A survey of life support system automation and control

The level of automation and control necessary to support advanced life support systems for use in the manned space program is steadily increasing. As the length and complexity of manned missions increase, life support systems must be able to meet new space challenges. Longer, more complex missions create new demands for increased automation, improved sensors, and improved control systems. It is imperative that research in these key areas keep pace with current and future developments in regenerative life support technology. This paper provides an overview of past and present research in the areas of sensor development, automation, and control of life support systems for the manned space program, and it discusses the impact continued research in several key areas will have on the feasibility, operation, and design of future life support systems

Exploring the Mysteries of System-Level Test

System-level test, or SLT, is an increasingly important process step in today's integrated circuit testing flows. Broadly speaking, SLT aims at executing functional workloads in operational modes. In this paper, we consolidate available knowledge about what SLT is precisely and why it is used despite its considerable costs and complexities. We discuss the types or failures covered by SLT, and outline approaches to quality assessment, test generation and root-cause diagnosis in the context of SLT. Observing that the theoretical understanding for all these questions has not yet reached the level of maturity of the more conventional structural and functional test methods, we outline new and promising directions for methodical developments leveraging on recent findings from software engineering.Comment: 7 pages, 2 figure

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 323)

This bibliography lists 125 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during April, 1989. Subject coverage includes; aerospace medicine and psychology, life support systems and controlled environments, safety equipment exobiology and extraterrestrial life, and flight crew behavior and performance

Five-Axis Machine Tool Condition Monitoring Using dSPACE Real-Time System

This paper presents the design, development and SIMULINK implementation of the lumped parameter model of C-axis drive from GEISS five-axis CNC machine tool. The simulated results compare well with the experimental data measured from the actual machine. Also the paper describes the steps for data acquisition using ControlDesk and hardware-in-the-loop implementation of the drive models in dSPACE real-time system. The main components of the HIL system are: the drive model simulation and input – output (I/O) modules for receiving the real controller outputs. The paper explains how the experimental data obtained from the data acquisition process using dSPACE real-time system can be used for the development of machine tool diagnosis and prognosis systems that facilitate the improvement of maintenance activities

An On-Chip Delay Measurement Technique for Small-Delay Defect Detection using Signature Registers

This paper presents a delay measurement technique using signature analysis, and a scan design for the proposed delay measurement technique to detect small-delay defects. The proposed measurement technique measures the delay of the explicitly sensitized paths with the resolution of the on-chip variable clock Generator. The proposed scan design realizes complete on-chip delay measurement in short measurement time using the proposed delay measurement technique and extra latches for storing the test vectors. The evaluation with Rohm 0.18- m process shows that the measurement time is 67.8% reduced compared with that of the delay measurement with standard scan design on average. The area overhead is 23.4% larger than that of the delay measurement architecture using standard scan design, and the difference of the area overhead between enhanced scan design and the proposed method is 7.4% on average. The data volume is 2.2 times of that of test set for normal testing on average

Holistic Management of Energy Storage System for Electric Vehicles

While electric vehicles (EVs) have recently gained popularity owing to their economic and environmental benefits, they have not yet dominated conventional combustion-engine vehicles in the market. This is due mainly to their short driving range, high cost and/or quick battery performance degradation. One way to mitigate these shortcomings is to optimize the driving range and the degradation rate with a more efficient battery management system (BMS). This dissertation explores how a more efficient BMS can extend EVs' driving range during their warranty periods. Without changing the battery capacity/size, the driving range and the degradation rate can be optimized by adaptively regulating main operational conditions: battery ambient temperature (T), the amount of transferred battery energy, discharge/charge current (I), and the range of operating voltage (min/max V). To this end, we build a real-time adaptive BMS from a cyber-physical system (CPS) perspective. This adaptive BMS calculates target operation conditions (T, I, min/max V) based on: (a) a battery performance model that captures the effects of operational conditions on the degradation rate and the driving range; (b) a real-time battery power predictor; and (c) a temperature and discharge/charge current scheduler to determine target battery operation conditions that guarantee the warranty period and maximize the driving range. Physical components of the CPS actuate battery control knobs to achieve the target operational conditions scheduled by the batteries cyber components of CPS. There are two subcomponents for each condition (T, I): (d) a battery thermal management system and (e) a battery discharge/charge current management system that consists of algorithms and hardware platforms for each sub-system. This dissertation demonstrates that a more efficient real-time BMS can provide EVs with necessary energy for the specified period of time while slowing down performance degradation. Our proposed BMS adjusts temperature and discharge/charge current in real time, considering battery power requirements and behavior patterns, so as to maximize the battery performance for all battery types and drivers. It offers valuable insight into both current and future energy storage systems, providing more adaptability and practicality for various mobile applications such as unmanned aerial vehicles (UAV) and cellular phones with new types of energy storages.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/143920/1/kimsun_1.pd