Title :
Battery diagnostics and performance prediction: computational vs. expert system based approach
Author :
Noviello, Ennio Italico ; Serio, Vito ; Plaitano, Aldo ; Tortora, Ciro
Author_Institution :
IRSIP, CNR, Napoli, Italy
Abstract :
In this paper, two methods for battery field diagnostics and performance prediction are discussed. The former is a computational method which employs the relationships between the internal state indicators of a cell and the most significant influencing factors (e.g., temperature, technology, electrolyte density, age, work cycle). The latter uses artificial intelligence techniques based on rules developed from the expertise of specialists. The two methods are compared with respect to stationary batteries
Keywords :
ageing; automatic test equipment; automatic testing; battery testers; chemistry computing; electrochemistry; electrolytes; expert systems; power engineering computing; secondary cells; age; artificial intelligence; computational method; electrolyte density; expert system; field diagnostics; internal state indicators; performance prediction; stationary batteries; technology; temperature; work cycle; Automatic control; Batteries; Diagnostic expert systems; Metrology; Rail to rail outputs;
Conference_Titel :
Telecommunications Energy Conference, INTELEC '93. 15th International
Conference_Location :
Paris
Print_ISBN :
0-7803-1842-0
DOI :
10.1109/INTLEC.1993.388480