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This paper explores detecting interturn short-circuit (ITSC) faults in surface permanent magnet synchronous machines (SPMSM) while simultaneously estimating the (typically large) fault current to determine if operation is within thermal limits. ITSC faults are caused by electrical insulation failures in the stator windings and can lead to shorts to ground resulting in oscillations in torque, localized heating, and even fires. This paper proposes a moving horizon observer methodology for detecting such faults, the level of fault, the motor state, and a thermally sensitive parameter in SPMSM. Theoretical verification of the observability and detection of fault levels and currents is also set forth. Fault detection, fault current estimation, and parameter estimation are verified via simulation for a set of ITSC faults using noisy measurements.

Recently, battery powered electric vehicles EV, such as the Tesla Model S, have reached commercialization. Future EVs will likely pair the battery with a supercapacitor to extend battery life by minimizing the effects of high power and rapidly fluctuating loads. As such, this paper investigates optimal power management of an EV powertrain with both a battery pack and a supercapacitor as energy sources. The battery-supercapacitor-based powertrain has four distinct controllable modes, each with a unique set of dynamics and constraints. Unique power flow expressions for the supercapacitor, vehicle motion, and drive system induction motor are presented. The overall powertrain is represented as a switched interconnected dynamical system having both differential and algebraic constraints in each mode of operation. Constrained by this model, this paper sets forth a hybrid model predictive control strategy for minimizing velocity tracking error and frictional braking to encourage regenerative braking while encouraging fast recharge of the supercapacitor. The optimization is performed using a relaxed representation of the control problem termed the embedding method, collocation for discretization, and traditional nonlinear programming to compute the mode and continuous control inputs. The methodology avoids the computational complexity associated with alternative approaches such as mixed-integer programming. The developed optimization methodology is shown to be useful as a rapid iterative prototyping tool by varying vehicle mass and electric drive maximum power to find combinations that result in satisfactory tracking performance of a trapezoidal drive profile. Performance of the originally specified powertrain and a first design iteration are compared using simulations of the EPA highway and urban drive profiles and the new European drive cycle to verify the first design iteration gives improvement.

A mesh-based magnetic equivalent circuit has been derived to model the dynamics of wound rotor synchronous machines (WRSMs). A particular focus has been placed on the derivation of flux tubes to model machines with an arbitrary number of damper bars placed at an arbitrary depth in the rotor pole tip. Faraday's Law is applied to establish a state model in which winding and damper bar flux linkages are selected as state variables. The resulting coupled magnetic equivalent circuit/state model is solved to predict machine dynamics. An important attribute of the model is that saturation is represented without the need for a relaxation factor, which enables its use as a practical tool in machine design. Data obtained from hardware experiment and a finite-element model are used to validate the proposed methods.

Leakage inductance is one of the most important aspects of transformer design. Herein, the calculation of the leakage inductance of core-type tape-wound transformers is considered in the context of a magnetic equivalent circuit-based analysis used to support optimization-based design. In optimization-based design, numerical efficiency is critical since 105–106 evaluations may be conducted. Thus, this paper presents a computationally efficient method to compute leakage inductances. The method is based on analytical calculation of the field intensity using Ampere's law in the noncore regions of the devices. The predictions of the proposed method are shown to be more consistent with the predictions of a 3-D finite-element analysis than other documented approaches.

Gallium Nitride (GaN) semiconductors have extremely low switching loss, high breakdown voltage, and high junction temperature rating. These characteristics enable improved device performance and thus improved switch mode power converter designs. This paper evaluates the Pareto-optimal performance improvements for a DC generation system with predicted GaN loss characteristics and a rigorous multi-objective optimization based design paradigm. The optimization results show that the application of GaN can achieve a 6.4% mass savings relative to Silicon Carbide (SiC) and 40% mass savings relative to Silicon (Si) at the same loss level for a 10 kW application.

This paper investigates the supervisory-level, fault tolerant control of a 2004 Prius powertrain. The fault considered is an interturn short circuit (ITSC) fault in the traction drive (a surface mount permanent magnet synchronous machine (SPMSM) for which its rotor is part of the vehicle's driveline). ITSC faults arise from electrical insulation failures in the stator windings where part of a phase winding remains functional while the remaining decoupled windings form a self-contained loop. Because the permanent magnets on the rotor (driveline) shaft are able to induce very large eddy currents in this self-contained loop if its rotational velocity is left unchecked, the maximum allowable driveline speed, and consequently, vehicle speed, must be reduced to avoid exceeding the drive's operational thermal limits. A method for detecting these ITSC faults and the induced eddy current in an SPMSM using a moving horizon observer (MHO) is reviewed. These parameters then determine which previously computed, fault-level-dependent SPMSM input–output power efficiency map and maximum safe operating speed is utilized by the supervisory-level controller. The fault tolerant control is demonstrated by simulating a Prius over a 40 s drive velocity profile with fault levels of 0.5%, 1%, 2%, and 5% detected at the midpoint of the profile. For comparison, the Prius is also simulated without a traction motor fault. Results show that the control reduces vehicle velocity upon detection of a fault to an appropriate safe value.

This paper examines the added cost, in terms of mass, required to provide confidence that a machine optimized for passive DC rectification can be accurately represented using a qd model. The inclusion of a set of constraints during the design process is shown to greatly improve the match between qd and detailed models along the entire range of operation for the system, however it is seen that there is an appreciable mass penalty for doing so. Pareto-optimal fronts are used to quantify the cost.

Several technical power system architectures are being evaluated for the Navy's next generation all-electric warship. One concept being considered includes a scheme to power both port and starboard busses from a single generator with dual-windings. This approach offers redundancy and reduces the effects of prime mover light loading, but it inherently couples the two busses through the common generator. In this work, dynamic issues of galvanic and electro-mechanical coupling of power systems through a single dual-wound generator are discussed. Previous works focused on harmonics and galvanic coupling. Herein, focus is placed on average-value modeling of the galvanic coupling and on evaluation for fault response. Conclusions are presented from analysis, simulation, and experimental results.

Future naval medium-voltage direct current (MVDC) power systems will contain a large number of power electronic devices. The switching events from these devices will produce undesirable effects, such as common-mode (ground) current through coupling of the power system and the ships hull. Historically, research in the area of electromagnetic characterization provides insight into common-mode and conduction currents within a specific component. However, there have been relatively few studies developed to understand the impacts of these common-mode drivers in the context of a full system. The aim of this paper is to provide further study of these system-level impacts. This paper utilizes a formalized common-mode modeling approach to further the discussion and research into common-mode issues in the system context. A brief review of the approach is provided. The approach is then applied to a representative notional two-zone MVDC simulation model.

In this research, a dynamic magnetic equivalent circuit (MEC)-based model of a 6-phase wound rotor synchronous generator has been developed. The model is coupled with dual active rectifier bridges to enable detailed switching waveform-level simulations of an MVDC generation system. The MEC model of the generator accurately captures time and spatial harmonics as well as saturation of magnetic material and it represents a reasonable balance between accuracy and computation time compared to lumped parameter or finite element models. In this paper, it is shown that the model enables one to efficiently and accurately explore system dynamics and alternative controls under cases in which a single generator sources multiple healthy or faulted buses.

In the system level design such as the design of distributed energy resources, it is required to perform system-level optimization. To achieve that without computational burden, the concept of scaling laws is considered. In this paper, an MEC based scaling technique is derived in which transformer size/mass is predicted based upon rated power, specified current density, and frequency. Curve-fitting techniques are used to derive a meta-model for scaled mass and power loss. The meta-model is compared to designs obtained using detailed design code. A strong agreement between the results from the detailed design code and that predicted by the meta-model is achieved.

In this letter, a multislice method has been extended to model skew in a magnetic equivalent circuit for wound rotor synchronous machines. Within the model, the machine is divided into a user-defined number of slices along its axial direction. A system of equations is derived in which the magnetic equivalent circuit (MEC) loop flux and the axial currents in each slice are unknowns. A constraint is used to enforce that the axial currents across all slices are equal. The method overcomes challenges of alternative approaches used to model skew in MECs that have been documented by the community. Hardware experiments are used to validate the approach.

When designing permanent magnet synchronous machines, the voltage waveforms and mechanical forces are important in many applications. Many analysts use the finite-element (FE) method to determine fields in the air gap of machines. These fields are then used to calculate vector forces, voltages, or other quantities of interest. Although the FE method has been used for decades, it requires significant computational resources, especially when transient analyses are required. This limits its application to a tool for analysis rather than a large design space, iterative optimization. To address this, an enhanced field reconstruction technique (EFRT) has been developed. Using the EFRT, the fields in the air gap of a machine are computed using a minimum number of FE evaluations. Using the results, a set of basis functions are established that enable the calculation of fields under arbitrary excitation and rotor position. The EFRT greatly reduces the computational effort required to compute the vector fields inside machines and compares favorably with the FE method and hardware results.

This paper considers optimal power management of a fuel cell-battery hybrid vehicle (FCHV) powertrain having three distinct modal configurations (modes): electric motor propelling/battery discharging, propelling/charging, and generating/charging. Each mode has a distinct set of dynamics and constraints. Using component dynamical/algebraic models appropriate to power flow management, the paper develops a supervisory-level switched system model as an interconnection of subsystems. Given the model, the paper sets forth a hybrid model predictive control strategy based on a minimization of a performance index (PI) that trades off tracking and fuel economy in each operational mode. Specifically, the PI trades off velocity tracking error, battery state of charge variance, and electric drive and hydrogen fuel usages while penalizing frictional braking to encourage regenerative braking. The optimization is performed using an embedded system model and collocation with matlab's fmincon to compute mode switches and continuous time controls. The methodology avoids the computational complexity of alternate approaches based on, e.g., mixed integer programming. Projection methods for approximating the switched system solution from the embedded solution are empirically evaluated. To demonstrate the methodology, an example of a FCHV is simulated using three standard velocity driving profiles: a sawtooth profile with a hill climb, the EPA urban dynamic driving schedule, and the New European Driving Cycle. Also, drive cycle fuel usage is compared to that from the Equivalent Consumption Minimization Strategy.

In recent years, population-based methods (evolutionary algorithms, particle swarm methods, etc.) have emerged as an effective tool for component and system design. Although relatively straightforward to apply, to capitalize on their potential, one must be able to explore a large design space. Herein, a magnetic equivalent circuit model is described to enable large-design-space exploration of salient-pole wound-rotor synchronous machine drive systems. Specifically, the model has been derived to evaluate machines with an arbitrary number of poles, stator slots (integer slots/pole/phase), winding layout, magnetic material, and a wide range of stator and rotor geometries. In addition, the model and solution technique have been structured to minimize the computational effort. An important attribute of the model is that saturation is handled with relatively few iterations and without the need for a relaxation factor to obtain convergence.

In recent research, a field reconstruction (FR) technique was developed to enable more efficient evaluation of the magnetic fields and forces within induction machines. By using the FR, the results of two finite-element (FE) solutions (in which stator current is used as the input to the FE model) are used to establish basis functions for the flux densities in the air gap of the machine. The basis functions are then used to predict the magnetic fields and forces under arbitrary stator excitation. In this paper, the technique is enhanced to enable modeling with stator voltage (rather than stator current) as the model input. This enables a more convenient coupling of the FR model to external circuit components to model overall system performance.

In recent research, a field construction technique (FCT) was derived to enable more efficient evaluation of the magnetic fields and forces within induction machines. Using the FCT, the results of two finite-element (FE) solutions are used to establish basis functions for the flux densities in the airgap of the machine. The basis functions are then used to predict the magnetic fields and forces under arbitrary stator excitation. In this paper, a multirate FCT (MRFCT) is proposed to enable efficient FCT modeling of machines that are connected to power electronic converters. Within the MRFCT, the low- and high-frequency components of the stator current are partitioned. The partitioned currents are then used to calculate the flux density and forces at time steps commensurate with the respective low- and high-frequency dynamics. It is shown that applying the MRFCT, the forces and fields of a machine connected to a power electronic circuit can be obtained at a small fraction of the time required for a coupled FE/circuit model.

The magnetic equivalent circuit (MEC) technique is a powerful analysis and design tool that combines relative accuracy with moderate computational effort. In this paper, a nodal-based MEC formulation and a mesh-based MEC formulation of a magnetic system are compared. The Newton-Raphson algorithm is used to solve the algebraic system, and to draw conclusions about the computational efficiency of the two formulations under linear and nonlinear operation. Although the two formulations exhibit similar performance under linear operating conditions, the performance of the mesh-based model is significantly better than that of the nodal-based model under nonlinear operation.

In this research, a goal has been to explore the design of the generator for a megawatt level DC power system. Population-based multi-objective optimizations have been performed for several machine/rectifier alternatives, including permanent magnet synchronous machines (PMSMs) with active rectifiers and wound rotor synchronous machines (WRSMs) with active and passive rectifiers. From the optimizations, Pareto-optimal fronts are used to show that the PMSM-based designs provide a machine with significantly lower mass for a specified efficiency. In addition, it is shown that the WRSMs designed for passive rectification are less massive than those designed for active rectification. Finally, it is shown that for the WRSM/passive rectifier systems, most machines on the Pareto-optimal front have no damper windings, which has the potential to greatly simplify machine construction.

Medium voltage dc distribution systems are presently of interest for future naval warships. In order to provide hardware validation for research associated with the development of these systems, the Purdue Reduced-Scale Naval DC Microgrid has been constructed. This paper documents the system being constructed and provides some initial test results.

This paper first puts the challenges from design constraints imposed by mission load requirements on future naval surface combatants into context. Moreover, it provides results from experiments at the three partner universities designed to de-risk emerging medium voltage DC (MVDC) technology based systems and to provide validated models for future systems studies. These experiments are carries out in three recently established test beds all designed for MVDC related work. The investigations specifically targeted two major areas of interest: fault management and rapid power transfer between loads and sources. The results obtained to date reveal valuable insight into both areas.

Both new and existing naval vessels of all sizes face ever-increasing power supply requirements to support advanced mission loads including high power sensors, weapons, and launchers. Adding additional conventional generators to support these loads is infeasible given size and weight constraints and given the pulsed nature of those new loads. Instead, an optimization-based Power Management Controller (PMC) is used to dynamically control power system sources and loads in real time in order to serve system needs with a minimal amount of power supply equipment. In this paper, a Model Predictive Control (MPC) approach is used to dynamically coordinate sources and loads based on future demand. A cost function is used to prioritize various ship goals and objectives, and constraints are added to reflect hardware limitations. A Constrained Nonlinear MPC algorithm is then used to minimize the cost over a finite future horizon and generate control commands in real-time. The PMC is demonstrated to successfully control and improve system performance on a hardware test bed for ship power system research.

In this research a general and scalable method is proposed to transform differential-mode circuits into their common-mode equivalents for the purpose of modeling common-mode voltage and current in large, complex power systems. The technique is demonstrated for an example dc-based ship power system and validated against a detailed model.

This paper highlights a magnetic equivalent circuit model for wound rotor synchronous machine design. The model includes provisions to calculate the performance of machines with an arbitrary number of damper windings in either the q- or d-axis. The computational cost of the model is considered on several modern computing platforms. Its use within design allows for a comprehensive, accurate exploration of a design space on a timeline that is consistent with most commercial product development.

The progression of distributed generation within a bulk power system will lead to the need for greater control of transmission-line power flows. Static synchronous compensators (STATCOMs) provide a power-electronics-based means of embedded control of transmission-line voltage and power flows. The integration of energy storage with a STATCOM can extend traditional STATCOM capabilities to four-quadrant power flow control and transient stability improvement. This paper discusses energy storage systems (ESSs) integrated with conventional and multilevel bidirectional power converters for a hybrid STATCOM/ESS. Conventional, diode-clamped, and cascaded multilevel converter-based STATCOM/ESSs are developed, and their performances for a variety of power system applications are compared using battery energy storage. The advantages and disadvantages of each topology are presented. Both simulation and experimental results are provided to validate the conclusions

Power management of a ship’s electrical system has become important due to increasing loads from manpower-reducing automation, greater power requirements of advanced weapons and sensors, introduction of all electric propulsion, and the increasing cost of oil-based fossil fuels. A coordinated power management strategy of the ship’s electric power grid is desired to optimally allocate power flows and minimize fuel consumption. This paper develops such an optimal power management system for an interconnected, supervisory-level ship power system model based upon a ship power system test bed developed for the Office of Naval Research. The ship power system consists of two electrical generators, one rated at 59 kW to represent a gas turbine engine-generator pair and the other rated at 11 kW to represent a diesel generator, an 8 kW pulsed power load that represents the discharge and charge of a capacitor bank for an electromagnetic railgun system, and 37 kW ship propulsion system comprised of an induction motor coupled to the propeller shaft. The ship propulsion system’s induction motor has switched operation with two modes of operation, propelling and generating; the latter mode means that excess kinetic energy during ship slowing can be used to charge the capacitor bank for loads such as pulsed power loads. Given the switched system model, the paper sets forth a hybrid model predictive control strategy based on a minimization of a performance index that trades off fuel consumption, velocity tracking error, and electrical bus voltage error. The optimization is performed using a relaxed representation of the control problem (termed the embedding method) and collocation for discretization with traditional numerical programming to compute the mode and continuous control inputs. The methodology avoids the computational complexity associated with alternative approaches, e.g., mixed-integer programming. Numerical optimization is performed with MATLAB’s sqpLineSearch. To demonstrate the power management approach, a scenario is simulated where the ship is to follow a changing desired velocity while simultaneously maintaining the bus voltage at a desired value, keeping the 11 kW generator at a fuel efficient operating point, and minimizing the fuel use of the 59 kW generator.Copyright © 2014 by ASME

This paper develops and validates a power flow behavioral model of a gas turbine engine (GTE) composed of a gas generator and free power turbine. The behavioral model is suitable for supervisory level (optimal) controller development of the engine itself or of electrical power systems containing gas-turbine-generator pairs as might be found in a naval ship or terrestrial electric utility plant. First principles engine models do not lend themselves to the supervisory level control development because of their high granularity. For the behavioral model, “simple” mathematical expressions that describe the engine's internal power flows are derived from an understanding of the engine's internal thermodynamic and mechanical interactions. These simple mathematical expressions arise from the balance of energy flow across engine components, power flow being the time derivative of energy flow. The parameter fit of the model to a specific engine such as the GE LM2500 detailed in this work utilizes constants and empirical fits of power conversion efficiencies obtained using data collected from a high-fidelity engine simulator such as the Gas Turbine Simulation Program (GSP). Transient response tests show that the two-norm normalized error between the detailed simulator model and behavioral model outputs to be 2.7% or less for a GE LM2500.

The derivation of accurate dynamic average-value models for synchronous machine-rectifier systems is challenging. A recently proposed parametric approach uses a computer-aided procedure for constructing the required averaged models, wherein the key nonlinear functions are extracted from a detailed (valve-by-valve) simulation. This letter shows that by using a judicious selection of parametric functions, a model obtained at a fixed generator speed is also valid for variable speeds. This is an important feature that makes this approach applicable to systems where electromechanical dynamics and variable speed operation is required.

A mesh-based dynamic magnetic equivalent circuit model for wound rotor synchronous machines has been derived in this research. As part of this effort, a reluctance network has been enhanced to model flux distribution around stator tooth tips and damper bar openings. Faraday's law is applied to establish a state model in which stator winding flux linkages are selected as state variables. The resulting coupled MEC/state model is solved to analyze machine dynamics.

Harmonics in the electromagnetic torque can be a source of concern in interior permanent magnet synchronous machine (IPMSM) drives. The harmonics are created by nonidealities in the electromagnetic fields produced by the magnets and the stator excitation. They lead to vibration that can cause premature wear of the drivetrain components as well as acoustic noise that may be bothersome to users. In this research, a feedback-based currentcontrol scheme has been developed to mitigate the torque harmonics.

Several key performance parameters of shipboard power systems are affected by the grounding scheme applied. The grounding scheme impacts the nature of voltage transients during switching events and faults, identifiability and locatability of ground faults, fault current levels, and power quality. Power system simulations play an important role in choosing an appropriate grounding scheme and optimizing its components. The tools typically used for power system analysis need to be carefully tested to determine if they are appropriate for modeling effects of different grounding schemes and in particular the high frequency transients. This paper sheds light on modeling and validation techniques specific to grounding models. Furthermore, insight is provided to present research into new types of power system modeling techniques based on scattering parameters for improved accuracy at higher frequencies of interest. A testbed designed to study the impact of different types of grounding schemes is also introduced and first characterization measurements in the frequency domain provided. The paper concludes with an outlook to future work, which will focus on rigorous validation of the models developed.

Excitation strategies are explored as part of an overall design to minimize mass and maximize efficiency of a 2 kW portable power generator. The design includes 16 variables and is based upon a magnetic equivalent circuit model that includes core loss. Despite the influence of saturation and core loss, a relatively straightforward field-oriented type control is derived that is consistent with the goals of mass and loss reduction. Design and control are validated through hardware experiment.

The electric power grid is evolving into a state that has yet to be defined. Renewable and other distributed energy sources cannot be economically and reliably integrated into the existing grid because it has been optimized over decades to support large centralized generation sources. Thus, the problem of achieving greater penetration of renewable energy has sparked fervor in research to improve reliability and reduce cost. Herein, we consider the problem of accomplishing hardware verification on Micro-Grids with dispatchable (diesel-engine or other combustible) generators. A significant hurdle to evaluating newly developed control and optimization schema can be the experimental validation in hardware. Given the hazards, expense, and space requirements of operating a combustion engine, this paper provides a simple and reliable alternative that is suitable for university and other space-constrained laboratories that wish to extend and validate their ideas for renewable energy integration.

In ac power systems, including micro-grids, it is important to regulate the amplitude and frequency of the voltages throughout the system. Many of the existing and proposed control strategies for micro-grids are patterned after the classic ac power system. That is, frequency regulation is achieved by designing micro-sources (commonly called Distributed Energy Resources or DERs) to exhibit an output-frequency-versus-power characteristic similar to the speed-versus-power (droop) characteristics of conventional turbo- and hydro-generators. Moreover, voltage regulation strategies are patterned after the output-voltage-versus-reactive-power (droop) characteristics of the automatic voltage regulators (AVRs) used in conventional turbo- and hydro-generators. In this paper, established approaches of frequency and voltage regulation are reviewed. Alternative strategies that utilize modern communication and control technologies are presented and discussed.

High penetration levels of stochastic renewable sources introduce variability into power systems that result in voltage and frequency regulation difficulties. As the cost of fossil fuels increase and governments mandate large renewable-energy portfolios, new engineering approaches will be necessary to compensate for this variable generation. Today renewable energy penetration levels are often limited by using curtailment, by installing additional fossil-fuel-based generation, or by installing expensive energy storage. Recent research focused on mitigating regulation challenges include: advanced sensing, storage, and controls. This paper introduces a new research facility at Sandia National Laboratories dedicated to the development of tools for designing and implementing adaptive, secure, scalable, microgrids with high penetration levels of stochastic renewables.

This paper considers optimal power flow control of a fuel cell-battery hybrid vehicle (FCHV) powertrain having three distinct modal configurations (modes): electric motor propelling/battery discharging, propelling/charging, and generating/charging. Each mode has a distinct set of dynamics and constraints. Using component dynamical/algebraic models appropriate to power management, the paper develops a supervisory-level switched system model as an interconnection of subsystems. Given the model, the paper sets forth a hybrid model predictive control strategy based on a minimization of a performance index (PI) that trades off tracking and fuel economy in each operational mode. Specifically the PI trades off velocity tracking error, battery state of charge variance, and hydrogen usage while penalizing frictional braking. The optimization is performed using an embedded system model and collocation with MATLAB's fmincon to compute mode switches and continuous time controls thereby avoiding the computational complexity of alternate approaches based on, e.g., mixed integer programming. To demonstrate the approach, an example FCHV following trapezoidal and sawtooth drive profiles is simulated. PI weights are varied for reduced hydrogen use and higher final battery charge to illustrate various performance trade-offs.

In this research, a magnetic equivalent circuit (MEC) model for population-based design (PBD) of salient-pole wound-rotor synchronous machines (WRSMs) is derived. The model includes a unique approach to represent fringing flux to the rotor poles based upon observations of flux paths seen in finite element solutions. In addition, the airgap flux tubes are simplified by including rotor fringing as separate static flux tubes. Finally, the flux tubes representing the rotor pole tip are selected to more effectively capture localized saturation. To enable rapid evaluation of design candidates, a mesh-based solution is applied to solve the MEC. A mesh approach is selected since it has been shown to have superior convergence properties compared to nodal-based models. The MEC model has been shown to match well with finite element (FE) models and measurements.

A recently developed method for real-time hybrid model predictive control (HMPC) of switching converters is extended to the Cuk converter. Specifically, an integral quadratic performance index is used for stored energy and power flow regulation. The discrete-time HMPC problem is solved in real time using an active set optimization. Experimental results show that the control performs well in both steady state and transient operation (buck and boost) over a wide range of operating points.

The focus of this research is to investigate the tradeoffs between mass, efficiency, and cost of commercially available induction machines (IMs). To support this effort, data from large number of IMs is used to establish Pareto-optimal fronts between efficiency and mass and efficiency and cost. From the Pareto-optimal fronts, relatively straightforward models are formulated for the mass versus efficiency and cost versus efficiency of IMs. Parameters of the models are obtained using a genetic algorithm (GA).

In this paper, a model predictive control method is implemented for improved performance of a boost converter sourcing a constant power load (CPL). The method applies results of recently developed hybrid optimal model predictive control to determine switching through real-time minimization of a user-defined performance index tailored to CPLs. In contrast to many controllers designed for boost converters, the proposed method does not utilize small-signal average value models in its development. Therefore, the controller design is not equilibrium-point specific. In addition, since the optimization is performed online, the control is more flexible than many recently proposed controllers that utilize the hybrid model to determine optimal switching strategies offline and subsequently apply utilizing a look-up table. The result is a robust, high bandwidth control that has been validated in hardware.

Permanent magnet and wound rotor synchronous machines (PMSMs and WRSMs) are often used in diesel engine-based portable power generation systems. In these applications, there is a growing desire to improve machine efficiency in order to reduce fossil fuel requirements. In addition, there is a desire to reduce mass to improve mobility. To attempt to address these competing performance objectives, a system analyst is confronted with numerous choices, including machine type (PM or WR), converter architecture (active/passive), and control. Herein, to assist the analyst, design tools capable of performing automated multi-objective optimization of PMSMs and WRSMs connected to both active and passive rectifiers are described. The tools are then used to derive tradeoffs between mass and efficiency for a 3 kW application.

Recently, a new approach to control switching in a boost converter was developed based upon hybrid optimal control theory. A focus of the initial research was on the theoretical development of the control and using simulation to compare its performance to more traditional control approaches. Herein, the research is extended with a particular focus on the hardware implementation of the approach. Included in the implementation are techniques to compensate for delay resulting from computation and sampling. In addition, a new parameter estimator has been derived to estimate load resistance and source voltage required by the controller. The results of time-domain simulation and hardware experiments are used to validate the performance of the hybrid optimal control and estimator.

This workshop will present recently developed results on the solution of the hybrid/switched optimal control problem using the embedding method developed by Bengea and DeCarlo (Automatica, January 2005). Using a variation of the collocation method, a numerical solution of the problem via sequential quadratic programming is outlined. With these tools and a model predictive control approach, application of the techniques to the switching control of a boost converter using a circuit specific estimator is then presented. Results include real time model predictive control of the boost converter at a switching speed of 10 kHz. This is followed by the model predictive control of mobile robots and groups of autonomous aerial vehicles (AUVs).

Medium voltage dc distribution systems are currently of interest for future naval warships. In order to provide hardware validation for research associated with the development of these systems, a low power Medium Voltage DC Testbed (MVDCT) is being constructed. This paper documents the system being constructed and provides some initial test results.

This workshop will present recently developed results on the solution of the hybrid/switched optimal control problem using the embedding method developed by Bengea and DeCarlo (Automatica, January 2005). Using a variation of the collocation method, a numerical solution of the problem via sequential quadratic programming is outlined. Using these tools and a model predictive control approach, application of the techniques to the switching control of a boost converter using a sliding mode observer is then presented followed by the model predictive control of mobile robots and groups of autonomous aerial vehicles (AUVs). Finally, a solution to the power management problem in a hybrid electric vehicle is presented with simulation studies for a variety of driving profiles including the new EPA driving profile. The examples will not only describe appropriate models, MPC control methodologies, and simulation studies, but also highlight the broader appeal of these newly developed techniques for modeling, analysis, and design of hybrid/switched systems. SCHEDULE: SEPTEMBER 2, 2008

The objective of th is program was to develop a flywheel energy storage system capable of achieving its maximum energy density, while being capable of repeated high peak -power demands. The key to achievi ng this objective is the development of a composite hub capable of supporting an optimized high -speed composite rim. The existing Beacon Power commercial flywheel system uses a composite rim and aluminum hub. The aluminum hub is the stress limiting part of the rotor, which prevents the carbon fiber composite from reaching its maximum capability at a significantly higher operating speed. During this project a composite hub has been designed that will allow the rim to run closer to its maximum stress capa bility resulting in a more compact and lighter weight system. Compared to battery energy storage systems, the FESS is more reliable, requires less maintenance, has a much longer life, high er cyclic capability, operates with minimal degradation in performa nce with time and in extreme environments, and eliminates environmental problems associated with disposal of batteries. The flywheel advantage begins where battery performance falls off. During ride -through and distributed generation use, electrical syst ems can experience multiple charge and discharge cycles even within one minute. Flywheels are not sensitive to high rates of charge and discharge, beyond checking that the torsional stresses are acceptable and the parts won’t slip; and such rates have no noticeable effects on the life of the flywheel. In fact, the greatest overall efficiency for a flywheel is achieved at high charge and discharge rates. If the battery rapidly discharges, it will only be able to extract a small percentage of its stored energy and more batteries may be needed to meet power and life requirements to account for this. In comparison, flywheels are relatively insensitive to deep discharge. The typical depth of a flywheel discharge is 75% to 90% of the stored energy and there are only minor effects on life due to these depths of discharge. Flywheels will also interface with any primary energy device on a space platform such as photovoltaic cells, fuel cells, or chemical batteries, improving their overall efficiency and energy density. The most important advantage is that flywheels can be designed to have more than 100,000 charge and discharge cycles. Batteries have a typical life cycle time below 1,000 charge/discharge cycles. In comparison, a flywheel is designed for many thousands of cycles with minimal degradation in performance of life. The discharge time of a flywheel is the time it takes for the flywheel to decelerate from its maximum speed at full rated power. In general and unlike batteries, flywheels are well suit ed for equal charge and discharge rates. Under cyclic conditions, the energy -to -weight ratio of a chemical battery will be significantly less, possibly less than half, of the claimed energy density, whereas the flywheel’s energy -to -weight capacity would r emain nearly constant under these same conditions.