The 1990 progress report and future plans

This document describes the progress and plans of the Artificial Intelligence Research Branch (RIA) at ARC in 1990. Activities span a range from basic scientific research to engineering development and to fielded NASA applications, particularly those applications that are enabled by basic research carried out at RIA. Work is conducted in-house and through collaborative partners in academia and industry. Our major focus is on a limited number of research themes with a dual commitment to technical excellence and proven applicability to NASA short, medium, and long-term problems. RIA acts as the Agency's lead organization for research aspects of artificial intelligence, working closely with a second research laboratory at JPL and AI applications groups at all NASA centers

A Modular Programmable CMOS Analog Fuzzy Controller Chip

We present a highly modular fuzzy inference analog CMOS chip architecture with on-chip digital programmability. This chip consists of the interconnection of parameterized instances of two different kind of blocks, namely label blocks and rule blocks. The architecture realizes a lattice partition of the universe of discourse, which at the hardware level means that the fuzzy labels associated to every input (realized by the label blocks) are shared among the rule blocks. This reduces the area and power consumption and is the key point for chip modularity. The proposed architecture is demonstrated through a 16-rule two input CMOS 1-μm prototype which features an operation speed of 2.5 Mflips (2.5×10^6 fuzzy inferences per second) with 8.6 mW power consumption. Core area occupation of this prototype is of only 1.6 mm 2 including the digital control and memory circuitry used for programmability. Because of the architecture modularity the number of inputs and rules can be increased with any hardly design effort.This work was supported in part by the Spanish C.I.C.Y.T under Contract TIC96-1392-C02- 02 (SIVA)

A Review of Fault Diagnosing Methods in Power Transmission Systems

Transient stability is important in power systems. Disturbances like faults need to be segregated to restore transient stability. A comprehensive review of fault diagnosing methods in the power transmission system is presented in this paper. Typically, voltage and current samples are deployed for analysis. Three tasks/topics; fault detection, classification, and location are presented separately to convey a more logical and comprehensive understanding of the concepts. Feature extractions, transformations with dimensionality reduction methods are discussed. Fault classification and location techniques largely use artificial intelligence (AI) and signal processing methods. After the discussion of overall methods and concepts, advancements and future aspects are discussed. Generalized strengths and weaknesses of different AI and machine learning-based algorithms are assessed. A comparison of different fault detection, classification, and location methods is also presented considering features, inputs, complexity, system used and results. This paper may serve as a guideline for the researchers to understand different methods and techniques in this field

Electronic operation and control of high-intensity gas-discharge lamps

The ever increasing amount of global energy consumption based on the application of fossil fuels is threatening the earth’s natural resources and environment. Worldwide, grid-based electric lighting consumes 19 % of total global electricity production. For this reason the transition towards energy efficient lighting plays an important environmental role. One of the key technologies in this transition is High-Intensity Discharge (HID) lighting. The technical revolution in gas-discharge lamps has resulted in the highlyefficient lamps that are available nowadays. As with most energy efficient light solutions, all HID lighting systems require a ballast to operate. Traditionally, magnetic ballast designs were the only choice available for HID lighting systems. Today, electronic lampdrivers can offer additional power saving, flicker free operation, and miniaturisation. Electronic lamp operation enables additional degrees of freedom in lamp-current control over the conventional electro-magnetic (EM) ballasts. The lamp-driver system performance depends on both the dynamics of the lamp and the driver. This thesis focuses on the optimisation of electronically operated HID systems, in terms of highly-efficient lamp-driver topologies and, more specifically, lamp-driver interaction control. First, highly-efficient power topologies to operate compact HID lamps on low-frequency-square-wave (LFSW) current are explored. The proposed two-stage electronic lamp-driver consists of a Power Factor Corrector (PFC) stage that meets the power utility standards. This converter is coupled to a stacked buck converter that controls the lamp-current. Both stages are operated in Zero Voltage Switching (ZVS) mode in order to reduce the switching losses. The resulting two-stage lamp-drivers feature flexible controllability, high efficiency, and high power density, and are suitable for power sandwich packaging. Secondly, lamp-driver interaction (LDI) has been studied in the simulation domain and control algorithms have been explored that improve the stability, and enable system optimisation. Two HID lamp models were developed. The first model describes the HID lamp’s small-signal electrical behaviour and its purpose is to aid to study the interaction stability. The second HID lamp model has been developed based on physics equations for the arc column and the electrode behaviour, and is intended for lampdriver simulations and control applications. Verification measurements have shown that the lamp terminal characteristics are present over a wide power and frequency range. Three LDI control algorithms were explored, using the proposed lampmodels. The first control principle optimises the LDI for a broad range of HID lamps operated at normal or reduced power. This approach consists of two control loops integrated into a fuzzy-logic controller that stabilises the lamp-current and optimises the commutation process. The second control problem concerns the application of ultra high performance (UHP) HID lamps in projection applications that typically set stringent requirements on the quality of the light generated by these lamps, and therefore the lampcurrent. These systems are subject to periodic disturbances synchronous with the LFSW commutation period. Iterative learning control (ILC) has been examined. It was experimentally verified that this algorithm compensates for repetitive disturbances. Third, Electronic HID operation also opens the door for continuous HID lamp dimming that can provide additional savings. To enable stable dimming, an observer-based HID lamp controller has been developed. This controller sets a stable minimum dim-level and monitors the gas-discharge throughout lamp life. The HID lamp observer derives physical lamp state signals from the HID arc discharge physics and the related photometric properties. Finally, practical measurements proved the proposed HID lamp observer-based control principle works satisfactorily

SoC estimation for lithium-ion batteries : review and future challenges

ABSTRACT: Energy storage emerged as a top concern for the modern cities, and the choice of the lithium-ion chemistry battery technology as an effective solution for storage applications proved to be a highly efficient option. State of charge (SoC) represents the available battery capacity and is one of the most important states that need to be monitored to optimize the performance and extend the lifetime of batteries. This review summarizes the methods for SoC estimation for lithium-ion batteries (LiBs). The SoC estimation methods are presented focusing on the description of the techniques and the elaboration of their weaknesses for the use in on-line battery management systems (BMS) applications. SoC estimation is a challenging task hindered by considerable changes in battery characteristics over its lifetime due to aging and to the distinct nonlinear behavior. This has led scholars to propose different methods that clearly raised the challenge of establishing a relationship between the accuracy and robustness of the methods, and their low complexity to be implemented. This paper publishes an exhaustive review of the works presented during the last five years, where the tendency of the estimation techniques has been oriented toward a mixture of probabilistic techniques and some artificial intelligence