Energy harvesting system design and optimization for wireless sensor networks

Wireless sensor networks (WSN) are becoming widely adopted for many applications including complicated tasks like building energy management. However, one major concern for WSN technologies is the short lifetime and high maintenance cost due to the limited battery energy. One of the solutions is to scavenge ambient energy, which is then rectified to power the WSN. The objective of this thesis was to investigate the feasibility of an ultra-low energy consumption power management system suitable for harvesting sub-mW photovoltaic and thermoelectric energy to power WSNs. To achieve this goal, energy harvesting system architectures have been analyzed. Detailed analysis of energy storage units (ESU) have led to an innovative ESU solution for the target applications. Battery-less, long-lifetime ESU and its associated power management circuitry, including fast-charge circuit, self-start circuit, output voltage regulation circuit and hybrid ESU, using a combination of super-capacitor and thin film battery, were developed to achieve continuous operation of energy harvester. Low start-up voltage DC/DC converters have been developed for 1mW level thermoelectric energy harvesting. The novel method of altering thermoelectric generator (TEG) configuration in order to match impedance has been verified in this work. Novel maximum power point tracking (MPPT) circuits, exploring the fractional open circuit voltage method, were particularly developed to suit the sub-1mW photovoltaic energy harvesting applications. The MPPT energy model has been developed and verified against both SPICE simulation and implemented prototypes. Both indoor light and thermoelectric energy harvesting methods proposed in this thesis have been implemented into prototype devices. The improved indoor light energy harvester prototype demonstrates 81% MPPT conversion efficiency with 0.5mW input power. This important improvement makes light energy harvesting from small energy sources (i.e. credit card size solar panel in 500lux indoor lighting conditions) a feasible approach. The 50mm × 54mm thermoelectric energy harvester prototype generates 0.95mW when placed on a 60oC heat source with 28% conversion efficiency. Both prototypes can be used to continuously power WSN for building energy management applications in typical office building environment. In addition to the hardware development, a comprehensive system energy model has been developed. This system energy model not only can be used to predict the available and consumed energy based on real-world ambient conditions, but also can be employed to optimize the system design and configuration. This energy model has been verified by indoor photovoltaic energy harvesting system prototypes in long-term deployed experiments

An Integrated Approach to Energy Harvester Modeling and Performance Optimization

This paper proposes an integrated approach to energy harvester (EH) modeling and performance optimization where the complete mixed physical-domain EH (micro generator, voltage booster, storage element and load) can be modeled and optimized. We show that electrical equivalent models of the micro generator are inadequate for accurate prediction of the voltage booster’s performance. Through the use of hardware description language (HDL) we demonstrate that modeling the micro generator with analytical equations in the mechanical and magnetic domains provide an accurate model which has been validated in practice. Another key feature of the integrated approach is that it facilitates the incorporation of performance enhanced optimization, which as will be demonstrated is necessary due to the mechanicalelectrical interactions of an EH. A case study of a state-of-the-art vibration-based electromagnetic EH has been presented. We show that performance optimization can increase the energy harvesting rate by about 40%

Integrated approach to energy harvester mixed technology modelling and performance optimisation

An energy harvester is a system consisting of several components from different physical domains including mechanical, magnetic and electrical as well as the external circuits which regulate and store the generated energy. To design highly efficient energy harvesters, we believe that the various components of the energy harvesters need to be modelled together and in systematic manner using one simulation platform. We propose an accurate HDL model for the energy harvester and demonstrate its accuracy by validating it experimentally and comparing it with recently reported models. It is crucial to consider the various parts of the energy harvester in the context of a complete system, or else the gain at one part may come at the price of efficiency loss else where, rending the energy harvester much less efficient than before. The close mechanical-electrical interaction that takes place in energy harvesters, often lead to significant performance loss when the various parts of the energy harvesters are combined. Therefore, to address the performance loss, we propose an integrated approach to the energy harvester modelling and performance optimisation and demonstrate the effectiveness of employing such an approach by showing that it is possible to improve the performance of vibration-based energy harvester, in terms of the effective energy stored in the super-capacitor, by 33% through optimising the micro-generator mechanical parameters and the voltage booster circuit components

Design of Processing Circuitry for an RF Energy Harvester

Significant advancements in technology and the use of low power sensors in both commercial and industrial applications have made it essential to develop wireless solutions for low power devices. Once such solution, which has generated attention in university and R&D environments, is radio frequency (RF) energy harvesting. RF energy harvesting seeks to capture ambient RF energy by means of an antenna and convert this energy to useable DC power. The presence of ambient RF energy in the environment is a result of numerous high-frequency technologies including Wi-Fi, cell phones, microwave ovens, and radio broadcasting, as well as many others. The intention of this thesis is to design the processing circuitry necessary to convert a received RF signal into useable DC power, with the ability to charge a Lithium-Ion battery. The design presented here was performed to process an RF energy signal received from an antenna that targets both the 2.4GHz and 5GHz Wi-Fi bands. The final design consists of two bandpass filters (one for each Wi-FI band) two two-stage voltage doubler circuits (one for each Wi-Fi band), and a boost converter that is designed to achieve an output voltage of 3.2V in order to charge a Lithium-Ion battery. Testing of the RF energy harvester in an environment with ambient 2.4GHz Wi-Fi signals and a 470μF capacitor connected at the output demonstrates the circuit’s ability to harvest a measureable amount of energy. While the maximum measured voltage of 50mV does not meet the design specification of 3.2V, the circuit demonstrates proof-of-concept. Additional design improvements are necessary to make it a viable solution for charging a battery