energy harvesters are now available commercially, they are specific to certain types of energy source. Energy availability can be a temporal as well as spatial effect. To address this issue, ‘hybrid’ energy harvesting systems combine multiple harvesters on the same platform, but the design of these systems is not straight-forward. This paper surveys their design, including trade-offs affecting their efficiency, applicability, and ease of deployment. This survey, and the taxonomy of multi-source energy harvesting systems that it presents, will be of benefit to designers of future systems. Furthermore, we identify and comment upon the current and future research directions in this field.

Hibernus: Sustaining Computation During Intermittent Supply for Energy-Harvesting Systems

A key challenge to the future of energy-harvesting systems is the discontinuous power supply that is often generated. We propose a new approach, Hibernus, which enables computation to be sustained during intermittent supply. The approach has a low energy and time overhead which is achieved by reactively hibernating: saving system state only once, when power is about to be lost, and then sleeping until the supply recovers. We validate the approach experimentally on a processor with FRAM nonvolatile memory, allowing it to reactively hibernate using only energy stored in its decoupling capacitance. When compared to a recently proposed technique, the approach reduces processor time and energy overheads by 76%-100% and 49%-79% respectively.

A comparison of power output from linear and nonlinear kinetic energy harvesters using real vibration data

The design of vibration energy harvesters (VEHs) is highly dependent upon the characteristics of the environmental vibrations present in the intended application. VEHs can be linear resonant systems tuned to particular frequencies or non-linear systems with either bi-stable operation or a Duffing-type response. This paper provides detailed vibration data from a range of applications, which has been made freely available for download through the Energy Harvesting Network’s online data repository. In particular, this research shows that simulation is essential in designing and selecting the most suitable vibration energy harvester for particular applications. This is illustrated through C-based simulations of different types of VEHs, using real vibration data from a diesel ferry engine, a combined heat and power pump, a petrol car engine and a helicopter. The analysis shows that a bistable energy harvester only has a higher output power than a linear or Duffing-type nonlinear energy harvester with the same Q-factor when it is subjected to white noise vibration. The analysis also indicates that piezoelectric transduction mechanisms are more suitable for bistable energy harvesters than electromagnetic transduction. Furthermore, the linear energy harvester has a higher output power compared to the Duffing-type nonlinear energy harvester with the same Q factor in most cases. The Duffing-type nonlinear energy harvester can generate more power than the linear energy harvester only when it is excited at vibrations with multiple peaks and the frequencies of these peaks are within its bandwidth. Through these new observations, this paper illustrates the importance of simulation in the design of energy harvesting systems, with particular emphasis on the need to incorporate real vibration data.

Photovoltaic Sample-and-Hold Circuit Enabling MPPT Indoors for Low-Power Systems

Photovoltaic (PV) energy harvesting is commonly used to power autonomous devices, and maximum power point tracking (MPPT) is often used to optimize its efficiency. This paper describes an ultra low-power MPPT circuit with a novel sample-and-hold and cold-start arrangement, enabling MPPT across the range of light intensities found indoors, which has not been reported before. The circuit has been validated in practice and found to cold-start and operate from 100 lux (typical of dim indoor lighting) up to 5000 lux with a 55 cm2 amorphous silicon PV module. It is more efficient than non-MPPT circuits, which are the state-of-the-art for indoor PV systems. The proposed circuit maximizes the active time of the PV module by carrying out samples only once per minute. The MPPT control arrangement draws a quiescent current draw of only 8 μA, and does not require an additional light sensor as has been required by previously reported low-power MPPT circuits.

A traffic-aware street lighting scheme for Smart Cities using autonomous networked sensors

Display Omitted TALiSMaN detects road users and sets streetlight brightness appropriately.A utility model is detailed to quantify the usefulness of street lighting.Street lighting schemes are evaluated with StreetlightSim.TALiSMaN offers comparable usefulness as conventional lighting schemes.TALiSMaN consumes 2-55% of the energy of conventional/state-of-the-art schemes. Street lighting is a ubiquitous utility, but sustaining its operation presents a heavy financial and environmental burden. Many schemes have been proposed which selectively dim lights to improve energy efficiency, but little consideration has been given to the usefulness of the resultant street lighting system. This paper proposes a real-time adaptive lighting scheme, which detects the presence of vehicles and pedestrians and dynamically adjusts their brightness to the optimal level. This improves the energy efficiency of street lighting and its usefulness; a streetlight utility model is presented to evaluate this. The proposed scheme is simulated using an environment modelling a road network, its users, and a networked communication system - and considers a real streetlight topology from a residential area. The proposed scheme achieves similar or improved utility to existing schemes, while consuming as little as 1-2% of the energy required by conventional and state-of-the-art techniques.

Hibernus++: A Self-Calibrating and Adaptive System for Transiently-Powered Embedded Devices

Energy harvesters are being used to power autonomous systems, but their output power is variable and intermittent. To sustain computation, these systems integrate batteries or supercapacitors to smooth out rapid changes in harvester output. Energy storage devices require time for charging and increase the size, mass, and cost of systems. The field of transient computing moves away from this approach, by powering the system directly from the harvester output. To prevent an application from having to restart computation after a power outage, approaches such as Hibernus allow these systems to hibernate when supply failure is imminent. When the supply reaches the operating threshold, the last saved state is restored and the operation is continued from the point it was interrupted. This paper proposes Hibernus++ to intelligently adapt the hibernate and restore thresholds in response to source dynamics and system load properties. Specifically, capabilities are built into the system to autonomously characterize the hardware platform and its performance during hibernation in order to set the hibernation threshold at a point which minimizes wasted energy and maximizes computation time. Similarly, the system auto-calibrates the restore threshold depending on the balance of energy supply and consumption in order to maximize computation time. Hibernus++ is validated both theoretically and experimentally on microcontroller hardware using both synthesized and real energy harvesters. Results show that Hibernus++ provides an average 16% reduction in energy consumption and an improvement of 17% in application execution time over state-of-the-art approaches.

Graceful Performance Modulation for Power-Neutral Transient Computing Systems

Transient computing systems do not have energy storage, and operate directly from energy harvesting. These systems are often faced with the inherent challenge of low-current or transient power supply. In this paper, we propose “power-neutral” operation, a new paradigm for such systems, whereby the instantaneous power consumption of the system must match the instantaneous harvested power. Power neutrality is achieved using a control algorithm for dynamic frequency scaling, modulating system performance gracefully in response to the incoming power. Detailed system model is used to determine design parameters for selecting the system voltage thresholds where the operating frequency will be raised or lowered, or the system will be hibernated. The proposed control algorithm for power-neutral operation is experimentally validated using a microcontroller incorporating voltage threshold-based interrupts for frequency scaling. The microcontroller is powered directly from real energy harvesters; results demonstrate that a power-neutral system sustains operation for 4%-88% longer with up to 21% speedup in application execution.

Approaches to Transient Computing for Energy Harvesting Systems: A Quantitative Evaluation

Systems operating from harvested sources typically integrate batteries or supercapacitors to smooth out rapid changes in harvester output. However, such energy storage devices require time for charging and increase the size, mass and cost of the system. A recent approach to address this is to power systems directly from the harvester output, termed transient computing. To solve the problem of having to restart computation from the start due to power-cycles, a number of techniques have been proposed to deal with transient power sources. In this paper, we quantitatively evaluate three state-of-the-art approaches on a Texas Instruments MSP430 microcontroller characterizing the application scenarios where each performs best. Finally, recommendations are provided to system designers for selecting the most suitable approach.

Modular Plug-and-Play Power Resources for Energy-Aware Wireless Sensor Nodes

Wireless sensors are normally powered by nonrechargeable batteries, but these must be replaced when depleted. Recent developments in energy harvesting technology allow sensors to be powered by environmental energy where it is present, but the wide range of situations where sensors are deployed means that it is desirable for the energy components of a sensor node (i.e. batteries, supercapacitors, and power generation devices) to be selected and configured at the time of node deployment. Previous energy harvesting-powered systems have been designed for specific energy hardware and been difficult to adapt for different resources. Energy-awareness is useful for state-of-the-art network algorithms, but present systems do not provide a standardized or straightforward way for nodes to monitor and manage their energy hardware. The developments reported in this paper deliver a reconfigurable energy subsystem for wireless autonomous sensors. The new system permits energy modules to be selected and fitted to the sensor node in-situ, in a plug-and-play manner, without the need for reprogramming or the modification of hardware. The node can monitor and intelligently manage its energy resources and assess its overall energy status by analyzing its level of stored energy and rate of power generation. These activities are facilitated by a proposed common hardware interface (which allows multiple energy modules to be connected) and an electronic datasheet structure for the energy modules. The system has been verified through the development and testing of a prototype wireless sensor node which operates from a mix of energy sources.