Lithium-ion battery design optimization based on a dimensionless reduced-order electrochemical model

Luis. D. Couto, Mohammad Charkhgard, Berke Karaman, Nathalie Job and Michel Kinnaert

Energy, 2023, vol. 263, issue PE

Abstract: Model-based optimal cell design is an efficient approach to maximize the energy density of lithium-ion batteries. This maximization problem is solved in this paper for a lithium iron phosphate (LFP) cell. We consider half-cells as opposed to full-cells typically considered, which are intermediate steps during battery manufacturing for electrode characterization and they are gaining popularity by themselves as lithium-metal batteries. First, a dimensionless reduced-order electrochemical model is used instead of high-order models. Second, sensitivity equations are analyzed to determine the ranking of the design parameters according to their effect on the energy density, which is often lacking in other contributions. Three parameters, namely electrode thickness, LFP particle radius and electrode cross sectional area, are shown to have the most influential effects. Third, a novel adaptive particle swarm optimization with a specific stopping criterion is used for LIB design optimization. The proposed optimization framework is tested in simulation on a LFP half-cell battery. The results show that the design optimization yields 250 Wh kg−1 for an LFP electrode of 310μm thickness, 10 nm particle radius and 2⋅10−4 m2 cross-sectional area, which is an increase of energy density of 61 Wh kg−1 with respect to an initial design proposed in the literature.

Keywords: Lithium-ion battery; Lithium iron phosphate; Reduced-order electrochemical model; Optimal cell design; Sensitivity analysis; Adaptive particle swarm optimization (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:263:y:2023:i:pe:s0360544222028523

DOI: 10.1016/j.energy.2022.125966

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