@inproceedings{6b00af7a07e14ad8896864b2b038cf26,
title = "Neural network adaptive modeling of battery discharge behavior",
abstract = "Dynamic processes are often influenced by external conditions. We expand the neural network approximation capability to behavior modeling within an original hierarchical master-slave relation. Unlike the control theory paradigm, neural weights will replace “state variables” that may be impossible to measure. An application aiming at predicting the end of discharge for rechargeable batteries is fully described. This new battery management tool leads to accurate predictions (mean error is about 3\%) and its implementation into a portable equipment demonstrates that neural networks could be useful even for small size products. The system is further improved by on-line adaptation to actual conditions and individual behavior. This improvement reduces the error prediction to a low 1.5\%.",
author = "Olivier G{\'e}rard and Patillon, \{Jean No{\"e}l\} and Florence D{\textquoteright}alch{\'e}-Buc",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 1997.; 7th International Conference on Artificial Neural Networks, ICANN 1997 ; Conference date: 08-10-1997 Through 10-10-1997",
year = "1997",
month = jan,
day = "1",
doi = "10.1007/bfb0020299",
language = "English",
isbn = "3540636315",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "1095--1100",
editor = "Wulfram Gerstner and Alain Germond and Martin Hasler and Jean-Daniel Nicoud",
booktitle = "Artificial Neural Networks - ICANN 1997 - 7th International Conference, Proceeedings",
}