Digital Twin Enables Rational Design of Ultrahigh-Power Lithium-Ion Batteries

With the widespread applications of electric vehicles, power grid stabilization, and high-pulsed power loads, high-power lithium-ion batteries (LIBs) are in urgent demand. However, the existing experimental-based design of high-power batteries is usually costly and inefficient, and provides limited information on the complex physicochemical processes inside the batteries. Digital twin concept is promising for capturing the batteries' electrochemical performance, and optimizing the power capability of LIBs. Here, an electrochemical-thermal coupled model is developed as a digital twin model for rational design of ultrahigh-power LiFePO4/graphite LIBs. The model can accurately predict the batteries' performance and help to predetermine the optimal parameters to achieve an ultrahigh power capability. After model-guided optimization, the battery shows a high energy density of 92.38 Wh kg(-1) at an ultrafast discharging current of 50 C and can withstand 150 C pulse discharging tests. Notably, the digital twin model can reveal experimentally inaccessible time- and space-resolved information and identify the rate-determining steps inside the battery. Hence, model-driven optimization of ultrahigh-power LiFePO4/graphite batteries is successfully realized aiming at the critical factors in the rate-determining steps. The work provides an instructive design of ultrahigh-power LiFePO4/graphite batteries, which might guide the future direction to boost the power capability of LIBs.

Automated summary

With the widespread applications of electric vehicles, power grid stabilization, and high-pulsed power loads, there is an urgent demand for high-power lithium-ion batteries. This study develops a digital twin model to optimize the design and improve the power capability of batteries, successfully achieving model-driven optimization of ultrahigh-power LIBs.