Dynamic behavior and modeling of prismatic lithium‐ion battery

Abstract

Summary The inevitable vehicle collision has made the safety of lithium‐ion battery (LIB) carried by electric vehicles (EVs) a problem that restricts the further and large‐scale promotion of EVs. Therefore, establishing the numerical mechanics model of LIBs and studying their mechanical integrity are imperative. In this study, we design indentation, compression, and drop‐weight experiments for prismatic LIBs (PLIBs). Mechanical integrity and internal short circuit are analyzed in consideration of state of charge (SOC) and dynamic effects. A homogeneous PLIB model that considers anisotropic property, SOC, and dynamic effects is developed for the first time for application in different loading conditions. After its effectiveness is validated, the affecting parameters (ie, SOC and impact velocity) of the mechanical behaviors during dynamic loadings are investigated using the established model. The results show that strain rate effect and SOC state have impact on the mechanical properties of PLIB. However, the strain rate effect has much larger influence than the SOC state. Results may shed lights on the safety design of PLIBs in a mechanical aspect.

Homogenized pouch cell material modelling and a comparison study

“…Short circuit is observed at lower displacements compared to quasi‐static tests 8,9 . For prismatic lithium‐ion cells, at compression and indentation, strain rate dependence could affect battery cell response up to 3.5 times at compression and 2 times at indentation when compared to quasi‐static conditions 17 . For cylindrical lithium‐ion cells, difference lowers to 18% by loading speed at dynamic conditions 13 …”

“…8,9 For prismatic lithium-ion cells, at compression and indentation, strain rate dependence could affect battery cell response up to 3.5 times at compression and 2 times at indentation when compared to quasi-static conditions. 17 For cylindrical lithium-ion cells, difference lowers to 18% by loading speed at dynamic conditions. 13 Due to the lack of standard test procedures for battery cells, there is no universal method that characterizes the mechanical response of them.…”

Bayesian optimization algorithm‐based Gaussian process regression for in situ state of health prediction of minorly deformed lithium‐ion battery

“…Lithium‐ion batteries (LIBs) have become a relatively good battery type for electric vehicles (EV) due to their high voltage level, excellent cycle performance, no memory effect, low self‐discharge rate, high energy density, and other obvious advantages 1–3 . However, LIBs have some potential threats, such as their safety, consistency, and service life 4–6 .…”

Improved covariance matching—electrical equivalent modeling for accurate internal state characterization of packing lithium‐ion batteries

“…[36][37][38][39] As the internal battery parameters in the equivalent model cannot be measured online, they are supposed to be calculated indirectly through the experimental analysis, such as ohmic resistance, polarization resistance, and capacitance. [40][41][42] Therefore, the mathematical description could only be implemented by utilizing external measurable parameters, such as voltage, current, and temperature.…”