Evaluating multifunctional efficiency of a structural battery composite via thermo-electro-chemical modelling

The emerging research field of structural batteries aims to combine the functions of load bearing and energy storage to improve system-level energy storage in battery-powered vehicles and consumer products. Structural batteries, when implemented in electric vehicles, will be exposed to greater temperature fluctuations than conventional batteries in EVs. However, there is a lack of published data regarding how these thermal boundary conditions impact power capabilities of the structural batteries. To fill this gap, the present work simulates transient temperature-dependent specific power capabilities of high aspect ratio structural battery composite by solving one-dimensional heat transfer equation with heat source and convective boundary conditions. Equivalent circuit modeling of resistivity-induced losses is used with a second-order finite difference method to examine battery performance. More than 60 different run configurations are evaluated, examining how thermal boundary conditions and internal heat influence power capabilities and multifunctional efficiency of the structural battery. The simulated structural battery composite is shown to have good specific Young’s modulus (79.5 to 80.3% of aluminum), a specific energy of 158 Wh/kg, and specific power of 41.2 to 55.2 W/kg, providing a multifunctional efficiency of 1.15 to 1.17 depending on configuration and thermal loading conditions and demonstrating the potential of load-bearing structural batteries to achieve mass savings. This work emphasizes the dependency of power efficiency on cell design and external environmental conditions. Insulating material is shown to improve multifunctional efficiency, particularly for low ambient temperatures. It is demonstrated that as cell temperature increases due to high ambient temperature or heat generation in the battery, the specific power efficiency increases exponentially due to a favorable nonlinear relation between ionic conductivity and cell temperature. The simulations also demonstrate a thermal feedback loop where resistivity-induced power losses can lead to self-regulation of cell temperature. This effect reduces run-averaged losses, particularly at low ambient temperature.