Martin Ordonez

Transportation electrification is at the core of the possible solutions to many challenges the world is currently facing. Efficient vehicle electrification has the potential to simultaneously reduce greenhouse gasses emissions and to tackle range anxiety issues. Among different strategies for advancements in Electric Vehicle (EV) efficiency, enhancing Regenerative Braking (REGEN) capabilities is an area with opportunities. As REGEN faces different impediments, upgrades in safety, efficiency, and/or battery quality of life are usually accompanied with further strain in energy management schemes, limiting REGEN performance. Power Electronics (PE) improvements are among the options that have the potential to benefit REGEN and overall efficiency. This work proposes a method to improves REGEN without adding extra stress on the other aspects that limit its performance, by optimizing PE-stage switch selection using openly available, manufacturer-provided data. To do so, the thesis develops a flexible simulation platform capable of: 1) integrating various subsystem modeling approaches, 2) analyzing different EV configurations, architectures, and components, and 3) analyzing the dynamic behavior of the Battery Electric Vehicle (BEV) while maintaining low simulation time. It also adopts a multiobjective optimization approach that gives the user freedom to define the weight of the objectives, as well as to include new objectives at any time - as long as the initial design choices do not change. The combination of a simulation platform suited for model-based design and an optimization formulation yields a method that fits well within the Design Automation (DA) framework. Therefore, the thesis is constructed with the framework as a guideline. The simulations show that proper switch selection can improve REGEN by over 18% and EV range efficiency by over 20%. The solution is corroborated by the results of the sensitivity and the robustness analysis.

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With the increasing number of extreme weather events caused by global warming, there is an escalatingneed for reliable and sustainable alternatives for powering up critical loads. In recent years,microgrids with renewable generation have emerged as a promising technology for powering criticalloads as they can achieve high power supply reliability and low carbon footprint. To meet therequirements of critical loads and to justify their economic viability, microgrids should be carefullyplanned and optimized. Existing tools for designing microgrids focus mainly on improving thedesign’s financial aspects by optimally sizing its energy sources; although these tools provide satisfactoryresults for conventional applications, they are not suitable for critical loads as reliabilityis not included in the design process.This work presents a new Vectorial Microgrid Optimization (VMO) design method for criticalloads. The proposed VMO method improves the microgrid design by 1) incorporating the selectionof the microgrid power conversion architecture and the size of the energy sources into a unifieddesign strategy, 2) include the microgrid reliability, net present cost, and energy efficiency as theperformance metrics. Multiobjective optimization is implemented as the decision-making tool tofulfill the critical load power requirements and reach the desire balance between the performancemetrics. To highlight the benefits of the proposed method, an example of a critical load is analyzedto find its optimal microgrid design. The results indicate that the proposed approach produces amicrogrid design with a 100 times lower downtime than those obtained with existing microgriddesign tools while maintaining an energy efficiency of 93.76% and reducing the net present cost by14%.

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Small wind turbines (WTs) are robust and commercially viable distributed generation alternatives to photovoltaic (PV) generation in locations deemed unsatisfactory due to low irradiance levels. However, small WTs are susceptible to variable environmental conditions and require sophisticated maximum power point tracking (MPPT) algorithms to ensure the system operates at the maximum power point (MPP) when subjected to fluctuating wind speeds. Optimal relationship based (ORB) and hill-climbing (HC) algorithms are the traditional MPPT methods for small WTs due to their simplicity, yet these strategies suffer from several challenges: ORB algorithms rely on parameterized coefficients that change over time, whereas HC variants are susceptible to algorithm confusion and lack standardized frameworks for choosing the optimal MPPT controller update frequency and perturbation magnitude.This work introduces a novel control-oriented small WT model that facilitates an intuitive approach for analyzing the electromechanical system. This modelling technique enables the development of two incremental conductance (InCond) based MPPT strategies that address the aforementioned challenges. The first presented MPPT strategy tracks the optimal system operating point using an adapted mechanical InCond algorithm and suppresses power oscillations around the MPP. This results in: 1) elimination of algorithm confusion, 2) accurate tracking and detection of the MPP and 3) improved steady state efficiency. The algorithm design requires only electrical sensing, thereby making this method sensorless from a mechanical perspective. The second presented MPPT framework uses the control-oriented model and an online impedance measurement technique to perform a system impedance frequency response analysis. Through this analysis, a small WT equivalent circuit is derived and MPPT controller is developed using a novel system identification (SysID) algorithm to perform InCond control. This methodology offers three advantages over conventional methods: 1) accurate tracking when subjected to erratic wind speeds, 2) optimal MPPT over the system lifetime and 3) a systematic approach for choosing the MPPT update frequency, facilitated by the system impedance frequency response analysis.The presented MPPT methods are supported with detailed mathematical procedures and validated with simulation and experimental results. This thesis significantly contributes to the advancement of small WT modelling and MPPT.

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Power loss estimation is essential for the design and optimization of power converters. Traditionally, the power loss estimation is done using datasheet-level information about the switching devices. However, this information is limited to isolated operating points, compromising the accuracy of the estimation. In addition, the representation of PCB effects and gate driver, which cannot be considered by using datasheet parameters, increase the complexity of the tasks by adding more unknown magnitudes and more complex equations without guaranteeing their correct estimation.In this work, a novel power loss estimation method, which can be applied to any topology, is presented. This proposed method utilizes Design of Experiments (DoE) and Response Surface Methodology (RSM) to model the different types of losses in all the elements in a power converter such as power switches, diodes, and inductors. With RSM, simple equations explain the different types of losses as a function of variables that directly affect them allowing the losses estimation under any operating condition accurately. These models are extensively validated to show the advantage of using the proposed method and significant improvement with respect to datasheet calculations is obtained. For complex topologies such as Power Factor Corrector (PFC), accurate power loss estimation is not only necessary but also a challenge. To show the capabilities of the proposed model, it is applied to Universal PFC, which is a complicated converter in terms of loss calculation and analysis. Using the proposed models, the inductor is designed optimally and the optimal switching frequency is selected to minimize the losses in the different input voltage levels. Experimental validation of the proposed method, prediction, and design impact is presented; the proposed method yields a power loss reduction up to 25%, having the greatest improvement at an input voltage of 110 V, and an output power higher than 500 W.

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Remote off-grid communities rely on diesel for generating electricity. In addition to the greenhouse gas emissions, diesel generators require a constant fuel supply leading to transportation and logistics issues over the lifespan of the project. On the other hand, PV-BESS microgrids offer a suitable alternative to provide clean and sustainable energy to the communities due to their decreasing cost, small size, versatility for interconnection and low maintenance. Conventional methods determine the required PV-BESS installed capacity utilizing simple models to assess the financial aspects of the systems. However, they do not provide information about the implementation, thus requiring an additional stage to select available commercial devices and the correct series-parallel interconnection of the PV, BEES and power converters. Consequently, the overall cost of the system increases, while the performance drifts away from the predicted behaviour.In this work, a novel sizing methodology is proposed, reducing the cost of the system by 23%, the installed PV and BESS by 9% and the necessary power converters by 58%. The proposed approach facilitates a comprehensive study of the scenario, incorporating advanced models in the optimization problem, maintaining the financial goals, and adding new goals to a multi-objective optimal energy management strategy (EMS). The proposed optimal solution provides the number of series-parallel interconnected PV and BESS, and the required number of power converters, which eliminates the need for an additional implementation stage. The developed tool provides a comprehensive understanding of standalone microgrids, closing the gap between the optimal solution and industrial implementation.

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Power converters are found nearly everywhere electric power is used and are ubiquitous in renewable energy generation and electric vehicles. All power converters suffer from losses, Modern power converters have very high efficiency, often reaching peak efficiency > 95%. However, the losses in these systems are still significant and must be considered for thermal and financial purposes. To enable maximum loss reduction, accurate estimation of the losses at the design stage is mandatory.Gallium Nitride (GaN) power switches are an emerging technology due to their high efficiency operation and smaller size compared to traditional Silicon devices. To date, simplistic power loss models have been employed for loss predication and thermal management design with Gallium Nitride (GaN). However, these simplistic models do not provide accurate loss prediction, resulting in over-design of the thermal management systems. This work proposes a comprehensive method to predict losses in GaN devices using high-accuracy thermal measurement. The proposed model is validated experimentally and provides a four-fold increase in loss predication accuracy compared to traditional methods.Having established accurate converter-level loss prediction, a higher level of abstraction is then considered. Existing system-level analysis focuses on distribution losses and oversimplifies converter losses by assuming fixed efficiency. In reality, converter losses are highly variable under different operating conditions. In this work, the Rapid Loss Estimation equation (RLEE) is proposed to provide computationally simple loss prediction under all operating conditions. The RLEE extracts detailed loss behavior from multi-domain simulation into a computationally simple parametric equation. Using the RLEE high accuracy and high speed loss estimation is obtained, as demonstrated in a DC microgrid with three different converters.Ultimately, the tools developed in this work improve loss estimation in power converters from the component level up to the system level. The proposed techniques, while explained through specific examples, are widely applicable and can be readily implemented to other devices, topologies and systems. Improved loss estimation is valuable at all levels, from designing thermal management systems for individual devices in a converter to optimizing the financial outcomes of a complex grid with multiple power converters.

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LLC resonant converters have become a mainstream topology in DC/DC power conversion applications such as electric vehicle charging, renewable energy generation and low power energy conversion. This converter presents advantages such as the soft-switching of active devices, which reduces power losses in the energy conversion process, allowing for a more efficient operation when compared to hard-switched topologies.Losses in the MOSFETs of the inverting and rectifying stages of this converter should be accurately determined so to allow for proper heat management design and thermal dissipation. However, determination of losses through simulation can be challenging due to the significant difference between time constants of electrical and thermal phenomena. Moreover, the information presented by the datasheet of power electronic devices is often limited to select operating points, which may compromise the accuracy of power loss estimation.In order to overcome the limitations imposed by the datasheet, a detailed characterization of the main loss mechanisms in the operation of LLC MOSFETs is presented. To avoid the time-consuming and computationally-intensive process of simulation, steady-state time-domain expressions for the converter are developed, based on the electrical behavior of the topology. These equations, based on the Time Interval Analysis, are able to predict key electrical and thermal behaviours based on circuit design considerations and operating conditions, being easily implementable in software such as MATLAB or MS Excel.As verified by simulation and experimental results, estimation of losses using the proposed method is considerably more precise than using the well-established yet oversimplified First-Harmonic Approximation (FHA). In the inverting stage, the observed error in loss determination is reduced from an average of 19%, using FHA, to 2.8% using the proposed method. When it comes to the rectification portion of the circuit, the reduction in error observed is from 12% to 2%. Such improvement in power loss estimation before the converter is built is fundamental for the design of an agile and cost-effective thermal management approach which guarantees the integrity and reliability of the power electronics device.

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For the last years, LLC resonant converters have gained wide popularity in a large number of domestic and industrial applications due to their high-efficiency and power density. Common applications of this converter are battery chargers and high efficiency power supplies, which require tight output voltage regulation. In traditional PWM converters, closed-loop controllers based on small-signal models are typically implemented to achieve zero steady-state error and minimize the effects of disturbances at the output. However, traditional averaging techniques employed in PWM converters cannot be applied to LLC's and highly complex mathematical models are required. As a consequence, designing linear controllers for this type of converter is usually based on empirical methods, which require high-cost equipment and do not provide any physical insight into the system. The implementation of current-mode controllers has been vastly developed for PWM converters. Employing an inner current loop and outer voltage loop has shown numerous advantages, such as, tight current regulation, over-current protection, and ample bandwidth. However, this control architecture is not commonly implemented in LLC resonant converters, and conventional single voltage loop controllers are employed.This work proposes a simple and straightforward methodology for designing linear controllers for LLC resonant converters. A simplified second order equivalent circuit is developed and employed to derive all the relevant equations for designing proper compensators. A dual-loop control scheme including an inner current loop and outer voltage loop is proposed. The implementation of the dual-loop configuration provides improved closed-loop performance for the entire operational range. The theoretical findings are supported by detailed mathematical procedures and validated by simulation and experimental results.

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Direct-current (dc) microgrids interconnect dc loads, distributed renewable energy sources, and energy storage elements within networks that can operate independently from the main grid. Due to their high efficiency, increasing technological viability and resilience to natural disturbances, they are set to gain popularity. When load-side converters in a microgrid tightly regulate their output voltages, they are seen as constant power loads (CPLs) from the standpoint of the source-end converters. CPLs can cause instability within the network, including large voltage drops or oscillations in the dc bus during load transients, which can lead to dc bus voltage collapse.Traditionally, the stability of CPL-loaded dc microgrids relies on the addition of passive elements, usually leading to dc-bus capacitance increase. In this scenarios, source-end converters controllers are usually linear dual proportional-integral (PI) compensators. The limited dynamic response of these controllers exacerbates the CPL behavior, which leads to the use of larger passive elements.Recent contributions focus on implementing control modifications on the source-end converter in order to improve the system performance under CPLs. Particularly, the use of state-plane based controllers has been studied for the case of a single dc-dc power converter loaded by a CPL, showing fast and robust transient performance. However, the microgrid problem, where these faster converters interface with others of a slower response has not been studied thoroughly. This work proposes the use of a fast state-plane controller to replace one of the system’s source-end converters controllers in order to improve three aspects of the microgrid operation: resiliency under CPL's steps, load transient voltage regulation, and voltage transient recovery time.Since the converter is operating within a microgrid, the controller incorporates a traditional droop rule to enable current sharing with the rest of the converters of the network. The small-signal stability improvement of the whole system obtained by the addition of a single faster controller is analyzed for a linear model, and a parametric analysis demonstrates the improvements in a detailed model.Simulations and experimental results of a microgrid with three converters feeding a CPL prove the effectiveness of the technique for large-signal transients.

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Recent developments in energy systems, including the rapid adoption of renewable energy sources and expansion of microgrids have been introducing new challenges and opportunities for the power electronics industry. Of particular interest to this thesis is the increase of grid-connected DC systems. As a means to reduce cost of copper infrastructure these systems favour the utilization of higher DC link voltages. To accommodate higher voltages, a variety of multilevel converters have been proposed, which generally can be built without specialized components, present lower dV/dt losses and synthesize AC signals with better power quality. Irrespective of the application, the power electronics industry has traditionally relied on generic rules and practices to quickly design converters. Rarely does the development cycle allow for thorough investigation of the converter design, which could enhance performance and give an edge over competitors. This thesis proposes using optimization techniques to aid power electronics engineers in the design of multilevel converters. The Neutral Point Clamped (NPC) with its variant the Active NPC (ANPC) were selected for the exercise presented. Chapter 2 of this thesis explains the operation and modulation of the topologies. From the analysis, the conduction and switching losses of each device can be predicted. A description of three semiconductor technologies is presented with their characteristics and source of losses. Lastly an equation to size the filter inductor is introduced. All this information is packaged into a model used in the optimization. Chapter 3 introduces the optimization strategy. Given the complex nature of power electronics, four objective functions were adopted: efficiency, loss distribution, inductance and cost. These functions were combined through a weight system which allows priorities to be asserted. Next, design variables are introduced along with their respective impacts on the objective functions. Experiments performed with a hardware platform showed the model closely predicts the impact of the design variables on the objective functions. Confident in the model, the optimization was carried out for various scenarios. Single objective optimization led to converters that excel in one aspect but were often not practical. When optimizing with multiple objectives a good compromise was reached with a practical converter.

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Digital control has become ubiquitous in the field of power electronics due to the ease of implementation, reusability, and flexibility. Practical engineers have been hesitant to use digital control rather than the more traditional analog control methods due to the unfamiliar theory, relatively complicated implementation and various challenges associated with digital quantization. This thesis presents discrete signal processing theory to solve issues in digitally controlled power converters including reference generation and filtering.First, this thesis presents advancements made in the field of digital control of dc-ac and ac-dc power converters. First, a multi-carrier PWM strategy is proposed for the accurate and computationally inexpensive generation of sinusoidal signals. This method aims to reduce the cost of implementing a sine-wave generator by reducing both memory and computational requirements. The technique, backed by theoretical and experimental evidence, is simple to implement, and does not rely on any specialized hardware. The method was simulated and experimentally implemented in a voltage-controlled PWM inverter and can be extended to any application involving the digital generation of periodic signals.The second advancement described in this thesis is the use of simple digital filters to improve the response time of single-phase active rectifiers. Under traditional analog control strategies, the bandwidth of an active rectifier is unduly restricted in order to reduce any unwanted harmonic distortion. This work investigates digital filters as a proposed means to improve the bandwidth, and thereby create a faster, more efficient ac-dc power converter. Finally, a moving average filter is proposed, due to its simple implementation and minor computational burden, as an efficient means to expand the bandwidth. Since moving average filters are well known and widely understood in industry, this proposed filter is an attractive solution for practicing engineers.The theory developed in this thesis is verified through simulations and experiments.

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The development of sustainable transport systems has experienced great improvements inthe last 15 years. As a result, electric vehicles, namely hybrid electric vehicles (HEVs) andall-electric or battery electric vehicles (BEVs), are slowly starting to coexist with regularinternal combustion vehicles around the world. The complex powering structure of automotive electric systems can be described as a distributed multiconverter architecture. In pursuit of performance, constant-power behavior of tightly regulated downstream converters has raised as an important challenge in terms of system stability and controllability. The first part of this work presents the theory and experimental validation of the unstable behavior introduced by constant-power loads (CPLs) in power converters, more precisely in a Buck+Boost cascade converter as the battery charge/discharge unit. The second part of this work presents the derivation of the Circular Switching Surfaces (CSS) and the implementation of the CSS-based control technique for CPL stabilization. The analysis shows that the constant-power load trajectories and the proposed CSS present a wide, stable operating area and near-optimal transient response. Furthermore, impedance analysis of the converter in close-loop control shows advantageous reduced output source impedance. This extremely high dynamic capability prevents the use of bulky DC capacitors for bus stabilization, and allows the implementation of metal-film capacitors, which have reliability advantages over commonly employed electrolytic capacitors, as well as reduced ESR to improve system efficiency. Beyond the improved stabilization properties of the proposed CCS-based controller, a comparison with traditional compensated linear controller and nonlinear SMC highlights significant improvements in terms of dynamic response for sudden CPL changes. Simulation and experimental results are provided to validate the work. The last part of this thesis work presents the design, construction, and testing of a high-power 3-phase converter. This platform is intended for electric motor driving and is able to manage 20kW of power flow and above, making it suitable for high power traction system development. The platform features an Intelligent Power Module (IPM) to provide with flexibility allowing for changing the power module according to the requirements of the development. Testing of the platform was done in a 0.5HP AC induction motor drive controlled with Voltz-per-Hertz control technique. The integration of the BCDU and the high-power 3-phase motor drive platform conform a high-power bidirectional motor drive platform for the development and testing of control techniques for energy management in EV.

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Maximum Power Point Tracking (MPPT) strategies in Photovoltaic (PV) systems ensure efficient utilization of PV arrays. Among different strategies, the Perturb and Observe (P&O) algorithm has gained wide popularity due to its intuitive nature and simple implementation. However, such simplicity in P&O introduces two inherent issues, an artificial perturbation that creates losses in steady-state operation and a limited ability to track transients in changing environmental conditions. This work develops and discusses in detail an MPPT algorithm with zero oscillation and slope tracking to address those technical challenges. The strategy combines three techniques to improve steady-state behavior and transient operation: 1) idle operation on the Maximum Power Point (MPP), 2) identification of the irradiance change through a natural perturbation and 3) a simple multi-level adaptive tracking step. Two key elements, which form the foundation of the proposed solution, are investigated: the suppression of the artificial perturbation at the MPP and the indirect identification of irradiance change through a current-monitoring algorithm which acts as a natural perturbation. The Zero-oscillation, Adaptive step Perturb and Observe (ZA-P&O) MPPT strategy builds on these mechanisms to identify relevant information and produce efficiency gains. As a result, the combined techniques achieve superior overall performance while maintaining simplicity of implementation. Simulations and experimental results are provided to validate the proposed strategy and illustrate its behavior in steady state and transient operation.

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Small-scale Wind Energy Conversion Systems (WECS) are becoming an attractive option for distributed and renewable energy generation. In order to be affordable, WECS must have low capital and maintenance costs. This leads to the increasing penetration of Permanent Magnet Synchronous Generators (PMSG) operating at variable frequency with connections to the power grid through a rectifier, and grid-tie inverter. Because PMSGs lack brushes and can be directly coupled to wind turbines, the capital and maintenance costs are greatly reduced. A direct connection to the grid further reduces system costs by removing the requirement of large battery banks.The loading produced by grid-tie inverters on the DC bus is different than more typical constant-current or constant-power loads. They are characterized by large input ripple currents at twice the inverter's grid frequency. These ripple currents are reflected through the DC bus into the PMSG causing increased heating in the stator, and ripple torques which lead to premature bearing failure and increased maintenance costs. To mitigate this problem, manufacturers typically add large amounts of capacitance on the DC bus to partially absorb these ripples at the expense of system size, cost, and reliability.In this work, the effects of the grid-tie inverter load are explored using system behavioural models which provide insight into the low frequency behaviour of the PMSG, rectifier, DC bus, and inverter. The swinging bus concept is presented and analysed in the time and frequency domains. A control philosophy is developed which allows the DC bus to swing, thus removing the effects of the grid-tie inverter on the PMSG while keeping the DC bus capacitor small. A solution consisting of a Moving Average Filter (MAF) is presented as an integral part of the control strategy.Full simulations of a complete system are developed and investigated to verify the ripple torque reduction technique. Finally, a prototype is developed and experimental results are presented for a 2.5kW PMSG turbine generator. The simulation and experimental results are compared to a traditional controller showing tangible improvements in ripple current and torque in the PMSG, while improving the dynamic response of the system.

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Controllers are an essential component in power conversion systems that have a significant impact on characteristic features such as performance, efficiency, size, and cost, among many others. During the last four decades, countless efforts have been made to find better controllers for power electronics systems in order to improve the converters steady state and dynamic behaviour, increase power densities and reduce losses in the system.Small-signal based linear controllers have been the preferred alternative during decades. This technique features fixed switching frequency and low computation/sensing requirements, while the dynamic response can be improved to only a limited extent and the global stability cannot be ensured. On the other hand, excellent dynamic performances and global stability are achieved by boundary controllers, in which the switching frequency is variable and faster sensors are required.The first part of this work presents a practical tool which allows to objectively quantize improvements made by the controllers to the performance of power converters. The theoretical optimal dynamic behaviour of buck converters is determined, analyzed, and characterized using closed-form mathematical expressions, setting a strong benchmark point for the performance evaluation.Taking the physical limits of dynamic performance into account, and merging the advantages of linear and boundary techniques, a novel control scheme is developed for buck converters. The proposed controller is based on a large-signal model introduced here: the Average Natural Trajectories (ANTs). Enhanced dynamic performance and global stability are achieved while low sensing and computational requirements are maintained, which makes the technique very appealing for use in high-volume production applications.Due to the outstanding results in the basic buck converter, and in order to illustrate the application of the ideas introduced in this work for different topologies, the ANTs and the centric-based controller are developed for boost converters. The obtained results confirm the enhanced dynamic response and fixed frequency operation as natural advantages of the proposed control scheme.The theoretical findings are supported by detailed mathematical procedures and validated by experimental results, which highlight the practical usefulness of the concepts introduced in this work.

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