CMOS indoor light energy harvesting system for wireless sensing applications

Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e de ComputadoresThis research thesis presents a micro-power light energy harvesting system for indoor environments. Light energy is collected by amorphous silicon photovoltaic (a-Si:H PV) cells, processed by a switched-capacitor (SC) voltage doubler circuit with maximum power point tracking (MPPT), and finally stored in a large capacitor. The MPPT Fractional Open Circuit Voltage (VOC) technique is implemented by an asynchronous state machine (ASM) that creates and, dynamically, adjusts the clock frequency of the step-up SC circuit, matching the input impedance of the SC circuit to the maximum power point (MPP) condition of the PV cells. The ASM has a separate local power supply to make it robust against load variations. In order to reduce the area occupied by the SC circuit, while maintaining an acceptable efficiency value, the SC circuit uses MOSFET capacitors with a charge reusing scheme for the bottom plate parasitic capacitors. The circuit occupies an area of 0.31 mm2 in a 130 nm CMOS technology. The system was designed in order to work under realistic indoor light intensities. Experimental results show that the proposed system, using PV cells with an area of 14 cm2, is capable of starting-up from a 0 V condition, with an irradiance of only 0.32 W/m2. After starting-up, the system requires an irradiance of only 0.18 W/m2 (18 mW/cm2) to remain in operation. The ASM circuit can operate correctly using a local power supply voltage of 453 mV, dissipating only 0.085 mW. These values are, to the best of the authors’ knowledge, the lowest reported in the literature. The maximum efficiency of the SC converter is 70.3% for an input power of 48 mW, which is comparable with reported values from circuits operating at similar power levels.Portuguese Foundation for Science and Technology (FCT/MCTES), under project PEst-OE/EEI/UI0066/2011, and to the CTS multiannual funding, through the PIDDAC Program funds. I am also very grateful for the grant SFRH/PROTEC/67683/2010, financially supported by the IPL – Instituto Politécnico de Lisboa

An Energy Harvesting Solution for IoT Sensors Using MEMS Technology

The significant development of IoT sensors will play a critical role in a large number of applications. It is predicted that billions of IoT sensors will be used worldwide by 2020 [1]. Batteries are commonly utilized to power on sensors, but they are depleted and they require maintenance and replacement. Battery replacement for billions of sensors is a daunting task and battery disposal for IoT sensors can become an environmental problem. Energy harvesting from ambient sources presents a viable solution to overcome these problems. Among all energy sources, light is considered as one of the best sources due to its high energy density and availability in both indoor and outdoor environments. In order to make an energy harvesting system efficient, many methods have been proposed in the literature to extract the maximum energy while minimizing the power consumption by the energy harvesting circuitry. In this work, a boost converter circuit is designed using MEMS-based switches to reduce the leakage current and power loss caused by conventional transistor-based switches. A light energy harvesting method is also proposed utilizing available components of a typical IoT sensor. The reuse of available components in the proposed solution reduces the overall power consumption and the area overhead of the energy harvesting solution

Power Management ICs for Internet of Things, Energy Harvesting and Biomedical Devices

This dissertation focuses on the power management unit (PMU) and integrated circuits (ICs) for the internet of things (IoT), energy harvesting and biomedical devices. Three monolithic power harvesting methods are studied for different challenges of smart nodes of IoT networks. Firstly, we propose that an impedance tuning approach is implemented with a capacitor value modulation to eliminate the quiescent power consumption. Secondly, we develop a hill-climbing MPPT mechanism that reuses and processes the information of the hysteresis controller in the time-domain and is free of power hungry analog circuits. Furthermore, the typical power-performance tradeoff of the hysteresis controller is solved by a self-triggered one-shot mechanism. Thus, the output regulation achieves high-performance and yet low-power operations as low as 12 µW. Thirdly, we introduce a reconfigurable charge pump to provide the hybrid conversion ratios (CRs) as 1⅓× up to 8× for minimizing the charge redistribution loss. The reconfigurable feature also dynamically tunes to maximum power point tracking (MPPT) with the frequency modulation, resulting in a two-dimensional MPPT. Therefore, the voltage conversion efficiency (VCE) and the power conversion efficiency (PCE) are enhanced and flattened across a wide harvesting range as 0.45 to 3 V. In a conclusion, we successfully develop an energy harvesting method for the IoT smart nodes with lower cost, smaller size, higher conversion efficiency, and better applicability. For the biomedical devices, this dissertation presents a novel cost-effective automatic resonance tracking method with maximum power transfer (MPT) for piezoelectric transducers (PT). The proposed tracking method is based on a band-pass filter (BPF) oscillator, exploiting the PT’s intrinsic resonance point through a sensing bridge. It guarantees automatic resonance tracking and maximum electrical power converted into mechanical motion regardless of process variations and environmental interferences. Thus, the proposed BPF oscillator-based scheme was designed for an ultrasonic vessel sealing and dissecting (UVSD) system. The sealing and dissecting functions were verified experimentally in chicken tissue and glycerin. Furthermore, a combined sensing scheme circuit allows multiple surgical tissue debulking, vessel sealer and dissector (VSD) technologies to operate from the same sensing scheme board. Its advantage is that a single driver controller could be used for both systems simplifying the complexity and design cost. In a conclusion, we successfully develop an ultrasonic scalpel to replace the other electrosurgical counterparts and the conventional scalpels with lower cost and better functionality

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

Design of Low-Cost Energy Harvesting and Delivery Systems for Self-Powered Devices: Application to Authentication IC

This thesis investigates the development of low-cost energy harvesting and delivery systems for low-power low-duty-cycle devices. Initially, we begin by designing a power management scheme for on-demand power delivery. The baseline implementation is also used to identify critical challenges for low-power energy harvesting. We further propose a robust self-powered energy harvesting and delivery system (EHDS) design as a solution to achieve energy autonomy in standalone systems. The design demonstrates a complete ecosystem for low-overhead pulse-frequency modulated (PFM) harvesting while reducing harvesting window confinement and overall implementation footprint. Two transient-based models are developed for improved accuracy during design space exploration and optimization for both PFM power conversion and energy harvesting. Finally, a low-power authentication IC is demonstrated and projected designs for self-powered System-on-Chips (SoCs) are presented. The proposed designs are proto-typed in two test-chips in a 65nm CMOS process and measurement data showcase improved performance in terms of battery power, cold-start duration, passives (inductance and capacitance) needed, and end-to-end harvesting/conversion efficiency.Ph.D

Smart energy management and conversion

This chapter introduced power management circuits and energy storage unit designs for sub‐1 mW low power energy harvesting technologies, including indoor light energy harvesting, thermoelectric energy harvesting and vibration energy harvesting. The solutions address several of the problems associated with energy harvesting, power management and storage issues including low voltage operation, self‐start, efficiency (conversion efficiency as well as impact of power consumption of the power management circuit itself), energy density and leakage current levels. Additionally, efforts to miniaturize and integrate magnetic parts as well as integrate discrete circuits onto silicon are outlined to offer improvements in cost, size and efficiency. Finally initial results from efforts to improve energy density of storage devices using nanomaterials are introduced

Maximum power point tracking and control of grid interfacing PV systems

Grid interfacing of PV systems is very crucial for their future deployment. To address some drawbacks of model-based maximum power point tracking (MPPT) techniques, new optimum proportionality constant values based on the variation of temperature and irradiance are proposed for fractional open circuit voltage (FOCV) and fraction short circuit current (FSCC) MPPT. The two MPPT controllers return their optimum proportionality values to gain high tracking efficiency when a change occurred to temperature and/or irradiance. A modified variable step-size incremental conductance MPPT technique for PV system is proposed. In the new MPPT technique, a new autonomous scaling factor based on the PV module voltage in a restricted search range to replace the fixed scaling factor in the conventional variable step-size algorithm is proposed. Additionally, a slope angle variation algorithm is also developed. The proposed MPPT technique demonstrates faster tracking speed with minimum oscillations around MPP both at steady-state and dynamic conditions with overall efficiency of about 99.70%. The merits of the proposed MPPT technique are verified using simulation and practical experimentation. A new 0.8Voc model technique to estimate the peak global voltage under partial shading condition for medium voltage megawatt photovoltaic system integration is proposed. The proposed technique consists of two main components; namely, peak voltage and peak voltage deviation correction factor. The proposed 0.8Voc model is validated by using MATLAB simulation. The results show high tracking efficiency with minimum deviations compared to the conventional counterpart. The efficiency of the conventional 0.8 model is about 93% while that of the proposed is 99.6%. Control issues confronting grid interfacing PV system is investigated. The proposed modified 0.8Voc model is utilized to optimise the active power level in the grid interfacing of multimegawatt photovoltaic system under normal and partial shading conditions. The active power from the PV arrays is 5 MW, while the injected power into the ac is 4.73 MW, which represents 95% of the PV arrays power at normal condition. Similarly, during partial shading conditions, the active power of PV module is 2 MW and the injected power is 1.89 MW, which represents 95% of PV array power at partial shading conditions. The technique demonstrated the capability of saving high amount of grid power.Grid interfacing of PV systems is very crucial for their future deployment. To address some drawbacks of model-based maximum power point tracking (MPPT) techniques, new optimum proportionality constant values based on the variation of temperature and irradiance are proposed for fractional open circuit voltage (FOCV) and fraction short circuit current (FSCC) MPPT. The two MPPT controllers return their optimum proportionality values to gain high tracking efficiency when a change occurred to temperature and/or irradiance. A modified variable step-size incremental conductance MPPT technique for PV system is proposed. In the new MPPT technique, a new autonomous scaling factor based on the PV module voltage in a restricted search range to replace the fixed scaling factor in the conventional variable step-size algorithm is proposed. Additionally, a slope angle variation algorithm is also developed. The proposed MPPT technique demonstrates faster tracking speed with minimum oscillations around MPP both at steady-state and dynamic conditions with overall efficiency of about 99.70%. The merits of the proposed MPPT technique are verified using simulation and practical experimentation. A new 0.8Voc model technique to estimate the peak global voltage under partial shading condition for medium voltage megawatt photovoltaic system integration is proposed. The proposed technique consists of two main components; namely, peak voltage and peak voltage deviation correction factor. The proposed 0.8Voc model is validated by using MATLAB simulation. The results show high tracking efficiency with minimum deviations compared to the conventional counterpart. The efficiency of the conventional 0.8 model is about 93% while that of the proposed is 99.6%. Control issues confronting grid interfacing PV system is investigated. The proposed modified 0.8Voc model is utilized to optimise the active power level in the grid interfacing of multimegawatt photovoltaic system under normal and partial shading conditions. The active power from the PV arrays is 5 MW, while the injected power into the ac is 4.73 MW, which represents 95% of the PV arrays power at normal condition. Similarly, during partial shading conditions, the active power of PV module is 2 MW and the injected power is 1.89 MW, which represents 95% of PV array power at partial shading conditions. The technique demonstrated the capability of saving high amount of grid power

Power Management Techniques for Micropower Energy Scavenging

Advances in semi-conductor technology have led to the reduction in size and power consumption of microelectronic circuits. With the miniaturization and increased efficiency of these circuits there are more potential applications for wireless sensor networks and portable electronic equipment. These applications include structural integrity and environment monitoring such as aircraft wing health monitoring and forest fire and natural disaster detection. Biomedical devices have also benefited from the improved size and performance of microelectronics. This thesis studies power management techniques to enable efficient energy scavenging at micropower input power levels from a number of power sources. These sources range from temperature gradients, radio frequency (RF) radiation, solar power, and mechanical vibrations. The scavenged energy is used to improve the performance and distribution of wireless sensors and devices by supplementing or potentially replacing the local power supply of the sensor or device. The major focus of this thesis is to combine source characterization, power management theory, detailed power loss analysis, and ultra-low power circuit design to maximize the extraction of energy from source and deliver it to the wireless sensor or device. The resistor emulation techniques from power factor correction (PFC) are leveraged to load an RF rectifying antenna (rectenna) such that maximum power point tracking (MPPT) of the rectenna is achieved naturally. An application specific integrated circuit (ASIC) is developed to implement this technique after experimental verification with commercially available discrete circuitry. Experimental results show efficient energy scavenging at power levels below 2 microwatts. In addition to resistor emulation, synchronous electric charge extraction (SECE) for energy scavenging from piezoelectric generators is also investigated. The presented techniques allow for the scavenging of usable power for sensors at power levels significantly lower than previous research

Circuits and Systems for Energy Harvesting and Internet of Things Applications

The Internet of Things (IoT) continues its growing trend, while new “smart” objects are con-stantly being developed and commercialized in the market. Under this paradigm, every common object will be soon connected to the Internet: mobile and wearable devices, electric appliances, home electronics and even cars will have Internet connectivity. Not only that, but a variety of wireless sensors are being proposed for different consumer and industrial applications. With the possibility of having hundreds of billions of IoT objects deployed all around us in the coming years, the social implications and the economic impact of IoT technology needs to be seriously considered. There are still many challenges, however, awaiting a solution in order to realize this future vision of a connected world. A very important bottleneck is the limited lifetime of battery powered wireless devices. Fully depleted batteries need to be replaced, which in perspective would generate costly maintenance requirements and environmental pollution. However, a very plausible solution to this dilemma can be found in harvesting energy from the ambient. This dissertation focuses in the design of circuits and system for energy harvesting and Internet of Things applications. The first part of this dissertation introduces the research motivation and fundamentals of energy harvesting and power management units (PMUs). The architecture of IoT sensor nodes and PMUs is examined to observe the limitations of modern energy harvesting systems. Moreover, several architectures for multisource harvesting are reviewed, providing a background for the research presented here. Then, a new fully integrated system architecture for multisource energy harvesting is presented. The design methodology, implementation, trade-offs and measurement results of the proposed system are described. The second part of this dissertation focus on the design and implementation of low-power wireless sensor nodes for precision agriculture. First, a sensor node incorporating solar energy harvesting and a dynamic power management strategy is presented. The operation of a wireless sensor network for soil parameter estimation, consisting of four nodes is demonstrated. After that, a solar thermoelectric generator (STEG) prototype for powering a wireless sensor node is proposed. The implemented solar thermoelectric generator demonstrates to be an alternative way to harvest ambient energy, opening the possibility for its use in agricultural and environmental applications. The open problems in energy harvesting for IoT devices are discussed at the end, to delineate the possible future work to improve the performance of EH systems. For all the presented works, proof-of-concept prototypes were fabricated and tested. The measured results are used to verify their correct operation and performance

Robustness and durability aspects in the design of power management circuits for IoT applications

With the increasing interest in the heterogeneous world of the “Internet of Things” (IoT), new compelling challenges arise in the field of electronic design, especially concerning the development of innovative power management solutions. Being this diffusion a consolidated reality nowadays, emerging needs like lifetime, durability and robustness are becoming the new watchwords for power management, being a common ground which can dramatically improve service life and confidence in these devices. The possibility to design nodes which do not need external power supply is a crucial point in this scenario. Moreover, the development of autonomous nodes which are substantially maintenance free, and which therefore can be placed in unreachable or harsh environments is another enabling aspect for the exploitation of this technology. In this respect, the study of energy harvesting techniques is increasingly earning interest again. Along with efficiency aspects, degradation aspects are the other main research field with respect to lifetime, durability and robustness of IoT devices, especially related to aging mechanisms which are peculiar in power management and power conversion circuits, like for example battery wear during usage or hot-carrier degradation (HCD) in power MOSFETs. In this thesis different aspects related to lifetime, durability and robustness in the field of power management circuits are studied, leading to interesting contributions. Innovative designs of DC/DC power converters are studied and developed, especially related to reliability aspects of the use of electrochemical cells as power sources. Moreover, an advanced IoT node is proposed, based on energy harvesting techniques, which features an intelligent dynamically adaptive power management circuit. As a further contribution, a novel algorithm is proposed, which is able to effectively estimate the efficiency of a DC/DC converter for photovoltaic applications at runtime. Finally, an innovative DC/DC power converter with embedded monitoring of hot-carrier degradation in power MOSFETs is designed