Lithium-ion battery pack performance and longevity can be severely affected by cell-to-cell variations. Statistical modeling is an important tool for optimization of performance and safety of battery packs. This work presents uncertainty quantification of Lithium-ion battery performance, in particular sensitivity analysis. This analysis is based on calculation of Sobol' indices from a surrogate model, based on Polynomial Chaos Expansion. Performance is compared with Monte Carlo simulations.
Uncertainty Quantification of Lithium-Ion Batteries with Polynomial Chaos / Orcioni, Simone; Conti, Massimo. - ELETTRONICO. - (2020), pp. 1-5. (Intervento presentato al convegno 2020 IEEE International Symposium on Circuits and Systems (ISCAS) nel 10-21 Oct. 2020) [10.1109/ISCAS45731.2020.9180515].
Uncertainty Quantification of Lithium-Ion Batteries with Polynomial Chaos
Orcioni, Simone;Conti, Massimo
2020-01-01
Abstract
Lithium-ion battery pack performance and longevity can be severely affected by cell-to-cell variations. Statistical modeling is an important tool for optimization of performance and safety of battery packs. This work presents uncertainty quantification of Lithium-ion battery performance, in particular sensitivity analysis. This analysis is based on calculation of Sobol' indices from a surrogate model, based on Polynomial Chaos Expansion. Performance is compared with Monte Carlo simulations.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
