Multi-physics design optimization of structural battery

Abstract

Structural battery composite is a new class of multifunctional lightweight materials with profound potential in harvesting electrical energy in the form of chemical energy, while simultaneously providing structural integrity to the system. In this study, we present a multi-physics design optimization framework for structural battery. The objective of the optimization framework is to change the geometrical features and material types of the constituents in a composite lamina to maximize the allowable charging current for a constant rate of charging. In this optimization framework, three sets of inequality constraints are defined to keep the structural battery lightweight, and make sure that the amount of induced stress and generated heat due to the intercalation process remains small. We have also considered several design parameters such as geometrical features of the composite lamina, volume fractions of fibers and LiFePO4 particles, and material types of constituents. The proposed framework includes a gradient-based design optimization method with the ability to perform the optimization process under any source of uncertainty in the material properties, manufacturing process, operating conditions, etc. It also contains a Bayesian design optimization scheme to select the best candidate for the materials of the constituents in a structural battery. We also develop an analytical sensitivity analysis of several electrochemical/thermal/structural response metrics with respect to a few geometrical and material design parameters of a composite lamina. The results show that by using the proposed optimization framework, we are able to maximize the allowable charging current for a constant rate of charging in the optimized solution compared to the considered reference designs while satisfying all of the prescribed constraints. Furthermore, we increase the design reliability of structural battery by at least 45% compared to the deterministic optimized solution. Finally, we find the optimized material types for the fiber and matrix in a structural battery.