Microprocessor based signal processing techniques for system identification and adaptive control of DC-DC converters

PhD ThesisMany industrial and consumer devices rely on switch mode power converters (SMPCs) to provide a reliable, well regulated, DC power supply. A poorly performing power supply can potentially compromise the characteristic behaviour, efficiency, and operating range of the device. To ensure accurate regulation of the SMPC, optimal control of the power converter output is required. However, SMPC uncertainties such as component variations and load changes will affect the performance of the controller. To compensate for these time varying problems, there is increasing interest in employing real-time adaptive control techniques in SMPC applications. It is important to note that many adaptive controllers constantly tune and adjust their parameters based upon on-line system identification. In the area of system identification and adaptive control, Recursive Least Square (RLS) method provide promising results in terms of fast convergence rate, small prediction error, accurate parametric estimation, and simple adaptive structure. Despite being popular, RLS methods often have limited application in low cost systems, such as SMPCs, due to the computationally heavy calculations demanding significant hardware resources which, in turn, may require a high specification microprocessor to successfully implement. For this reason, this thesis presents research into lower complexity adaptive signal processing and filtering techniques for on-line system identification and control of SMPCs systems. The thesis presents the novel application of a Dichotomous Coordinate Descent (DCD) algorithm for the system identification of a dc-dc buck converter. Two unique applications of the DCD algorithm are proposed; system identification and self-compensation of a dc-dc SMPC. Firstly, specific attention is given to the parameter estimation of dc-dc buck SMPC. It is computationally efficient, and uses an infinite impulse response (IIR) adaptive filter as a plant model. Importantly, the proposed method is able to identify the parameters quickly and accurately; thus offering an efficient hardware solution which is well suited to real-time applications. Secondly, new alternative adaptive schemes that do not depend entirely on estimating the plant parameters is embedded with DCD algorithm. The proposed technique is based on a simple adaptive filter method and uses a one-tap finite impulse response (FIR) prediction error filter (PEF). Experimental and simulation results clearly show the DCD technique can be optimised to achieve comparable performance to classic RLS algorithms. However, it is computationally superior; thus making it an ideal candidate technique for low cost microprocessor based applications.Iraq Ministry of Higher Educatio

Enabling low cost test and tuning of difficult-to-measure device specifications: application to DC-DC converters and high speed devices

Low-cost test and tuning methods for difficult-to-measure specifications are presented in this research from the following perspectives: 1)"Safe" test and self-tuning for power converters: To avoid the risk of device under test (DUT) damage during conventional load/line regulation measurement on power converter, a "safe" alternate test structure is developed where the power converter (boost/buck converter) is placed in a different mode of operation during alternative test (light switching load) as opposed to standard test (heavy switching load) to prevent damage to the DUT during manufacturing test. Based on the alternative test structure, self-tuning methods for both boost and buck converters are also developed in this thesis. In addition, to make these test structures suitable for on-chip built-in self-test (BIST) application, a special sensing circuit has been designed and implemented. Stability analysis filters and appropriate models are also implemented to predict the DUT’s electrical stability condition during test and to further predict the values of tuning knobs needed for the tuning process. 2) High bandwidth RF signal generation: Up-convertion has been widely used in high frequency RF signal generation but mixer nonlinearity results in signal distortion that is difficult to eliminate with such methods. To address this problem, a framework for low-cost high-fidelity wideband RF signal generation is developed in this thesis. Depending on the band-limited target waveform, the input data for two interleaved DACs (digital-to-analog converters) system is optimized by a matrix-model-based algorithm in such a way that it minimizes the distortion between one of its image replicas in the frequency domain and the target RF waveform within a specified signal bandwidth. The approach is used to demonstrate how interferers with specified frequency characteristics can be synthesized at low cost for interference testing of RF communications systems. The frameworks presented in this thesis have a significant impact in enabling low-cost test and tuning of difficult-to-measure device specifications for power converter and high-speed devices.Ph.D

On-chip adaptive power management for WPT-Enabled IoT

Internet of Things (IoT), as broadband network connecting every physical objects, is becoming more widely available in various industrial, medical, home and automotive applications. In such network, the physical devices, vehicles, medical assistance, and home appliances among others are supposed to be embedded by sensors, actuators, radio frequency (RF) antennas, memory, and microprocessors, such that these devices are able to exchange data and connect with other devices in the network. Among other IoT’s pillars, wireless sensor network (WSN) is one of the main parts comprising massive clusters of spatially distributed sensor nodes dedicated for sensing and monitoring environmental conditions. The lifetime of a WSN is greatly dependent on the lifetime of the small sensor nodes, which, in turn, is primarily dependent on energy availability within every sensor node. Predominantly, the main energy source for a sensor node is supplied by a small battery attached to it. In a large WSN with massive number of deployed sensor nodes, it becomes a challenge to replace the batteries of every single sensor node especially for sensor nodes deployed in harsh environments. Consequently, powering the sensor nodes becomes a key limiting issue, which poses important challenges for their practicality and cost. Therefore, in this thesis we propose enabling WSN, as the main pillar of IoT, by means of resonant inductive coupling (RIC) wireless power transfer (WPT). In order to enable efficient energy delivery at higher range, high quality factor RIC-WPT system is required in order to boost the magnetic flux generated at the transmitting coil. However, an adaptive front-end is essential for self-tuning the resonant tank against any mismatch in the components values, distance variation, and interference from close metallic objects. Consequently, the purpose of the thesis is to develop and design an adaptive efficient switch-mode front-end for self-tuning in WPT receivers in multiple receiver system. The thesis start by giving background about the IoT system and the technical bottleneck followed by the problem statement and thesis scope. Then, Chapter 2 provides detailed backgrounds about the RIC-WPT system. Specifically, Chapter 2 analyzes the characteristics of different compensation topologies in RIC-WPT followed by the implications of mistuning on efficiency and power transfer capability. Chapter 3 discusses the concept of switch-mode gyrators as a potential candidate for generic variable reactive element synthesis while different potential applications and design cases are provided. Chapter 4 proposes two different self-tuning control for WPT receivers that utilize switch-mode gyrators as variable reactive element synthesis. The performance aspects of control approaches are discussed and evaluated as well in Chapter 4. The development and exploration of more compact front-end for self-tuned WPT receiver is investigated in Chapter 5 by proposing a phase-controlled switched inductor converter. The operation and design details of different switch-mode phase-controlled topologies are given and evaluated in the same chapter. Finally, Chapter 6 provides the conclusions and highlight the contribution of the thesis, in addition to suggesting the related future research topics.Internet de las cosas (IoT), como red de banda ancha que interconecta cualquier cosa, se está estableciendo como una tecnología valiosa en varias aplicaciones industriales, médicas, domóticas y en el sector del automóvil. En dicha red, los dispositivos físicos, los vehículos, los sistemas de asistencia médica y los electrodomésticos, entre otros, incluyen sensores, actuadores, subsistemas de comunicación, memoria y microprocesadores, de modo que son capaces de intercambiar datos e interconectarse con otros elementos de la red. Entre otros pilares que posibilitan IoT, la red de sensores inalámbricos (WSN), que es una de las partes cruciales del sistema, está formada por un conjunto masivo de nodos de sensado distribuidos espacialmente, y dedicados a sensar y monitorizar las condiciones del contexto de las cosas interconectadas. El tiempo de vida útil de una red WSN depende estrechamente del tiempo de vida de los pequeños nodos sensores, los cuales, a su vez, dependen primordialmente de la disponibilidad de energía en cada nodo sensor. La fuente principal de energía para un nodo sensor suele ser una pequeña batería integrada en él. En una red WSN con muchos nodos y con una alta densidad, es un desafío el reemplazar las baterías de cada nodo sensor, especialmente en entornos hostiles, como puedan ser en escenarios de Industria 4.0. En consecuencia, la alimentación de los nodos sensores constituye uno de los cuellos de botella que limitan un despliegue masivo práctico y de bajo coste. A tenor de estas circunstancias, en esta tesis doctoral se propone habilitar las redes WSN, como pilar principal de sistemas IoT, mediante sistemas de transferencia inalámbrica de energía (WPT) basados en acoplamiento inductivo resonante (RIC). Con objeto de posibilitar el suministro eficiente de energía a mayores distancias, deben aumentarse los factores de calidad de los elementos inductivos resonantes del sistema RIC-WPT, especialmente con el propósito de aumentar el flujo magnético generado por el inductor transmisor de energía y su acoplamiento resonante en recepción. Sin embargo, dotar al cabezal electrónico que gestiona y condicionada el flujo de energía de capacidad adaptativa es esencial para conseguir la autosintonía automática del sistema acoplado y resonante RIC-WPT, que es muy propenso a la desintonía ante desajustes en los parámetros nominales de los componentes, variaciones de distancia entre transmisor y receptores, así como debido a la interferencia de objetos metálicos. Es por tanto el objetivo central de esta tesis doctoral el concebir, proponer, diseñar y validar un sistema de WPT para múltiples receptores que incluya funciones adaptativas de autosintonía mediante circuitos conmutados de alto rendimiento energético, y susceptible de ser integrado en un chip para el condicionamiento de energía en cada receptor de forma miniaturizada y desplegable de forma masiva. La tesis empieza proporcionando una revisión del estado del arte en sistemas de IoT destacando el reto tecnológico de la alimentación energética de los nodos sensores distribuidos y planteando así el foco de la tesis doctoral. El capítulo 2 sigue con una revisión crítica del statu quo de los sistemas de transferencia inalámbrica de energía RIC-WPT. Específicamente, el capítulo 2 analiza las características de diferentes estructuras circuitales de compensación en RIC-WPT seguido de una descripción crítica de las implicaciones de la desintonía en la eficiencia y la capacidad de transferencia energética del sistema. El capítulo 3 propone y explora el concepto de utilizar circuitos conmutados con función de girador como potenciales candidatos para la síntesis de propósito general de elementos reactivos variables sintonizables electrónicamente, incluyendo varias aplicaciones y casos de uso. El capítulo 4 propone dos alternativas para métodos y circuitos de control para la autosintonía de receptores de energíaPostprint (published version

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

Real-Time Power Management of A Fuel Cell/Ultracapacitor Hybrid

This thesis presents the system architecture design, system integration methodology, and real-time control of a fuel cell/ultracapacitor hybrid power system. The main objective is for the hybrid system to respond to real-world fluctuations in power without negatively impacting fuel cell life. A Proton Exchange Membrane (PEM) Fuel Cell is an electrochemical device which converts the chemical energy of pure hydrogen into electricity through a chemical reaction with oxygen. The high conversion efficiency, zero harmful emissions, high power-to-weight ratio, scalability, and low temperature operation make PEM fuel cells very attractive for stationary and portable power applications. However, fuel cells are limited in responding to fast transients in power demand, moreover power fluctuations have negative impact on fuel cell durability. This motivates the use of a supplementary energy storage device to assist the fuel cell by buffering sharp transients in power demand. The high power density, long cycle life, and efficiency of ultracapacitors make them an ideal solution for such auxiliary energy storage in a hybrid fuel cell system. The power management strategy that determines the power split between the fuel cell and ultracapacitor is key to the power following capability, long-term performance, and life-time of the fuel cell. In this thesis, a rule-based and a model predictive control strategy are designed, implemented and evaluated for power management of a fuel cell/ultracapacitor hybrid. The high-level control objectives are to respond to rapid variations in load while minimizing damaging fluctuations in fuel cell current and maintaining ultracapacitor charge (or voltage) within allowable bounds. An experimental test stand was created to evaluate the performance of the controllers. The test stand connects the fuel cell and ultracapacitor to an electronic load through two dc/dc converters, which provide two degrees of freedom, enabling independent low-level control of the DC BUS voltage and the current split between the fuel cell and ultracapacitor. Experiments show that both rule-based and model predictive power management strategies can be tuned to meet both high and low-level control objectives for a given power demand profile. However, the capability to explicitly enforce the constraints in model predictive scheme and its predictive nature in meeting power demands enables a more systematic design and results in general in smoother performance

Vibration-powered sensing system for engine condition monitoring

Condition monitoring is becoming an established technique for managing the maintenance of machinery in transport applications. Vibration energy harvesting allows wireless systems to be powered without batteries, but most traditional generators have been designed to operate at fixed frequencies. The variety of engine speeds (and hence vibration frequencies) in transport applications therefore means that these are not usable. This paper describes the application-driven specification, design and implementation of a novel vibration-powered sensing system for condition monitoring of engines. This demonstrates that, through careful holistic design of the entire system, condition monitoring systems can be powered solely from machine vibration, managing their energy resources and transmitting sensed data wirelessly

High efficiency smart voltage regulating module for green mobile computing

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.In this thesis a design for a smart high efficiency voltage regulating module capable of supplying the core of modern microprocessors incorporating dynamic voltage and frequency scaling (DVS) capability is accomplished using a RISC based microcontroller to facilitate all the functions required to control, protect, and supply the core with the required variable operating voltage as set by the DVS management system. Normally voltage regulating modules provide maximum power efficiency at designed peak load, and the efficiency falls off as the load moves towards lesser values. A mathematical model has been derived for the main converter and small signal analysis has been performed in order to determine system operation stability and select a control scheme that would improve converter operation response to transients and not requiring intense computational power to realize. A Simulation model was built using Matlab/Simulink and after experimenting with tuned PID controller and fuzzy logic controllers, a simple fuzzy logic control scheme was selected to control the pulse width modulated converter and several methods were devised to reduce the requirements for computational power making the whole system operation realizable using a low power RISC based microcontroller. The same microcontroller provides circuit adaptations operation in addition to providing protection to load in terms of over voltage and over current protection. A novel circuit technique and operation control scheme enables the designed module to selectively change some of the circuit elements in the main pulse width modulated buck converter so as to improve efficiency over a wider range of loads. In case of very light loads as the case when the device goes into standby, sleep or hibernation mode, a secondary converter starts operating and the main converter stops. The secondary converter adapts a different operation scheme using switched capacitor technique which provides high efficiency at low load currents. A fuzzy logic control scheme was chosen for the main converter for its lighter computational power requirement promoting implementation using ultra low power embedded controllers. Passive and active components were carefully selected to augment operational efficiency. These aspects enabled the designed voltage regulating module to operate with efficiency improvement in off peak load region in the range of 3% to 5%. At low loads as the case when the computer system goes to standby or sleep mode, the efficiency improvent is better than 13% which will have noticeable contribution in extending battery run time thus contributing to lowering the carbon footprint of human consumption

Microprocessor based signal processing techniques for system identification and adaptive control of DC-DC converters

Many industrial and consumer devices rely on switch mode power converters (SMPCs) to provide a reliable, well regulated, DC power supply. A poorly performing power supply can potentially compromise the characteristic behaviour, efficiency, and operating range of the device. To ensure accurate regulation of the SMPC, optimal control of the power converter output is required. However, SMPC uncertainties such as component variations and load changes will affect the performance of the controller. To compensate for these time varying problems, there is increasing interest in employing real-time adaptive control techniques in SMPC applications. It is important to note that many adaptive controllers constantly tune and adjust their parameters based upon on-line system identification. In the area of system identification and adaptive control, Recursive Least Square (RLS) method provide promising results in terms of fast convergence rate, small prediction error, accurate parametric estimation, and simple adaptive structure. Despite being popular, RLS methods often have limited application in low cost systems, such as SMPCs, due to the computationally heavy calculations demanding significant hardware resources which, in turn, may require a high specification microprocessor to successfully implement. For this reason, this thesis presents research into lower complexity adaptive signal processing and filtering techniques for on-line system identification and control of SMPCs systems. The thesis presents the novel application of a Dichotomous Coordinate Descent (DCD) algorithm for the system identification of a dc-dc buck converter. Two unique applications of the DCD algorithm are proposed; system identification and self-compensation of a dc-dc SMPC. Firstly, specific attention is given to the parameter estimation of dc-dc buck SMPC. It is computationally efficient, and uses an infinite impulse response (IIR) adaptive filter as a plant model. Importantly, the proposed method is able to identify the parameters quickly and accurately; thus offering an efficient hardware solution which is well suited to real-time applications. Secondly, new alternative adaptive schemes that do not depend entirely on estimating the plant parameters is embedded with DCD algorithm. The proposed technique is based on a simple adaptive filter method and uses a one-tap finite impulse response (FIR) prediction error filter (PEF). Experimental and simulation results clearly show the DCD technique can be optimised to achieve comparable performance to classic RLS algorithms. However, it is computationally superior; thus making it an ideal candidate technique for low cost microprocessor based applications.EThOS - Electronic Theses Online ServiceIraq Ministry of Higher EducationGBUnited Kingdo