| Autor: |
ECHEVARRÍA, YUVINY, COUSO, INÈS, ANSEÁN, DAVID, BLANCO, CECILIO, SÁNCHEZ, LUCIANO |
| Předmět: |
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| Zdroj: |
Journal of Multiple-Valued Logic & Soft Computing; 2019, Vol. 32 Issue 3/4, p343-367, 25p |
| Abstrakt: |
A Genetic Fuzzy Model of the State of Health of a Li-Ion battery is developed where both outputs of the system and its first derivative with respect to the stored charge are approximated. This approximation is a viable diagnosis technique to detect cell degradation in modern Li-Ion battery technologies. The model is fitted to data by means of a specialization of the θ-Dominance Evolutionary Algorithm, that alters the prioritization of the individuals in the selection stage. An specific operator is used which complements Pareto Non-Dominance levels with a partial order at each level thus models that are potentially better have a reproductive advantage. An empirical study is performed where the results of different multi and many-objectives genetic algorithms are assessed for this problem. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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