During the past two decades desperate need for energy-efficient vehicles which has less emission have led to a great attention to and development of electrified vehicles like pure electric, Hybrid Electric Vehicle (HEV) and Plug-in Hybrid Electric Vehicles (PHEVs). Resultantly, a great amount of research efforts have been dedicated to development of control strategies for this type of vehicles including PHEV which is the case study in this thesis. This thesis presents a real-time control scheme to improve the fuel economy of plug-in hybrid electric vehicles (PHEVs) by accounting for the instantaneous states of the system as well as the future trip information. To design the mentioned parametric real-time power management policies, we use dynamic programming (DP). First, a representative power-split PHEV powertrain model is introduced, followed by a DP formulation for obtaining the optimal powertrain trajectories from the energy cost point of view for a given drive cycle. The state and decision variables in the DP algorithm are selected in a way that provides the best tradeoff between the computational time and accuracy which is the first contribution of this research effort. These trajectories are then used to train a set of linear maps for the powertrain control variables such as the engine and electric motor/generator torque inputs, through a least-squares optimization process. The DP results indicate that the trip length (distance from the start of the trip to the next charging station) is a key factor in determining the optimal control decisions. To account for this factor, an additional input variable pertaining to the remaining length of the trip is considered during the training of the real-time control policies. The proposed controller receives the demanded propulsion force and the powertrain variables as inputs, and generates the torque commands for the engine and the electric drivetrain system. Numerical simulations indicate that the proposed control policy is able to approximate the optimal trajectories with a good accuracy using the real-time information for the same drive cycles as trained and drive cycle out of training set. To maintain the battery state-of-charge (SOC) above a certain lower bound, two logics have been introduced a switching logic is implemented to transition to a conservative control policy when the battery SOC drops below a certain threshold. Simulation results indicate the effectiveness of the proposed approach in achieving near-optimal performance while maintaining the SOC within the desired range. / MS

細數過去數十年，台灣類比IC設計產業發展從無到有，從客戶不相信台灣類比IC設計公司的能力，到現在彼此成為合作夥伴，從外商完全看不起台商，到現在大家同場競技，從沒有一家類比IC設計公司上市、櫃掛牌，到現在已有近十家類比IC設計公司掛牌，台灣類比IC設計產業實在值得更多的喝采與投資人的注意。 目前為止，台灣共有二十幾家類比IC設計公司，本研究主要以民國九十四年十二月底以前上市、櫃之茂達、立錡、沛亨、安茂、富鼎先進、致新、崇貿、點晶、圓創等九家類比IC設計公司為樣本 依其八十九年至九十三年之財務報表做為預估個案公司未來成長率及獲利率的依據，利用現金流量折現法採銷售導向及盈餘導向等兩種模式，依最樂觀、最可能發生及最悲觀等三種情境，估算其實質價格區間，並與各股目前之實際股價相比較，以推論目前股價的合理性以及目前股價可能隱含的銷售成長率及盈餘成長率，另以敏感度分析將各個評價因子繪製成龍捲風圖，來觀察個別關鍵評價因子對股價的影響程度。 此外，本研究依Aaker的分析架構，針對此依產業進行外在與內在分析，包括整個產業的環境分析、產業分析、競爭對手分析、顧客分析與關鍵成功因素(SWOT)分析，以期本研究能在財務分析之外，提供投資人對類比IC設計產業ㄧ全面通盤性之分析。 最後，根據本研究之實證結果，發現過去五年個股與大盤股價作分析，ϐ值均偏高，其可能原因: 1. 類比IC設計產業(相對於數位IC設計產業)，為一新興產業，市場給予之本益比較高， 2. 進口替代效應之潛在業績成長題材，持續發酵。

Submitted by Johnny Rodrigues (johnnyrodrigues@ufcg.edu.br) on 2018-04-04T21:30:07Z No. of bitstreams: 1 DIÓGENES GALDINO GONDIM - DISSERTAÇÃO PPGCC 2014..pdf: 1586466 bytes, checksum: 3b6e47836d1098cd946a0d8486669b23 (MD5) / Made available in DSpace on 2018-04-04T21:30:07Z (GMT). No. of bitstreams: 1 DIÓGENES GALDINO GONDIM - DISSERTAÇÃO PPGCC 2014..pdf: 1586466 bytes, checksum: 3b6e47836d1098cd946a0d8486669b23 (MD5) Previous issue date: 2014-08-04 / A maioria dos sistemas operacionais oferecem suas próprias estratégias de gerenciamento de energia, mas é muito difícil modificar ou ampliar as políticas de energia sem acesso ao código fonte. Várias arquiteturas em gerenciamento dinâmico de energia já foram propostas na literatura, mas elas não são integradas com o sistema operacional subjacente. Neste trabalho, é proposto um arcabouço de software para o desenvolvimento de aplicações gerenciadoras de energia ao nível de usuário, com a flexibilidade arquitetural de se adaptar a diferentes políticas e de se integrar às políticas de gerenciamento do sistema operacional. Para validar o arcabouço, é descrito um estudo de caso mostrando sua viabilidade, demonstrando que a aplicação resultante oferece redução no consumo de energia. / Most operating systems implement their own power management techniques, but it is hard to modify or hack their power policies without the source code. Many dynamic power management architectures have been proposed in the literature, but they are not integrated with the underlying OS power manager. In this work, we proposed a software framework for user-level power management, with a flexible architecture to be adapted to different policies and integrated with OS power managers and validated its feasibility with a case study.

Power management is an important part when developing a smartwatch to meet user expectations of battery lifetime and functionality. To develop a good power management structure, measurements of the device is crucial to understand the behavior and power consumption of hardware and software. In this thesis, measurements have been made to hardware connected to the PineTime smartwatch to get knowledge of its behavior and power consumption. A structure for hardware and software was developed to enable the possibility to debug, flash, and perform measurements. The purpose of the measurements is to find possible areas of improvement that have the potential to lower the overall power consumption of the device. From the measurements, the st7789V display driver and the hardware design was detected to have a high power consumption. Bluetooth was also found to have an odd behavior in terms of power consumption. From these findings, suggestions on how to lower the power consumption are presented.

Sweden’s energy system is facing major changes in the near future in order to reducecarbon emissions and to switch to sustainable energy sources. PV systems havebecome a sensible alternative for homeowners that want to be a part of this changeand at the same time reduce the cost of their electricity bill. To further improve theutilization of their PV system and to handle the intermittent nature of solar power,battery storages have become an interesting system complement. This thesisinvestigates how batteries can provide smart services; load shift and peak price energyutilization to a household. This is done by developing an optimized battery algorithmmodel that can provide these smart services which is compared to a simple batteryalgorithm. The results show that the developed battery optimization model works asintended. It performs both load shift and peak price energy utilization. The economicanalysis shows that the most profitable PV system and battery configuration is a 20kW PV system with a 5 kWh battery. The system has an internal rate of return, IRR,of 2.3% which does not reach Vattenfall’s weighted average cost of capital, WACC, at7%. The results also show that the battery cost is an important factors for a system'sprofitability. A larger battery system is more expensive and the increased yield doesnot cover the increased cost. Further research is needed to implement the optimizedbattery as a functional application since the model has access to a perfect forecast andthus a method for forecasting PV production and load profile of the household arecrucial to get similar results.

Energy harvesting is becoming increasingly important in low-power applications where energy from the environment is used to power the system alone, or to supplement a battery. For example, pulse oximeter sensors inside helmets of road racing cyclists are powered by the sun. These sensors have become smaller and more practical without the limitation of a finite energy supply. Harvested energy from an energy transducer (solar, piezoelectric, etc.) must be maximized to ensure these devices can survive periods where environmental energy is scarce. The conversion process from the transducer to usable power for the device is not perfectly efficient. Specifically, the output voltage of a solar cell is a function of the light intensity, and by extension the load it powers. A small perturbation of the light source quickly diminishes the available power. The wasted power reduces the energy available for the application, and can be improved using an approach called maximum power point tracking (MPPT). This technique maximizes harvesting efficiency by dynamically impedance matching the transducer to its load. This report introduces the Maximum Efficient Solar Harvester (MESH), an MPPT algorithm tuned for a specific Wireless Sensor Network (WSN) application. MESH specifically controls the operation of the DC-DC converter in a solar power management unit (PMU). The control is done by monitoring the available light and feeding that information to choose the optimal operating point DC-DC converter. This operating point has a direct dependency on the overall efficiency of the system. For MESH to be practical, the cost and power overhead of adding this functionality must be assessed. Empirical results indicate that MESH improves the maximum efficiency of the popular Texas Instruments (TI) RF2500-SEH WSN platform by an average of 20%, which far exceeds the power overhead it incurs. The cost is also found to be minimal, as WSN platforms already include a large portion of the hardware required to implement MESH. The report was done in collaboration with Stephen Kobdish. It covers the software implementation and MESH architecture definition; Kobdish's companion report focuses on hardware components and the bench automation environment. / text

The thesis examines the design and implementation of a supervisory controller for the energy management of an AC stand-alone microgrid. The microgrid under study consists of a photovoltaic (PV), battery energy storage system (BESS) and auxiliary (micro gas turbine) units connected to a common AC bus and supplies a local load. The BESS unit has to maintain the AC bus voltage and frequency and needs to balance the difference between the intermittent PV power and that consumed by the load. However, the BESS has limited energy capacity and power rating and therefore it is important to implement a supervisory controller that can curtail the PV power to prevent the battery from being overcharged and also to operate the auxiliary unit to prevent the battery from being over discharged. A Fuzzy Logic Controller (FLC) that can be implemented inside the BESS unit is proposed. It monitors the battery power and State of Charge (SOC) and varies the bus frequency accordingly. The variation in the bus frequency serves as a communication means to the PV and auxiliary units. If the frequency is increased above the nominal value, the PV unit starts to curtail its power and if the frequency is decreased, the auxiliary unit starts to generate power. Power curtailment and supplement are proportional to the frequency variation. In order to avoid any need for communication links between the units, the DC/AC inverters of all the units adopt the well-known wireless droop technique. The droop control of the auxiliary unit is implemented in such a way that the unit is floating on the bus and thus it generates power only if the bus frequency is decreased below its nominal value. The main merits of the proposed controller are simplicity and easiness of implementation inside the BESS unit. The effectiveness of the controller in protecting the battery from over-charging/over-discharging has been verified by simulations including a real-time simulation and experimentally. Furthermore, the thesis investigates the effect of sudden shading of a PV and concentrated PV (CPV) on the bus frequency of an AC stand-alone microgrid. It is known that the CPV power can drop drastically, compared to traditional PV, when it is exposed to shading. A simulation model of the CPV in a microgrid has been built and the results are compared to those of the traditional PV. It is found that shading of the CPV has much more stronger effect on the bus frequency.

A presente tese busca desenvolver uma metodologia para o gerenciamento e controle de uma geração distribuída que utiliza como fonte principal células a combustível do tipo PEM (Proton Exchange Membrane). A finalidade do trabalho consiste em analisar, controlar e gerenciar a operação da célula a combustível (CaC) nas operações ilhada e conectada em relação à rede de distribuição. Nos primeiros capítulos do texto é elaborada uma revisão acerca do princípio de funcionamento e do modelo da CaC. Após este estágio inicial, são analisadas e modeladas as estruturas dos estágios CC e CA que compõem a geração distribuída. Para o modo conectado é desenvolvida uma estratégia para o controle da tensão do link CC que, a partir da regulação da corrente do estágio CA, permite o gerenciamento da potência fornecida pela CaC. Sequencialmente ao texto e com a adição do estágio de armazenamento de energia, é apresentada uma proposta que vincula a dinâmica da CaC com a estrutura de gerenciamento do estágio CC e CA. Esse fato garante que a alteração do ponto de operação da CaC seja descrito conforme uma dinâmica predeterminada, garantindo assim que transitórios não sejam absorvidos pela CaC. Como parte final da tese, é desenvolvida uma estratégia para a inicialização da CaC, a qual associa o próprio comportamento da célula e o estágio de armazenamento de energia. Os resultados apresentados ao longo do texto mostram que as estruturas propostas tornam a CaC menos sensível a transitórios de carga, além de serem capazes de deslocar (gerenciar) o ponto de operação da célula. Ao final de cada capítulo, são apresentados resultados experimentais e de simulações que auxiliam o entendimento e suportam as propostas do trabalho. / This thesis proposes a methodology for management and control of distributed generation with a Proton Exchange Membrane Fuel Cell (PEMFC) as the main source. Additionally, the analysis of performance is used when the PEM fuel cell operates in two different operation modes, i.e. in grid-connected and stand-alone modes. In the first chapters, a review of main features and a mathematical model of fuel cells are presented. Sequentially, the theoretical models of the DC- and AC-power converters are analyzed. For grid-connected operation mode, a strategy based on the DC-link voltage control is proposed via current regulation of the AC stage affording thus the management of the power produced by the fuel cell. Additionally, with the use of the storage devices, a proposal that associates the dynamics of the PEM fuel cell with the DC and AC stages is shown. This fact ensures that the movement of the fuel cell operating point is described within a predetermined dynamic, ensuring that transients are not absorbed by the fuel cell. Finally, a strategy for the startup of fuel cell in association with the energy storage stage is developed. The results show that the proposed structures makes the cell less sensitive to the load transient, in order to move (manage) the fuel cell operating point. At the end of each chapter, experimental and simulation results are presented to support the proposed approach.

L'avènement de l'Internet des Objets a permis de déployer de nombreux réseaux de capteurs sans-fil. Ces réseaux sont utilisés dans des domaines aussi variés que l'agriculture, l'industrie ou la ville intelligente, où ils permettent d'optimiser finement les processus. Ces appareils sont le plus souvent alimentés par des piles ou batteries, ce qui limite leur autonomie. De plus, il n'est pas toujours possible ou financièrement viable de changer ou recharger les batteries. Une solution possible est d'alimenter ces capteurs en récupérant l'énergie présente dans l'environnement alentour. Ces sources d'énergie sont cependant peu fiables, et le capteur doit être capable d'éviter de vider complètement sa réserve d'énergie. Afin de moduler sa consommation d'énergie, le capteur peut adapter sa qualité de service à ses capacités énergétiques. L'appareil peut ainsi fonctionner en continu sans interruption de service. Cette thèse présente les méthodes utilisées pour la conception d'un capteur entièrement autonome alimenté par récupération d'énergie ambiante, communiquant sur un réseau longue portée LoRa. Afin d'assurer l'alimentation électrique, une carte permettant de récupérer de l'énergie depuis plusieurs sources d'énergie simultanément a été conçue. Un module logiciel de gestion d'énergie a ensuite été développé afin de calculer un budget énergétique que le capteur peut dépenser, et choisir la meilleure manière de dépenser ce budget pour exécuter une ou plusieurs tâches. Ce travail a ainsi permis le développement d'un prototype de produit industriel entièrement autonome en énergie. / The advent of the Internet of Things has enabled the roll-out of a multitude of Wireless Sensor Networks. These networks can be used in various fields, such as agriculture, industry or the smart city, where they facilitate fine optimization of processes. These devices are often powered by primary or rechargeable batteries, which limits their battery life. Moreover, it is sometimes not possible or financially viable to change and/or recharge these batteries. A possible solution is to harvest energy from the environment to power these sensors. But these energy sources are unreliable, and the sensor must be able to prevent the complete depletion of its energy storage. In order to adapt its energy consumption, the node can match its quality of service to its energetical capabilities. Thus, the device can continuously operate without any service interruption. This thesis presents the methods used for the conception of a completely autonomous sensor, powered by energy harvesting and communicating through a long range LoRa network. In order to ensure its power supply, a board has been designed to harvest energy from multiple energy sources simultaneously. A power management software module has then been developed to calculate an energy budget the sensor can use, and to choose the best way to spend this budget over one or multiple tasks. This work has enabled the development of an energy autonomous industrial sensor prototype.

As technology scales down and CMOS circuits are powered by lower supply voltages, standby leakage current becomes significant. A behavioral level framework for the synthesis of data-paths with low leakage power is presented. There has been minimal work done on the behavioral synthesis of low leakage datapaths. We present a fast architectural simulator for leakage (FASL) to estimate the leakage power dissipated by a system described hierarchically in VHDL. FASL uses a leakage power model embedded into VHDL leafcells. These leafcells are characterized for leakage accurately using HSPICE. We present results which show that FASL measures leakage power significantly faster than HSPICE, with less than a 5% loss in accuracy, compared to HSPICE. We present a comprehensive framework for synthesizing low leakage power data-paths using a parameterized Multi-threshold CMOS (MTCMOS) component library. The component library has been characterized for leakage power and delay as a function of sleep transistor width. We propose four techniques for minimization of leakage power during behavioral synthesis: (1) leakage power management using MTCMOS modules; (2) an allocation and binding algorithm for low leakage based on clique partitioning; (3) selective binding to MTCMOS technology, allowing the designer to have control over the area overhead; and (4) a performance recovery technique based on multi-cycling and introduction of slack, to alleviate the loss in performance attributed to the introduction of MTCMOS modules in the data-path. Finally, we propose two iterative search based techniques, based on Tabu search, to synthesize low leakage data-paths. The first technique searches for low leakage scheduling options. The second technique simultaneously searches for a low leakage schedule and binding. It is shown that the latter technique of unified search is more robust. The quality of results generated bytabu-based technique are superior to those generated by simulated annealing (SA) search technique.