Juri Jatskevich


Relevant Degree Programs


Graduate Student Supervision

Doctoral Student Supervision (Jan 2008 - Nov 2019)
Efficient modelling of special purpose multi-phase electrical machines for transient simulation programs (2020)

No abstract available.

Average-value modeling of high power ac-ac and ac-dc converters for power systems transient studies (2019)

The ac–ac and ac–dc line-commutated converters are widely used in various high-power applications due to their high reliability and efficiency and low cost. Efficient and accurate computer simulations are necessary to analyze various aspects of power systems in both normal and unbalanced/faulty conditions where using detailed switching models of converters is computationally expensive due to switching. As an alternative, for system-level studies, the so-called parametric average-value modeling (PAVM) technique has been developed to achieve computationally efficient models of power-electronic converters that neglect the switching and capture the averaged dynamics of converters only. In this thesis, the PAVM methodology is extended to three-phase ac–ac class of converter systems. Furthermore, a generalized PAVM (GPAVM) is proposed for ac–dc converters that includes the ac harmonics in thyristor-controlled rectifier models considering their dependency on the line frequency. It is shown that any existing PAVM can be realized as a subset of the proposed GPAVM. Then, the PAVM methodology is extended to rectifiers with internal faults. The new formulation considers the asymmetrical operation of rectifiers by including the ac-side harmonics in both positive and negative sequences as well as dc components that may be present on ac variables. Finally, a new parametric methodology is presented that can provide continuous–detailed models of rectifiers which can also reconstruct the switching details similar to discrete–switching–detailed models. However, the proposed parametric–detailed model is continuous and can be simulated with much larger time-steps. Moreover, the new model can be easily converted to a PAVM by disabling the reconstruction of dc details/switching. All the models in this dissertation are verified by extensive experimental measurements and computer studies using detailed models of the subject converters. It is demonstrated that all the proposed new models have excellent accuracy over a wide range of operating conditions while being computationally much faster than the corresponding detailed switching models. It is envisioned that the models and methodologies proposed in this dissertation will receive wide acceptance in the research community and simulation software industry, and will enable the next generation of power systems simulation tools.

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Numerically efficient modelling and simulation of integrated ac-dc power systems using dynamic phasor type solutions (2018)

Modern power systems, from continent-spanning networks down to isolated microgrids, are experiencing unprecedented technological changes with broader use of direct current (dc) in addition to traditional alternating current (ac). Such integrated ac-dc power systems present notable challenges in all aspects of design, analysis, control, and operation, where extensive computer simulations play the essential and enabling role. Due to the use of diverse types of signal representation and component formulation, state-of-the-art power system simulation tools are limited to their distinct time scales of transient phenomena. This thesis considers the dynamic phasor (DP) type modelling approaches, where two types of DP theories, namely the shifted-frequency analysis (SFA) and the generalized averaging method (GAM), are considered. In DP-type simulations, power systems are modelled using analogous low-pass time-phasor signals, thereby offering flexible selection of time-step sizes and superior combination of numerical accuracy and efficiency.The ultimate goal of this research is to increase the numerical efficiency of DP-type simulations for the integrated ac-dc power systems. This is achieved by proposing several new DP component models with desirable features and improved numerical properties. First, the constant-parameter SFA model of synchronous machines is proposed to avoid numerically-costly recalculations of the time-varying stator-network matrices. This model is then extended to induction machines for modelling in state-variable based (SV-based) simulation tools. Next, we propose a new, highly efficient model of line-commutated rectifiers using a parametric DP formulation, which is demonstrated as valid for various system operating conditions. Moreover, the effect of ac side harmonics is incorporated to improve modelling fidelity. Finally, the interface between SFA- and GAM-type DPs is achieved to interconnect the proposed DP models. Rigorous case studies demonstrate the superior numerical efficiency of the proposed models, and their advantageous accuracy in capturing the desired phenomena of ac-dc power systems. It is envisioned that the proposed models will become highly useful to many researchers and engineers worldwide, and facilitate the development of next-generation power system simulation tools.

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Efficient algorithms to expedite transient stability analysis of power systems (2015)

With rapid increase in complexity of modern power systems, there is a strong need for better computational tools to ensure the reliable operation of electrical grids. These tools need to be accurate, computationally efficient, and capable of using advanced measurement devices. In this context, transient stability assessment (TSA) is an important study that determines system’s dynamic security margins following a major disturbance. The TSA consists of a set of differential-algebraic equations (DAEs), which are typically solved using time-domain simulation (TDS) approach. While being very accurate, the TDS requires significant computational resources when applied to practical power systems. This problem becomes more significant in transient stability monitoring (TSM), wherein the computational performance of the TDS is typically the bottleneck. This research is to investigate available challenges in the TSM applications and develop new algorithms to help realizing a practical monitoring tool for transient stability studies. The thesis focuses on three research thrusts: i) dynamic reduction of power system to reduce problem size; ii) advanced computation approaches to expedite the TDS method; iii) integration of PMU measurements into the TSM. Initially, a new adaptive aggregation algorithm for dynamic reduction is proposed, wherein parameters of generators and structure of transmission network are considered to aggregate coherent generators and create a reduced-order system. Also, a new criterion is defined to monitor validity of the constructed reduced system. It is shown that the proposed technique is more accurate than traditional aggregation methods. To expedite the TDS approach, this thesis presents two new integration techniques, which are called Multi-Decomposition Approach (MDA) and Successive Linearization and Integration Technique (SLIT). In these methods, the nonlinear DAEs are decomposed into a series of linear subsystems, which participate in approximating actual solution. It is demonstrated that sequential and parallel versions of the MDA and SLIT are faster than state-of-the-art integration techniques. Finally, a dynamic state estimator based on Extended Kalman Filter is developed to convert the PMU measurements into a set of state variables suitable for transient stability studies. Computer studies show that the proposed framework provides accurate results in highly disturbed power systems with fairly low PMU sampling rates.

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Enhancing state estimation in distribution and transmission systems using advanced metering infrastructure (2015)

State estimation is the heart of many tools used in operations of distribution and transmission power systems. The quality of distribution systems state estimation (DSSE) typically suffers from a lack of adequate/accurate measurements and has not been fully implemented by many utilities. Recently, as part of many smart grid related initiatives to modernize power systems, electric utilities started to invest in advanced metering infrastructure (AMI) throughout their distribution systems. The main challenge in this area is that AMI measurements are generally not synchronized, and the difference between the measuring times of smart meters can be significant. In generation and transmission systems, the transmission system state estimation (TSSE) is already prevalent in many utilities. However, TSSE typically suffers from four major problems: partial unobservability, numerical ill-conditioning, bad data, and low accuracy. This thesis is based on three contributions. Firstly, an innovative method is developed to incorporate the non-synchronized measurements coming from AMI based on the credibility of each available measurement and appropriately adjusting the statistical property of the measurement signals. To illustrate the effectiveness of the proposed method, it is compared with traditional approach used in DSSE and the results show the improvements in the accuracy of DSSE. Next, based on the interconnection of the transmission system and distribution systems at PQ buses (feeder heads), a novel approach in TSSE method is presented which uses the DSSE results to provide additional measurements at the PQ buses of the transmission system. Comparisons between the traditional TSSE and the proposed TSSE show that significant improvements are achieved. The third contribution is the methodology for identification of electricity theft points in distribution systems without violating privacy of consumers. The proposed approach models theft as bad data and consists of two stages. Firstly, the multiple bad data identification problem is solved using a heuristic optimization method to locate the points of theft which have redundant measurements. In the second stage, regarding identification of theft points which do not have redundant measurements, a method is proposed based on the discrepancies between the measured and estimated voltage magnitudes. Simulations results demonstrate the effectiveness of the proposed approach.

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Numerically efficient modeling of saturable ac machines for power systems electromagnetic transients simulation programs (2015)

Extensive computer simulations are necessary to operate power systems in a stable, secure, and optimal manner. This thesis considers electromagnetic transients (EMT) simulators, which are widely used to study modern power systems of which rotating machines are essential components. In EMT simulations, induction and synchronous machines are usually represented by general-purpose lumped-parameter models, which can be formulated using different sets of coordinates and state variables. While algebraically equivalent, these models’ numerical properties can differ greatly, which in turn can significantly affect the numerical accuracy and efficiency of entire EMT simulations. The ultimate goal of this thesis is to increase the numerical efficiency of EMT simulators without degrading their numerical accuracy and stability. This is achieved by proposing several new machine models with improved numerical properties. Models are presented for both families of EMT simulators, namely nodal-analysis-based (EMTP-type) and state-variable-based (SVB) programs. Moreover, we incorporate the effect of saturation to improve modeling fidelity. This thesis makes several important contributions to the state of the art. As a first step, the implicit flux correction (FC) method frequently used in SVB programs is reformulated to achieve explicit qd models with main flux saturation. Next, we propose new highly efficient saturable SVB voltage-behind-reactance (VBR) machine models with constant-parameter interfacing circuits. A new and accurate EMTP-type VBR induction machine model with a saturation-independent interfacing circuit is then proposed, thereby avoiding numerically costly re-factorizations of the network’s conductance matrix. Finally, the numerical efficiency of this VBR model is further improved by using multirate techniques. Numerous case studies demonstrate the superior combination of numerical accuracy and efficiency of the proposed models, and their beneficial impact on the speed of EMT simulations. It is envisioned that the proposed models will eventually be included in commercial EMT programs, extending their reach to thousands of engineers worldwide.

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Modeling alternating current rotating electrical machines using constant-parameter RL-branch interfacing circuits (2014)

Transient simulation programs are used extensively for modeling and simulation of various electrical power and energy systems that include rotating alternating current machines as generators and motors. In simulation programs, traditionally, the machine models are expressed in qd-coordinates (rotational reference frame) and transformed variables, and the power networks are modeled in abc-phase coordinates (physical variables), which represents an interfacing problem. It has been shown in the literature that the method of interfacing machine models and the electric network models plays an important role in numerical accuracy and computational performance of the overall simulation. This research considers the state-variable-based simulation programs and proposes a unified constant-parameter decoupled RL-branch circuit in abc-phase coordinates (with optional zero-sequence). The proposed circuits are based on voltage-behind-reactance (VBR) formulation and can be used for interfacing both induction and synchronous machine models. The new models achieve a direct and explicit interface with arbitrary external electrical networks, which results in many computational advantages. Extensive computer studies are presented to verify the proposed models and to demonstrate their implementation in several commonly-used simulation programs. The new models are shown to offer significant improvements in accuracy and numerical efficiency over the existing state-of-the-art models due to their direct interface. It is further envisioned that the proposed models will receive a wide acceptance in research community and simulation software industry, and may enable the next generation of power systems simulation tools.

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Dynamic average-value model of high power ac-dc converters and HVDC systems (2013)

High power switching converters such as line-commutated converters (LCC) and high voltage direct current (HVDC) systems are widely used in modern energy grids for interconnection of industrial loads, large motor drives, as well as electronically-interfaced renewable/alternative/distributed energy resources (DER) and storage systems. For design and analysis of systems with power-electronic-based DERs and loads, accurate and efficient computer models are essential. This thesis is focused on dynamic average-value models (AVM) that neglect switching of converter circuits and are established by averaging the variables (currents and voltages) over a prototypical switching interval. The AVMs are continuous (free of switching), allow using larger integration time steps, and typically run much faster than the conventional detailed switching models, which makes them particularly useful for the system-level studies. This thesis considers the parametric AVM framework, and extends this approach to the thyristor-controlled LCCs operating in inverter mode with current source or voltage source control. The proposed modeling methodology is demonstrated on various topologies including the HVDC CIGRE benchmark system. The research is further extended to incorporate the ac side harmonics into the AVM using the multiple reference frame theory. Traditionally, the AVMs are developed using state-variable-based approach. This thesis also presents a new parametric AVM for direct interfacing in nodal-analysis-based electromagnetic transient programs (EMTP), e.g., PSCAD/EMTDC, EMTP-RV, and MicroTran. It is expected that the proposed models and interfacing approaches will find their application in widely used transient simulation tools and will be appreciated by many researchers and practicing engineers worldwide.

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Generalized dynamic average modeling of line-commutated converter systems in transient simulation programs (2012)

Power electronic converters are used in a wide range of applications as well as being the enabling technology for interfacing the alternative energy resources and many loads in modern power systems. The methodology of developing the so-called dynamic average-value models (AVMs) for such converters is based on averaging the variables (currents and voltages) within a switching interval resulting in numerically efficient models that are much more suitable than the detailed switching models for system-level studies as well as numerical linearization and the respective small-signal analysis. However, the AVMs available in the literature for line-commutated converters have several limitations such as neglecting the effects of losses, being only valid in certain operational modes and under balanced excitation, as well as employing a simplified representation of the multi-phase transformer in high-pulse-count converters. Moreover, a unified AVM methodology for high-pulse-count converters has not yet been established.In this thesis, a generalized AVM methodology is developed for voltage-source- and rotating-machine-fed multi-pulse line-commutated converters for both classes of transient simulation software packages, i.e., state-variable-based and nodal-analysis-based electromagnetic transient program (EMTP) type. The previously-developed AVM approaches, i.e., analytical and parametric, are extended to the EMTP-type programs, and the indirect and direct methods of interfacing the models with external circuit-network are introduced and compared. For the machine-converter systems, the effects of machine and bridge losses are taken into account in the new AVM. Finally, a generalized dynamic AVM methodology is developed for high-pulse-count converters based on the parametric approach. An effective multi-phase transformer model is developed in transformed (qd0) and phase (abc) variables. An efficient transformer model is also developed, which accurately represents the multi-phase transformer using an equivalent three-phase formulation. The proposed generalized AVM remains valid for all operational modes under balanced and unbalanced excitation. This model is employed for AVM implementation in state-variable-based and EMTP-type programs. Extensive simulation and experimental studies are carried out on several example systems in order to compare the developed AVMs against the detailed and previously-developed average models in time- and frequency-domains. The results demonstrate the great accuracy of the proposed AVMs and a significant improvement compared to the previously-developed models.

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Modeling of ac machines using a voltage-behind-reactance formulation for simulation of electromagnetic transients in power systems (2010)

Modeling of electrical machines for power system’s electromagnetic transient programs (EMTP) has been an active area of research since the late 1970s. Most machine models are based on the qd reference frame. The phase-domain (PD) model was also proposed wherein the direct interface with the external network is achieved at a price of increased the computational cost. This thesis focuses on improving the numerical efficiency and accuracy of machine models for power systems transient simulation. The modeling approach developed in this thesis is based on the so-called voltage-behind-reactance (VBR) formulation. The new VBR models of synchronous and induction machines are proposed for EMTP-type solution. It is shown that the proposed VBR models significantly improve the overall numerical accuracy and efficiency, compared with the traditional qd and PD models, due to the direct machine-network interface and better-scaled eigenvalues. The proposed model implementations require as little as 240 flops for synchronous and 108 flops for induction machines, per time-step, respectively. This amounts to 3.75 microseconds and 1.6 microseconds (per time-step) of the CPU time on a modest personal computer and represents a significant improvement over existing EMTP machine models. Magnetic saturation has been incorporated into the VBR models for EMTP-type solution. Computer studies demonstrate that the proposed saturable VBR model in addition of being very efficient also preserves good numerical accuracy and stability even at very large time step. A new full-order VBR induction machine model is also proposed for state-variable simulation languages. Computer studies demonstrate that the proposed models achieve a 740% improvement in computational efficiency as compared with the coupled-circuit models used in state-variable simulation languages. Finally, an approximate VBR induction machine model is proposed for the discretized EMTP solution wherein a constant equivalent conductance matrix is achieved. This further improves the efficiency of the machine-network solution since it avoids the re-factorization of the network conductance matrix at every time step. It is envisioned by the author that due to structural and numerical advantages, the proposed VBR models will find wide application in simulation packages and tools widely used in the power industry.

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Master's Student Supervision (2010 - 2018)
Smart electronic loads for harmonic compensation in future electrical distribution systems (2018)

Common solutions to mitigating harmonics and improving power quality of power systems would include installing dedicated passive or active harmonic filters at the point of common coupling (PCC). However, as the complexity of energy systems increases with integration of renewables and storage systems on the one side, and the number of electronic loads increases rapidly on the other, the centralized compensation of harmonics may not be cost effective. At the same time, many modern loads and energy sources have high–bandwidth front–end power converters that present an opportunity for alternative solutions to improve power quality. This thesis presents a new methodology to compensate harmonics. Utilizing widely deployed smart meters, the measured information of harmonics can be transmitted in real time through the internet to smart electronic loads, where the loads can inject out–of–phase harmonics for compensation in a distributed fashion. First, this thesis investigates the feasibility of using smart meter measurements in the Fred Kaiser Building on the University of British Columbia (UBC) Vancouver campus, which are then used to demonstrate potential harmonic compensation using installed grid–tied converters. Next, since many modern single–phase electronic loads include a power factor correction (PFC) stage, this thesis develops a PFC controller algorithm to inject typical harmonics (i.e. 3rd, 5th, and 7th) at different levels and phase angles for compensation. This concept is further extended to smart LED drivers that also have a PFC stage, which are envisioned to have advanced power quality features. Such smart electronic loads and LED drivers can be integrated into future distribution systems of residential/commercial buildings, microgrids, etc., with distributed controls and communications through Internet of Things (IoT)/advanced user interfaces.

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The application of Shifted Frequency Analysis in power system transient stability studies (2018)

Power system engineers use transient stability computer simulation programs tomodel the power grid’s behaviour when large disruptions cause the grid to deviatefrom its 60-Hz operating frequency. These programs must be able to capture thesefrequency dynamics around 60 Hz while being computationally efficient, as an extensive number of simulations are typically run for a given scenario. In the traditionalpower grid, the large mechanical inertia of the synchronous generators stabilizes thenetwork during disturbances and maintains the system frequency close to the 60 Hzoperating frequency. In the modern grid, however, the increase of renewable energysources lowers the grid’s inertia and larger frequency deviations can occur. Thephasor solution method employed in the traditional programs solves the networkassuming a constant 60-Hz frequency. When deviations from 60 Hz are prominent,the Electromagnetic Transients Program (EMTP) is used as an alternative to thephasor solution to capture these fluctuations. The EMTP models the electricalnetwork based on the differential equations of the network components, which allows the tracing of the network waveforms. However, this discretization requiressmall time-steps, which makes the solution method computationally expensive. TheShifted Frequency Analysis (SFA) method discussed in this work is an alternativeto the traditional phasor solution and to the EMTP solution. In this work, a generalized SFA-based program is written and used for transient stability analysis. SFAis a discrete-time solution method, like the EMTP, but uses a frequency-shiftingtransformation to bring the solution domain down to 0 Hz. Because of this transformation, SFA can capture network dynamics around 60 Hz using large time-steps,making it suitable for transient stability analysis studies.

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Active adaptive auxiliary circuit for stabilizing dc distribution systems with constant power loads (2015)

The portion of high-bandwidth power converters in modern DC distribution systems has been increasing and is projected to dominate over time. These devices having fast response act as constant power loads (CPLs) and possess the so-called negative incremental input impedance characteristics at the input terminals, which may ultimately cause dynamic interactions and instability at certain interfaces in the system. Most existing approaches that address this problem use passive or active damping to reshape the source/load impedances so that stability may be achieved. The drawbacks of most existing methods include energy losses in passive components and/or requirement of changing the internal controls in existing loads.This thesis presents a new active damping methodology using an auxiliary converter circuit to stabilize DC distribution systems with CPLs. A simplified single frequency criterion is proposed for identifying the damping parameters. The proposed auxiliary converter circuit exchanges the energy between very strong power bus and a potentially unstable bus with CPLs, which requires very small injected damping current and achieves lossless damping (conserves the energy during transients). The methodology may operate by emulating fixed or operating-point-depended virtual RC values of the equivalent damping, with the latter having potential advantages of achieving faster damping.To verify and demonstrate the proposed concept, the auxiliary converter circuit has been designed and built with innovative compensated average current control mode. The experimental studies have been carried out on a reduced scale subsystem of a DC microgrid installed by Alpha Technologies Ltd., in Kaiser building at UBC. It is envisioned that the proposed active damping methodology using low-power auxiliary converter circuit may be very cost-effective and practical solution for the future DC systems with modular design and multiple sources/loads being constructed by different vendors with limited knowledge of their parameters and access to their internal controls.

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Large- and small-signal average modeling of dual active bridge dc-dc converter considering power losses (2015)

Detailed switching models are commonly used for analysis of power electronic converters, whereas the average-value modeling (AVM) provides an efficient way to study the power electronic systems in large and small signal sense. This thesis considers a dual-active-bridge (DAB) DC-DC converter, as this topology is very common in applications that require bi-directional power flow and galvanic isolation between the input (primary) and output (secondary) sides. Although this type of converter is very common, the available state-of-the-art models often relay on many assumptions and neglect the losses, which make such models inaccurate for studies where the converter efficiency and small- and large-signal responses must be predicted with high fidelity in system-level studies. We first present an improved detailed model of the DAB DC-DC converter by including the conduction loss, switching loss and core loss, which are derived based on the conventional phase shift modulation approach while considering the energy conservation principle. According to the proposed methodology, the equivalent resistances representing switching loss and core loss have been appropriately derived and added to the final simplified circuit model. The proposed approach is simple to use for modeling DAB converters when considering non-ideal circuit components. The new detailed model increases the accuracy in efficiency predictions over wide range of converter operating conditions.Furthermore, this thesis presents a new reduced-order AVM that includes the parasitic resistance and input/output filters. Based on the large-signal AVM, the small-signal model and control-to-output transfer function are also derived. The proposed AVM is compared with full-order generalized average model and the detailed model in predicting large-signal transients in time domain and small-signal analysis in frequency domain. Experimental prototype of a 150W, 24/48 VDC DAB converter has been designed and built to validate the proposed modeling methodologies. The experimental results confirm that the proposed detailed and average-value models yield high accuracy in predicting the power losses and time-domain responses, which represents an improvement over the existing state-of-the-art models.

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Multiple-input multiple-output converters for future low-voltage DC power distribution architectures (2015)

Multiple-input multiple-output (MIMO) converters have been identified as a cost-effective approach for energy harvesting and dispatching in hybrid power systems such as those envisioned in future smart homes and DC microgrids. Compared with relatively complex set-up of single-input single-output (SISO) converters linked at a common DC bus to exchange power, the MIMO converters possess promising features of fewer components, higher power density, and centralized control. This thesis addresses various issues regarding the development of MIMO converters. Both non-isolated and isolated MIMO converter topologies are proposed. Steady-state analysis and dynamic modeling of MIMO non-inverting buck–boost and flyback converters are introduced and presented in detail. Specific switching strategies are proposed and appropriate control algorithms are presented to enable power budgeting between diverse sources and loads in addition to regulating output voltages. Furthermore, a simple method is put forward for deriving the non-isolated MIMO converters with DC-link inductor (DLI) and DC-link capacitor (DLC). Based on a basic structure, a set of rules is listed for the synthesis of MIMO converters. Using the time-sharing concept, multiple sources provide energy in one period, and multiple loads draw energy in the subsequent period. In the end, general techniques are introduced for extending the SISO converters to their MIMO versions, where parts of the conventional SISO converters are replaced with multiport structures. It is envisioned that MIMO converters presented in this thesis will find their acceptance in the future in various applications with DC distribution, which are becoming increasingly accepted by industry.

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Circuit averaging and numerical average value modeling of flyback converter in CCM and DCM including parasitics and snubbers (2014)

Modeling and analysis of basic DC-DC converters is essential for enabling power-electronic solutions for the future energy systems and applications. Average-value modeling (AVM) provides a time-efficient tool for studying power electronic systems, including DC/DC converters. Many AVM techniques including the analytical and numerical state-space averaging and circuit averaging have been developed over the years and available in the literature. Average-value modeling of ideal PWM converters neglects parasitics (losses) to simplify the derivations and modeling procedures, and the resulting models may not be sufficiently accurate for practical converters. In this work, first we consider a second-order Flyback converter, which has transformer isolation and additional parasitics such as conduction losses that have not been accurately included in the prior literature. We propose three new AVMs using the analytical state-space averaging, circuit averaging, and parametric AVM approaches, respectively. By taking into account conduction losses, the accuracy of the proposed average-value models is significantly improved. The derived (corrected) models show noticeable improvement over the traditional (un-corrected) models. Next, we consider the Flyback converter including the snubbers and leakage inductances in the full-order model. Snubbers reduce electromagnetic interfaces (EMI) during transients and protect switching devices from high voltage, and therefore are necessary in many practical converter circuits. Including snubbers into the model improves accuracy in predicting the circuit variables during the time-domain transients as well as predicting the converter efficiency. It is shown that conventional analytical/numerical methods of averaging do not result in accurate AVM for the full-order Flyback converter. A new formulation for the state-space averaging methodology is proposed that is functional for higher-order converters with parasitics and result in highly accurate AVM. The new approach is justified mathematically and verified experimentally using hardware prototype and measurements. The new model is demonstrated to achieve accurate results in large signal time-domain transients, and small-signal frequency-domain analysis in continuous conduction mode (CCM) and discontinuous conduction mode (DCM), which represents advancement to the state-of-the-art in this field.

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Dynamic average-value modeling of the 120° VSI-commutated brushless dc motors with non-sinusoidal back EMF (2012)

For large and small signal analysis of electromechanical systems with power electronic devices such as Brushless DC (BLDC) motor-inverter drives, average-value models (AVMs) are indisputable. Average-value models are typically orders of magnitude faster than the corresponding detailed models. This advantage makes AVMs ideal for representing motor-drive components in system level studies. Derivation of accurate dynamic average-value model of BLDC motor-drive system is generally challenging and requires careful averaging of the stator phase voltages and currents over a prototypical switching interval (SI) to find the corresponding average-value relationships for the state variables and the resulting electromagnetic torque.The so-called 120° voltage source inverter (VSI) driven brushless dc (BLDC) motors are very common in many commercial and industrial applications. This thesis extends the previous work and presents a new and improved dynamic average-value model (AVM) for such BLDC motor-drive systems. The new model is explicit and uses a proper model of the permanent magnet synchronous machine with non-sinusoidal rotor flux. The model utilizes multiple reference frame theory to properly include the back EMF harmonics as well as commutation and conduction intervals into the averaged voltage and torque relationships. The commutation angle is readily obtained from the detailed simulation. The proposed model is then demonstrated on two typical industrial BLDC motors with differently-shaped back EMF waveforms (i.e. trapezoidal and close to sinusoidal). The results of studies are compared with experimental measurements as well as previously established state-of-the-art models, whereas the new model is shown to provide appreciable improvement especially for machines with pronounced trapezoidal back EMF.

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Hall sensor-based locking electric differential system for BLDC motor driven electric vehicle with independent wheel drives (2012)

It is generally known that stability of vehicles under certain driving conditions may be improved by forcing the wheels to turn at the same speed and angle regardless of the available traction under individual wheels. For conventional all-terrain vehicles or sport-utility vehicles, this function can be achieved by locking the mechanical differential system. In this thesis, we propose an innovative approach for locking the electrical differential system (EDS) of electric vehicles (EV) with independent brushless DC (BLDC) machine-based wheel drives. The proposed method locks the active wheels of the vehicle as if they were operating on a common “virtual” shaft. The locking algorithm is implemented by processing the Hall sensor signals of the considered motors and driving them with a single set of “averaged” Hall signals, thereby operating the motors at the same speed and angle. A detailed switch-level model of EDS embedded with the proposed Sync-Lock Control (SLC) along with the BLDC propulsion motors has been developed and compared against measurements for the considered BLDC propulsion motors. The proposed technique is shown to achieve better results compared to a conventional speed control loop as the considered motors are locked directly through the corresponding magnetic fields. An efficient realization of the proposed controller is presented that makes it possible to be potentially programmed inside existing motor controllers or implemented in a stand-alone microcontroller which can be packaged into a dongle circuit. The proposed SLC is implemented digitally using a programmable integrated circuit microcontroller. First, the Hall signals undergo a layer of filtering to mitigate the errors that are common due to Hall sensor misalignment in low-cost BLDC motors. Then, the locking algorithm is implemented by averaging the filtered Hall sensor signals. The SLC prototype is implemented in form of a standalone dongle-circuit that can be easily placed between the original Hall-sensors and the BLDC motor driver. Operation of typical industrial BLDC motors with the proposed controller is shown to outperform conventional controllers and lock both speed and angle of the motors.

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Parametric average value modeling of flyback converters in ccm and dcm including parasitics and snubbers (2011)

Modeling of switched-mode DC-DC converters has been receiving significant interest due to their widespread applications. Averaged modeling is the most common approach (and tool) that has been used to analyze dynamic performance of converter circuits. Specifically, state-space averaged models are widely used because of their simplicity and generality. However, as has been shown in the literature, the challenges of directly applying this approach to predict the discontinuous variables (states) and include the parasitics and losses have limited application of this approach to a wider range of converter circuits. The recently introduced parametric average value models (PAVM) has a potential to overcome this problem. In this Thesis, first of all a second-order flyback converter has been investigated. An analytical solution of state-apace averaging and small-signal analysis of the flyback converter in continuous conduction mode (CCM) and discontinuous conduction mode (DCM) is given without and with parasitics. The PAVM methodology has been applied to the second-order model to overcome the problem of discontinuous state during the DCM.The snubber circuits in flyback converter have also been investigated. Appearance of snubbers in the model introduces a problem on the output voltage besides improving the efficiency prediction. It is shown that with the snubbers the conventional state-space averaging cannot predict the output voltage correctly in CCM and DCM. To solve this problem the model is partitioned into two different sub-circuits: i) switching sub-circuit circuit; and ii) non-switching sub-circuit. Thereafter it becomes possible apply the averaging on the switching sub-circuit only.Finally, a full-order flyback converter with two RC snubber circuits and all the basic parasitics is considered. The PAVM methodology has been extended to this class of switching converter for the first time. It is shown that including the snubbers and parasitics significantly improves the model accuracy in terms of predicting converter efficiency, which represents an appreciable improvement over all previously existing average models. The proposed model has been verified with detailed simulations and hardware measurements.

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