Lithium-ion batteries exhibit a well-known trade-off between energy and power, which is problematic for electric vehicles which require both high energy during discharge (high driving range) and high power during charge (fast-charge capability). Design and material parameters influence the macroscopically-observable performance in a complex and nonlinear way.

Here we present the development and application of three methodologies for model-based interpretation and visualization of these influences: (1) deconvolution of overpotential contributions, including ohmic, concentration, and activation overpotentials of the various cell components; (2) partial electrochemical impedance spectroscopy, allowing a direct visualization of the origin of different impedance features; and (3) sensitivity analyses, allowing a systematic assessment of the influence of cell parameters on capacity, internal resistance, and impedance.

We use two commercial lithium-ion cells (high-energy and high-power) to parameterize and validate physicochemical pseudo-two-dimensional models. In a systematic virtual design study, we vary electrode thicknesses, cell temperature, and the type of charging protocol. We are able to show that low anode potentials during charge, causing lithium plating and cell aging, can be effectively avoided either by using high temperatures or by using a CCCPCV charge protocol which includes a constant anode potential phase. We introduce and quantify a specific charging power as the ratio of discharged energy (at slow discharge) and required charging time (at fast charge). This value is shown to exhibit a distinct optimum with respect to electrode thickness. At 35 °C, the optimum was achieved using a high-energy electrode design, yielding 23.8 Wh/(min∙l) specific charging power at 15.2 min charging time (10 % to 80 % SOC) and 517 Wh/l discharge energy density.

By analyzing the various overpotential contributions, we were able to show that electrolyte transport losses are dominantly responsible for the insufficient charge and discharge performance of cells with very thick electrodes.

Acknowledgements:
This work was supported by DFG through the Research Training Group GRK 2218 SiMET (Simulation of Mechanical, Electrical and Thermal processes in lithium-ion batteries).