- author = "Giulia {Di Capua} and Francesco Porpora and Filippo Milano and Nunzio Oliva and Antonio Maffucci",
- title = "Behavioral Models for Lithium Batteries Based on Genetic Programming",
- journal = "IEEE Access",
- year = "2024",
- volume = "12",
- pages = "108275--108290",
- keywords = "genetic algorithms, genetic programming, Batteries, Integrated circuit modelling, Voltage, Analytical models, Mathematical models, Discharges (electric), Computational modelling, Lithium-ion batteries, Pareto optimisation, Li-ion batteries, behavioural modelling, multi-objective optimisation",
- ISSN = "2169-3536",
-
DOI = "
doi:10.1109/ACCESS.2024.3434716",
- abstract = "This paper proposes a novel methodology based on the Genetic Programming (GP) to derive behavioural models describing the transient evolution of the terminal voltage of a battery. These models analytically relate the battery voltage to its state of charge, charge/discharge rate, and temperature. Compared to the popular equivalent circuit-based models, one of the main advantages is the significant reduction of the effort to produce the experimental dataset required to identify the model parameters. The GP generates a family of optimal 'candidate' analytical models, each associated with suitable metrics that quantify performance indicators like simplicity and accuracy. The methodology is applied to describe the transient discharge phase of a Lithium Iron Phosphate (LiFePO4 or LFP) battery under realistic operating conditions, considering the state-of-charge between 20percent and 80percent, discharge rates comprised between 0.25C and 1C, and temperature ranging from 5degreeC to 35degreeC. The GP provides different solutions that can be chosen by imposing the desired trade-off between accuracy and simplicity. Two models are selected and validated against experimental results. The chosen models guarantee a quite low level of the relative root mean square error (maximum 0.31percent and 0.22percent, respectively) over the range of analysis.",
-
notes = "Also known as \cite{10613806}
See also \cite{Di-Capua:2023:ISCAS}",
