Predicting Life Of Electric Vehicle And Load Leveling Lead Acid Batteries From Initial Acceptance Test Data By Use Of Pattern Recognition Analysis
Download Predicting Life Of Electric Vehicle And Load Leveling Lead Acid Batteries From Initial Acceptance Test Data By Use Of Pattern Recognition Analysis PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Predicting Life Of Electric Vehicle And Load Leveling Lead Acid Batteries From Initial Acceptance Test Data By Use Of Pattern Recognition Analysis book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Energy Research Abstracts
Semiannual, with semiannual and annual indexes. References to all scientific and technical literature coming from DOE, its laboratories, energy centers, and contractors. Includes all works deriving from DOE, other related government-sponsored information, and foreign nonnuclear information. Arranged under 39 categories, e.g., Biomedical sciences, basic studies; Biomedical sciences, applied studies; Health and safety; and Fusion energy. Entry gives bibliographical information and abstract. Corporate, author, subject, report number indexes.
Predicting Life of Electric Vehicle and Load-Leveling Lead Acid Batteries from Initial Acceptance Test Data by Use of Pattern Recognition Analysis
A novel approach to battery lifetime prediction was applied to life-cycling data for 108 ESB EV-106 6-V golf cart batteries (tests conducted by TRW for NASA-Lewis). Computerized pattern recognition methods were used to examine initial cycling measurements and to classify individual batteries into long-lived or short-lived classes with greater than 85% accuracy. Results of this study were used to design a fabrication and test program for 340 GNB lead-acid cells in a 500 kWh load-leveling battery to be tested at the Battery Energy Storage Test Facility. Preliminary observations on initial test data are reported here. Keywords: Multivariate analysis.