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This paper solves the inverse dynamics of a tethered kite analytically. Specifically, the paper presents a procedure for determining the angle of attack, induced roll angle, and tether tension magnitude needed to achieve a desired combination of translational kite position, velocity, and acceleration. The focus of the paper is on energy harvesting kites. However, the underlying approach is applicable to other kite systems, such as kites for propulsion (e.g., SkySails, Hamburg, Germany). Solving inverse kite dynamics analytically is valuable for trajectory optimization, online state estimation, and the analysis of fundamental limitations on kite maneuvers. Previous work in the literature presents several models of kite dynamics, with varying degrees of fidelity and complexity. However, the nonlinearity of these models often makes them difficult to use for optimization, estimation, and control. The paper shows that, under reasonable assumptions, inverse kite dynamics can be solved in terms of the roots of a fourth-order polynomial function of angle of attack. This function has a geometric interpretation, providing insight into the multiplicity of resulting solutions. Moreover, for special cases including a kite with noncambered wings, these solutions can be computed analytically. A simulation validates the success of the proposed approach in computing inverse kite dynamics for a cross-current trajectory.

Shipboard power systems that service large-scale dynamic loads and electric propulsion can significantly improve their performance by adding controllable energy storage. These systems require power management controls that consider dynamics like generator ramp rates, along with energy storage capacity and location. In the early-stage design process, many alternative designs are considered, and each requires a unique controller. This article describes a numerical optimization technique that establishes an upper bound performance criteria without manually designing controllers for each system. The solution is a best case performance that assumes perfect future knowledge of the time-varying load. While unrealistic in real-time, this technique yields a fair comparison between competing architectures without the variability of different control methods. To demonstrate the concept, a notional multi-bus power system architecture is evaluated on a representative set of operational duties to illustrate comparisons between system attributes like energy storage power and efficiency ratings. A design trade study shows that the success rate for a baseline ship can improve from under 60% to nearly 100% by increasing generator power by 10% and energy storage capacity by 100%. These automated architecture benchmarks fit into a broader total ship optimization process, or can be used in human-driven trade studies.

In the design of nuclear reactor systems, reliability is always a top consideration. Their main control method is the movement of “control rods” which inhibit the rate of reaction. Various gravity-based fail-safe methods are available during the failure of an actuator, but even safe failures limit reactor capability. This is especially important for mobile platforms like submarines and aircraft carriers where it may be months before maintenance can be performed. By introducing a redundant system and adding features like hot-swapping, overall system reliability is improved. This paper proposes a design for supporting reactor control rods utilizing three independently powered and controlled linear motors. By utilizing a three motor design, the system becomes resilient to two points of motors failing off, or a single point of failure should a motor fail on or become corrupted in some way. In addition, there is no central computer, failure detection logic, or direct communication between these motors, which makes the system simpler and avoids single points of failure. Each motor acts independently and if one has a failure, the other two will overpower it.

A semi-active hybrid energy storage system, consisting of a Li-ion battery pack, dc/dc converter, and Li-ion capacitor pack was developed for a range extended plug-in vehicle. The vehicle has a series-parallel drivetrain with two electric motors, a gas engine, gearbox, and a clutch to allow the engine to run decoupled from the gearbox in range extending mode. The peak dc electrical requirement of the electric drivetrain is about 175 kW, which is similar to the peak power capability of the developed hybrid energy storage system. A model of the prototype hybrid energy storage system, which has the Li-ion capacitor pack connected directly to the motor drive's dc bus and the battery pack connected to the Li-ion capacitor pack via a dc/dc converter, is developed and used to determine the optimal power split between the battery and Li-ion capacitor packs and for tuning the developed real-time control system. The real-time control system is shown through modeling and experimental testing of the full scale hybrid energy storage systems to reduce battery pack losses, increase vehicle range, and to have performance approaching that of the optimal control solution as calculated via dynamic programming.

Practical laboratory exercises improve student understanding and motivation for learning abstract engineering concepts. The Department of Electrical and Computer Engineering at the United States Naval Academy (USNA), a four-year undergraduate institution, is tasked with teaching all students a course in electrical circuits and power. The course aimed at non-STEM majors includes a weekly two hour laboratory period to assist in drawing out these abstract concepts. The instructors for an Electrical Engineering circuits and power course for non-STEM majors jointly developed and troubleshot a series of five real-world, laboratory experiments. These experiments are intended to demonstrate real world skills and applications of the abstract concepts covered during the class.

Small power systems are often used in support of broader systems like factories, climate control, and electric warships. Aggressive operation of the power systems often creates power shortfalls, which can be studied and controlled by assigning a value of lost load. However, this formulation is typically not sufficient to cover the potential interactions between the power system and the “process controller” that supervises the overall system and creates the load demand. For example, if a load demand for a device is not met, it will re-occur rather than just disappear. This paper formulates a general partition of the system control into a process controller which proposes actions, and a power manager which provides feedback on the feasibility of those actions. The two modules communicate via a defined interface to agree on a set of feasible actions that best accomplish the tasks within the limits of a power system. An electric warship is used as an example to demonstrate this setup, which can be used to operate power systems and to generate representative load profiles for use in evaluating candidate designs.

A relatively new class of power converter controls can create self-forming AC networks without synchronous generators. These controllers have significant development and stability proofs under normal operating conditions. This paper studies one particular type, the Dead-Zone Oscillator, under unbalanced load and fault conditions. Two different implementations of this controller are used to control commercial three-phase inverters that accept either voltage or current commands. Simulations and experiment demonstrate the robustness of this controller to single phase unbalance, phase to phase faults, and open phase failures. Understanding the characteristics of this type of oscillator and applying it to unbalanced loads will help to further the process of implementing these small self-sustaining converters into larger networks with little to no adverse effects.

The dynamics of a general class of weakly nonlinear oscillators can be used to control power converters to create a self-forming AC network of distributed generators. Many control stability results for these &ldquo, virtual&rdquo, oscillators consider the interaction of voltage-source converters, but most practical converters use a nested current loop. This paper develops a general method to extend voltage-source stability results to current-controlled converters using a virtual admittance. A fast current control loop allows a singular perturbations analysis to demonstrate the equivalence of the two. This virtual admittance can also manipulate load sharing between converters without changing the core nonlinear dynamics. In addition, Virtual Oscillator Control is experimentally demonstrated with three-phase voltage-sourced and current-controlled inverters. This validates the equivalence of the two formulations, and extends previous single phase testing into three phases. The extension to current-controlled converters enhances safety and increases the breadth of applications for existing control methods.

This paper presents a new pulse width modulation (PWM) technique for a high-frequency link Modular Multilevel Converter topology for grid-integrated renewables. The topology generates a multilevel output voltage with low harmonic distortion, increased reliability, and design flexibility due to the modular nature of the converter. A central full-bridge converter is connected to multiple High Frequency Link modules via high frequency transformers. Each module produces its own isolated DC voltage, and modules are inserted or bypassed to synthesize large AC voltages. The proposed PWM technique equalizes module utilization without increasing losses, and retains inherent capacitor voltage balancing. Simulation results using SIMULINK models show that the proposed modulation scheme results in better performance than conventional schemes such as level-shifted carrier PWM, phase-shifted carrier PWM, hybrid schemes or nearest-level modulation.

This paper presents a new method of constructing a transformerless voltage-sourced medium-voltage multilevel converter using existing discrete power semiconductor devices and printed circuit board technology. While the approach is general, it is particularly well suited for medium-voltage converters and motor drives in the 4.16 kV 500–1000 kW range. A novel way of visualizing the power stage topology is developed, which allows simplified mechanical layouts, while managing the commutation paths. Using so many discrete devices typically drives cost and complexity of the gate-drive system including its control and isolation; a gate-drive circuit is presented to address this problem. As with most multilevel topologies, the dc-link voltages must be balanced during operation. This is accomplished using an auxiliary circuit made up of the same power stage and an associated control algorithm. Experimental results are presented for a 4.16-kV 746-kW five-level power converter prototype.

Many control stability results consider the interaction of voltage-source converters, but most real converters use a nested current loop. This paper develops a general method to extend voltage-source stability results to current-controlled converters. Nonlinear dead-zone oscillator (DZO) control, a control method originally formulated for voltage-source inverters, is experimentally validated with a three-phase system of current-controlled inverters. This validates the equivalence of current-based control, and also demonstrates DZO control in three-phase hardware for the first time. The extension to current-controlled converters enhances safety and increases the breadth of application for existing control methods that assume voltage-source converters. In addition, current-based control can manipulate the load sharing between converters using a virtual output impedance.

Shipboard integrated power systems, the key enablers of ship electrification, call for effective power management control (PMC) to achieve optimal and reliable operation in dynamic environments under hardware limitations and operational constraints. The design of PMC can be treated naturally in a model predictive control (MPC) framework, where a cost function is minimized over a prediction horizon subject to constraints. The real-time implementation of MPC-based PMC, however, is challenging due to computational complexity of the numerical optimization. In this paper, an MPC-based PMC for a shipboard power system is developed and its real-time implementation is investigated. To meet the requirements for real-time computation, an integrated perturbation analysis and sequential quadratic programming (IPA-SQP) algorithm is applied to solve a constrained MPC optimization problem. Several operational scenarios are considered to evaluate the performance of the proposed PMC solution. Simulations and experiments show that real-time optimization, constraint enforcement, and fast load following can be achieved with the IPA-SQP algorithm. Different performance attributes and their tradeoffs can be coordinated through proper tuning of the design parameters.

Both naval and commercial ships are incorporating new power and energy system technologies to improve fuel economy and performance while servicing high power pulsed loads. These assets can be best utilized with load demand forecasting and/or prediction, especially when considering limits on generator ramp rates, distribution lines, and energy storage capacity. Obtaining future load demand data and designing a controller to accommodate it can be challenging, but with potentially large payoff. However, this information is not useful in all cases. This paper develops a method to quantify the potential value of future information depending on the specific power system characteristics. This quantitative approach aids designers in deciding how and when to deploy future forecasting in controller design, and provides insight into the potential benefits of these more complex controllers. To quantify this trade off, two optimization-based control methods are developed. One uses only current information, while the other has an exact forecast of the future. As examples, the method is applied to a notional naval ship and drill platform service vessel with representative power and energy system architectures under indicative operational load demands.

Power converter topologies with series-connected devices must maintain repeatable blocking voltages across the devices to ensure reliability. Effective voltage sharing requires consistent diode reverse recovery charges, which is not guaranteed with commercially produced devices. To evaluate this effect, this paper measures and statistically quantifies the variation in reverse recovery characteristics of diodes from one manufacturer. Statistics are provided for various groupings by date code, shipment tube, and back-and front-end epitaxy processes. The devices are then matched for reverse recovery charge and series-connected in a medium-voltage five-level power converter. Voltage sharing is significantly better than a similar test with devices chosen at random. However, the device voltage mismatch exceeds predictions based solely on charge mismatch.

A low voltage ride-through solution for an indirect three-level matrix converter based open-end winding drive is demonstrated. The proposed method uses the input filter capacitors to exchange the inertial energy from the motor and thereby maintain the flux in the motor during grid fault conditions. The input filter capacitors act as the voltage source for inverters during the fault. Ride-through is achieved without any additional energy storage elements or modifications to the converter topology. The presented approach demonstrates that the drive is capable of handling voltage-sag conditions and reaccelerate without any significant transients after the fault clears. This paper briefly discusses the topology followed by the proposed strategy for ride-through, its implementation and reconnection to the grid. The method is validated through simulations and the results are presented. The experimental setup with the results are also shown with analysis.

AC/DC converters for worldwide deployment or multiple applications are often required to operate with single-or three-phase AC connections at a variety of voltages. Electric vehicle charging is an excellent example: a typical AC/DC converter optimized for a 400 V three-phase European connection will only produce about 35% of rated power when operating on a 240 V single-phase connection in North America. This paper proposes a reconfigurable AC-DC converter with integral DC-DC stage that allows the single-phase AC power to roughly double compared to a standard configuration, up to 2/3 of the DC/DC stage rating. The system is constructed with two conventional back-to-back three-phase two-level bridges. When operating in single-phase mode, rather than leaving the DC side under-utilized, our proposed design repurposes one of the DC phase legs and the unused AC phase to create two parallel single-phase connections. This roughly doubles the AC output current and hence doubles the single phase AC power.

The utility-scale renewables, PV and wind, are already approaching grid parity. To further enhance their penetration rapidly requires additional cost reduction and increased efficiency. There are other applications in utility-scale energy storage systems and in substations with power ratings in MW range for rapid charging of multiple electric vehicles. Towards this goal, one approach to interface with grid voltages of up to 34.5 kV is to use Power Electronic Transformers (PETs) consisting of back-to-back MMCs (Modular Multilevel Converters) and a high-frequency transformer. The control in such systems is challenging because of the lack of significant energy storage in the dc link between the two MMCs, unlike those in applications such as HVDC transmission and medium-voltage motor drives. Constraints on the modulation scheme under such conditions are pointed out and a novel control scheme is proposed in this paper that results in a ripple-free voltage dc link voltage, but controllable, between the two MMCs, reduced ripple in the capacitor voltages in each MMC module, and low THD in the ac currents at the terminals of the MMCs. Using this control scheme, the operation at controllable power factor and under unbalanced grid conditions is investigated and the simulation results are presented.

Future shipboard power system architectures are designed to service high-power pulsed loads through a combination of generators and energy storage for volume and weight considerations. Optimal control solutions therefore depend on both past and future events. This complicates evaluation of the relative performance of different architectures due to dependence on controller strategies and algorithms. Herein, we introduce a technique for early stage evaluation of the relative performance of various ship power system designs by assuming a known future and calculating the best-case performance of any possible controller design. We demonstrate this technique using 6 mission scenarios on a representative multi-bus power system architecture. The controller has perfect future knowledge of the loads on each 10 minute mission, which provides an upper bound on performance for a given architecture. While not usually achievable in practice, this technique allows a fair early stage comparison of multiple architectures regardless of controller type.

High energy pulse load weapons and sensors on smaller, more affordable platforms are the driving factors behind future all-electric warship power and energy systems. For design space exploration, legacy design tools based on ideal steady-state conditions are not sufficient. Design studies must factor in the significant impact that these dynamic loads have on the stability of the warship's power and energy system, especially under critical operational demands. This paper continues to improve the fidelity of a shipboard load demand model by introducing exogenous features that trigger load responses. This operational vignette-based model contains a set of shipboard asset and rival characteristic features in a virtual battlespace. With pre-defined rules that model human-in-the-loop decision-making, a representative time-domain battle scenario is simulated and ship-wide load demands are recorded. By modifying ship and opponent features along with the rules that define engagement, a set of realistic test cases designed specifically for Monte Carlo simulation can accurately predict the load demand over a wide range of notional operational vignettes. In addition, since representative rival data is now added to the model, tactical mission effectiveness can be assessed as a function of power demand.

Range anxiety and battery cycle life are two major factors which restrict the development of electric vehicles. Battery degradation can be reduced by adding supercapacitors to create a Hybrid Energy Storage System. This paper proposes a systematic approach to configure the hybrid energy storage system and quantifies the battery degradation for electric vehicles when using supercapacitors. A continuous power-energy function is proposed to establish supercapacitor size based on national household travel survey statistics. By analyzing continuous driving action in standard driving cycles and special driving phases (start up and acceleration), the supercapacitor size is calculated to provide a compromise between the capacitor size and battery degradation. Estimating the battery degradation after 10 years, the battery capacity loss value decreases 17.55% and 21.6%, respectively, under the urban dynamometer driving schedule and the US06. Furthermore, the battery lifespan of the continuous power-energy configured system is prolonged 28.62% and 31.39%, respectively, compared with the battery alone system.

Hybrid vehicle fuel economy performance is highly sensitive to the energy management strategy used to regulate power flow among the various energy sources and sinks. Optimal non-causal solutions are easy to determine if the drive cycle is known a priori. It is very challenging to design causal controllers that yield good fuel economy for a range of possible driver behavior. Additional challenges come in the form of constraints on powertrain activity, such as shifting and starting the engine, which are commonly called “drivability” metrics and can adversely affect fuel economy. In this paper, drivability restrictions are included in a shortest path stochastic dynamic programming (SP-SDP) formulation of the real-time energy management problem for a prototype vehicle, where the drive cycle is modeled as a stationary, finite-state Markov chain. When the SP-SDP controllers are evaluated with a high-fidelity vehicle simulator over standard government drive cycles, and compared to a baseline industrial controller, they are shown to improve fuel economy more than 11% for equivalent levels of drivability. In addition, the explicit tradeoff between fuel economy and drivability is quantified for the SP-SDP controllers.

The papers in this special section focus on energy conversion in next generation electric ships. These papers bring together papers focused on the recent advancements in energy conversion techniques used in electric ship technologies.

Power converter operation on high-impedance grids can result in oscillatory behavior as a result of “self-synchronization” of an inverter's phase detection unit (PDU). This phenomenon is particularly of concern in renewable energy applications and it occurs when the converter's injected current changes the voltage angle at the point-of-common coupling (PCC) and synchronizes to itself through its PDU. One of the most prevalent PDUs in industry is based on the synchronous-reference frame (SRF) phase-locked loop (PLL). In this work the large signal stability limit of the SRF-PLL is modified to include the angle of reactive current injection, the phenomena of reduced gain margin as a result of self-synchronization is explained and a method to prevent the effects of self-synchronization is proposed and demonstrated. The proposed method is referred to as the grid-sync (GS) PLL and requires a real-time estimation of the grid impedance. The GS-PLL is shown to improve small-signal stability in order to reduce phase-margin erosion.

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.

The design and control of electric warship power systems is a complex, challenging problem and numerous power system architectures, technologies, algorithms, and control schemes have been proposed. Instead of a quantitative assessment of these ideas based on ideal, steady-state conditions, a set of representative operational vignettes that span the entire electric warship mission package is introduced in order to obtain true results. This paper describes a set of realistic test cases that provide load demand dynamics based on a variety of unique scenarios, mission load characteristics, and human-in-the-loop decision-making. Stochastic and deterministic power profiles are established for individual ship systems and mission loads, which are then combined together for a particular scenario. These test cases can be applied to early-stage design trade studies as well as design tool development. For example, various control methods can be benchmarked against the same test cases. In addition to the established test cases, the method used here enables operators to communicate to design engineers how they intend to use the ship (not the other way around).

The field of biomimetics seeks to distill biological principles from nature and implement them in engineering systems in an effort to improve various performance metrics. In this paper, a biology-based approach is used to address the problem of radiated propulsor noise in underwater vehicles using active control. This approach is one of "tail articulation" of a stator blade, which is carried out using a suitable strategy that effectively alters the flow field impinging on a rotor downstream and in turn changes the radiated noise characteristics of the rotor blades. A reduced-order two-dimensional noise model is developed by characterizing the impact of the articulation as a point circulation input, which is then used to develop an active control strategy. An experimental investigation of such a control strategy is also carried out in this paper using a simple benchtop open-channel water tunnel at Re=4000 and stepper motor controlled articulation. Tail articulations using sinusoidal and transient motion were able to reduce the wake deficit behind the stator by as much as 40-60%. The implications of the proposed method for reducing blade tonal noise in autonomous underwater vehicles are briefly discussed at the end of the paper.

An energy management controller based on shortest path stochastic dynamic programming (SP-SDP) is implemented and tested in a prototype vehicle. The controller simultaneously optimizes fuel economy and powertrain activity, namely gear shifts and engine on–off events. Previous work reported on the controller's design and its extensive simulation-based evaluation. This paper focuses on implementation of the controller algorithm in hardware. Practical issues concerning real-time computability, driver perception, and command timing are highlighted and addressed. The SP-SDP controllers are shown to run in real-time, gracefully handle variations in engine start and gear-shift-completion times, and operate in a manner that is transparent to the driver. A hardware problem with the test vehicle restricted its maximum engine torque, which prevented a reliable fuel economy assessment of the SP-SDP controller. The data that were collected indicated that SP-SDP controllers could be straightforwardly designed to operate at different points of the fuel economy tradeoff curve and that their fuel economy may equal or exceed that of a baseline industrial controller designed for the vehicle.

This paper addresses the electrical power management control problem for naval vessels. Traditional electrical system designs use a small number of large generators to provide sufficient power. Modern and future ships have a variety of power sources and loads, including fast pulse power loads. These various power sources and sinks must be coordinated to attain maximum performance. The analytical Pontryagin minimum principle is used to produce solutions for a simple system model and provide insight into the problem. A numerical optimization technique, Deterministic Dynamic Programming, is then used to develop similar solutions and study similarities and differences between the two techniques.

Wind farms typically contain a variety of voltage control equipment including tap-changing transformers, switched capacitors, SVCs, STATCOMs, and the generators themselves. This paper focuses on the control of this equipment by addressing three major issues. The first is the ability of wind turbines to provide reactive power; voltage saturation in the collector system often limits the reactive power output of individual generators. The second topic is the stability of the system when independent control laws for the various types of equipment interact. Specifically, under some conditions a tap-changing transformer may not behave as expected or become unstable. The third major issue is the high-level control of the substation or wind farm; it is desirable to treat all the equipment as an integrated system rather than independent devices in order to meet cost, maintenance, fault tolerance, or other requirements. This high-level control problem is addressed for several types of available future information including exact future knowledge and stochastic predictions. Deterministic and Stochastic Dynamic Programming are used to develop control algorithms. The results demonstrate that while exact future knowledge is very useful, simple prediction methods yield no benefit.

Hybrid Vehicle fuel economy and drivability performance are very sensitive to the “Energy Management” controller that regulates power flow among the various energy sources and sinks. Many methods have been proposed for designing such controllers. Most analytical studies evaluate closed-loop performance on government test cycles. Moreover, there are few results that compare stochastic optimal control algorithms to the controllers employed in today's production hybrids. This paper studies controllers designed using Shortest Path Stochastic Dynamic Programming (SPSDP). The controllers are evaluated on Ford Motor Company's highly accurate proprietary vehicle model over large numbers of real-world drive cycles, and compared to a controller developed by Ford for a prototype vehicle. Results show the SPSDP-based controllers yield 2–3% better performance than the Ford controller on real-world driving data, with even more improvement on a government test cycle. In addition, the SPSDP-based controllers can directly quantify tradeoffs between fuel economy and drivability.

Hybrid Vehicle fuel economy performance is highly sensitive to the energy management strategy used to select among multiple energy sources. Optimal solutions are easy to specify if the drive cycle is known a priori. It is very challenging to compute controllers that yield good fuel economy for a class of drive cycles representative of typical driver behavior. Additional challenges come in the form of constraints on powertrain activity, like shifting and starting the engine, which are commonly called ?drivability? metrics. These constraints can adversely affect fuel economy. The benefits of including drivability restrictions in a Shortest Path Dynamic Programming (SPDP) formulation of the energy management problem are investigated for the first time. It is shown that this method yields up to 10% fuel economy improvement on a representative parallel electric hybrid when compared to a simpler instantaneous optimization formulation. This result is obtained by comparing a SPDP controller designed for drivability to a second SPDP controller, designed for fuel economy only, that uses an additional instantaneous optimization step for the incorporation of drivability. The results also quantify the tradeoff between drivability and fuel economy.