10 research outputs found
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Real Time Flux Control in PM Motors
Significant research at the Oak Ridge National Laboratory (ORNL) Power Electronics and Electric Machinery Research Center (PEEMRC) is being conducted to develop ways to increase (1) torque, (2) speed range, and (3) efficiency of traction electric motors for hybrid electric vehicles (HEV) within existing current and voltage bounds. Current is limited by the inverter semiconductor devices' capability and voltage is limited by the stator wire insulation's ability to withstand the maximum back-electromotive force (emf), which occurs at the upper end of the speed range. One research track has been to explore ways to control the path and magnitude of magnetic flux while the motor is operating. The phrase, real time flux control (RTFC), refers to this mode of operation in which system parameters are changed while the motor is operating to improve its performance and speed range. RTFC has potential to meet an increased torque demand by introducing additional flux through the main air gap from an external source. It can augment the speed range by diverting flux away from the main air gap to reduce back-emf at high speeds. Conventional RTFC technology is known as vector control [1]. Vector control decomposes the stator current into two components; one that produces torque and a second that opposes (weakens) the magnetic field generated by the rotor, thereby requiring more overall stator current and reducing the efficiency. Efficiency can be improved by selecting a RTFC method that reduces the back-emf without increasing the average current. This favors methods that use pulse currents or very low currents to achieve field weakening. Foremost in ORNL's effort to develop flux control is the work of J. S. Hsu. Early research [2,3] introduced direct control of air-gap flux in permanent magnet (PM) machines and demonstrated it with a flux-controlled generator. The configuration eliminates the problem of demagnetization because it diverts all the flux from the magnets instead of trying to oppose it. It is robust and could be particularly useful for PM generators and electric vehicle drives. Recent efforts have introduced a brushless machine that transfers a magneto-motive force (MMF) generated by a stationary excitation coil to the rotor [4]. Although a conventional PM machine may be field weakened using vector control, the air-gap flux density cannot be effectively enhanced. In Hsu's new machine, the magnetic field generated by the rotor's PM may be augmented by the field from the stationery excitation coil and channeled with flux guides to its desired destination to enhance the air-gap flux that produces torque. The magnetic field can also be weakened by reversing the current in the stationary excitation winding. A patent for advanced technology in this area is pending. Several additional RTFC methods have been discussed in open literature. These include methods of changing the number of poles by magnetizing and demagnetizing the magnets poles with pulses of current corresponding to direct-axis (d-axis) current of vector control [5,6], changing the number of stator coils [7], and controlling the air gap [8]. Test experience has shown that the magnet strengths may vary and weaken naturally as rotor temperature increases suggesting that careful control of the rotor temperature, which is no easy task, could yield another method of RTFC. The purpose of this report is to (1) examine the interaction of rotor and stator flux with regard to RTFC, (2) review and summarize the status of RTFC technology, and (3) compare and evaluate methods for RTFC with respect to maturity, advantages and limitations, deployment difficulty and relative complexity
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Modeling Reluctance-Assisted PM Motors
This report contains a derivation of the fundamental equations used to calculate the base speed, torque delivery, and power output of a reluctance-assisted PM motor which has a saliency ratio greater than 1 as a function of its terminal voltage, current, voltage-phase angle, and current-phase angle. The equations are applied to model Motor X using symbolically-oriented methods with the computer tool Mathematica to determine: (1) the values of current-phase angle and voltage-phase angle that are uniquely determined once a base speed has been selected; (2) the attainable current in the voltage-limited region above base speed as a function of terminal voltage, speed, and current-phase angle; (3) the attainable current in the voltage-limited region above base speed as a function of terminal voltage, speed, and voltage-phase angle; (4) the maximum-power output in the voltage-limited region above base speed as a function of speed; (5) the optimal voltage-phase angle in the voltage-limited region above base speed required to obtain maximum-power output; (6) the maximum-power speed curve which was linear from rest to base speed in the current limited region below base speed; (7) the current angle as a function of saliency ratio in the current-limited region below base speed; and (8) the torque as a function of saliency ratio which is almost linear in the current-limited region below base speed. The equations were applied to model Motor X using numerically-oriented methods with the computer tool LabVIEW. The equations were solved iteratively to find optimal current and voltage angles that yield maximum power and maximum efficiency from rest through the current-limited region to base speed and then through the voltage-limited region to high-rotational speeds. Currents, voltages, and reluctance factors were all calculated and external loops were employed to perform additional optimization with respect to PM pitch angle (magnet fraction) and with respect to magnet strength. The conclusion was that the optimal-magnet fraction for Motor X is 0.72 which corresponds to a PM pitch angle of 130{sup o}, a value close to the maximum-saliency ratio in a plot of saliency ratio versus PM pitch angle. Further, the strength of Motor X magnets may be lowered to 80% of full strength without significantly impacting motor performance for PM pitch angles between the peak saliency (130{sup o}) and peak-characteristic current (160{sup o}). It is recommended that future research involve maximizing a driving-cycle-weighted efficiency based on the Federal Urban Driving Cycle and the Federal Highway Driving Cycle as criteria for selecting the final optimal-PM fraction and magnet strength for this inset PM motor. Results of this study indicate that the reduction in PM torque due to reduced-magnet fraction will be more than compensated by the reluctance torque resulting from the higher saliency ratio. It seems likely that the best overall performance will require saliency; consequently, we think the best motor will be a reluctance-assisted PM motor. This should be explored for use with other types of PM motors, such as fractional-slot motors with concentrated windings
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Importance of momentum dynamics in BWR neutronic stability: experimental evidence
Momentum dynamics affect the boiling water reactor (BWR) neutronic stability by coupling steam void perturbations and core-inlet coolant flow. Computer simulations have shown that proper modeling of the recirculation loop, which shares the upper and lower plena pressures with the reactor core, is essential for accurate stability calculations. Purpose of this paper is to show experimental evidence, obtained from a recent series of stability tests performed at the Browns Ferry-1 BWR, demonstrating the important role of momentum dynamics in BWR neutronic stability
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Study of the Advantages of Internal Permanent Magnet Drive Motor with Selectable Windings for Hybrid-Electric Vehicles
This report describes research performed on the viability of changing the effectively active number of turns in the stator windings of an internal permanent magnet (IPM) electric motor to strengthen or weaken the magnetic fields in order to optimize the motor's performance at specific operating speeds and loads. Analytical and simulation studies have been complemented with research on switching mechanisms to accomplish the task. The simulation studies conducted examine the power and energy demands on a vehicle following a series of standard driving cycles and the impact on the efficiency and battery size of an electrically propelled vehicle when it uses an IPM motor with turn-switching capabilities. Both full driving cycle electric propulsion and propulsion limited starting from zero to a set speed have been investigated
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The Role of Reluctance in PM Motors
The international research community has lately focused efforts on interior permanent magnet (IPM) motors to produce a traction motor for hybrid electric vehicles (HEV). One of the beneficial features of this technology is the additional torque produced by reluctance. The objective of this report is to analytically describe the role that reluctance plays in permanent magnet (PM) motors, to explore ways to increase reluctance torque without sacrificing the torque produced by the PMs, and to compare three IPM configurations with respect to torque, power, amount of magnet material required (cost), and percentage of reluctance torque. Results of this study will be used to determine future research directions in utilizing reluctance to obtain maximum torque and power while using a minimum amount of magnet material
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Supervisory control in a distributed, hierarchical architecture for a multimodular LMR
This paper describes the directions and present status of the research in supervisory control for multimodular nuclear plants being conducted at Oak Ridge National Laboratory (ORNL) as part of US Department of Energy's (DOE) Advanced Controls Program. First, the hierarchical supervisory control structure envisioned for a Power Reactor Inherently Safe Module (PRISM) multimodular LMR is discussed. Next, the architecture of the supervisory module closest to the process actuators and its implementation for demonstration in a network of CPU's are presented. 12 refs., 3 figs
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Supervisory, hierarchical control for a multimodular ALMR
This paper describes the directions and present status of research in supervisory control for multimodular nuclear plants at ORNL as part of DOE's advanced controls program ACTO. The hierarchical supervisory structure envisioned for a PRISM-like supervisor closest to the process actuators and how it has actually been implemented for demonstration in a network of CPU's is presented next. Two demonstrations of supervisory control with an expert system are also described, one for control of a plant with a single reactor and turbine, the other for control of a plant with three reactors and one turbine. An appendix contains the mathematical basis for the novel approach to large scale system decomposition we have used in the demonstrations of supervisory distributed control of the single reactor plant. 6 refs., 5 figs
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Hierarchical control of a nuclear reactor using uncertain dynamics techniques
Recent advances in the nonlinear optimal control area are opening new possibilities towards its implementation in process control. Algorithms for multivariate control, hierarchical decomposition, parameter tracking, model uncertainties actuator saturation effects and physical limits to state variables can be implemented on the basis of a consistent mathematical formulation. In this paper, good agreement is shown between a centralized and a hierarchical implementation of a controller for a hypothetical nuclear power plant subject to multiple demands. The performance of the hierarchical distributed system in the presence of localized subsystem failures is analyzed. 4 refs., 13 figs
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A distributed hierarchical architecture of expert systems for supervisory control of multimodular nuclear reactors
A hierarchical supervisory control architecture has being implemented at ORNL to coordinate the controllers of a multimodular nuclear plant. The supervisory controller form a network of distributed expert system interfaced with a real-time simulation of the plant, the plant's automatic controllers, and the human operator. The main goal of the supervisory controllers is to maintain the plant operating within safety envelopes while optimizing availability, minimizing stress to components and operators, and facilitating operations. Representative rules implementing strategies for situation dependent reassignment of process goals by embedding diagnostics into the control philosophy are discussed. It should noted that the control philosophies here described use the ALMR concept for illustration purposes and are not part of the official ALMR design at this time. 3 refs., 1 fig
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Application of expert systems to heat exchanger control at the 100-megawatt high-flux isotope reactor
The High-Flux Isotope Reactor (HFIR) is a 100-MW pressurized water reactor at the Oak Ridge National Laboratory. It is used to produce isotopes and as a source of high neutron flux for research. Three heat exchangers are used to remove heat from the reactor to the cooling towers. A fourth heat exchanger is available as a spare in case one of the operating heat exchangers malfunctions. It is desirable to maintain the reactor at full power while replacing the failed heat exchanger with the spare. The existing procedures used by the operators form the initial knowledge base for design of an expert system to perform the switchover. To verify performance of the expert system, a dynamic simulation of the system was developed in the MACLISP programming language. 2 refs., 3 figs