From material properties to device metrics: a data-driven guide to battery design

Abstract

The suitability of a battery for a given application depends on its metrics for energy (W h kg⁻¹ and/or W h L⁻¹), power (W kg⁻¹ and/or W L⁻¹), cost ($ per kWh), lifetime (cycles and/or years), and safety. This paper provides a data-driven perspective explaining how material properties, cell design decisions, and manufacturing costs influence and control these metrics. Insights drawn from the literature and past experience are supported by 200 000+ Monte Carlo simulations, which were conducted for lithium-ion batteries using the Battery Performance and Cost Model (BatPaC). A cell with optimal energy, power, and cost is best achieved with a high voltage and a low area specific impedance. If the focus is only on optimal energy and/or cost (i.e., where power is less critical), cells also benefit from active materials with high specific capacities. For example, the energy metric of 500 W h kg⁻¹ can be met in cells with open circuit voltages less than 4 V only if the average specific capacity of the positive and negative materials is at least ∼500 mA h g⁻¹. The values of other parameters (e.g., thicknesses, densities, and material costs) are shown to have less influence on achieving cell metrics. It is suggested that the best way to achieve optimal energy, power, and/or cost while maintaining long lifetimes and safe operation is through modification of these other parameters to facilitate the stable operation of materials with high voltage, high capacity, and low area specific impedance. It is also shown that new negative active materials must produce cells with an area specific impedance less than 85 Ω cm² to be cost-competitive in all electric vehicles.