Rigid-flexible Hybrid Tolerance Analysis of EV Batteries with Weighted Objective Function of Assembly

Abstract The multi-component stacked assembly of EV batteries has the characteristic of rigid-flexible hybrids between contact surfaces, such as aerogel thermal insulation pads, which challenges assembly quality control of large-scale and high-speed manufacturing. This manuscript proposes an approach using the Weighted Objective Function of Assembly (WFA) to solve the hybrid assembly problem. In order to predict the interface contact state of the rigid-flexible hybrid assembly, the approach considers the distance constraint, the interference constraints and the equilibrium equation to transform the rigid-flexible hybrid assembly problem into a weighted optimization problem. The target dimension distribution is obtained by leveraging an enhanced genetic algorithm, which combines the elite retention strategy and the targeted gene mutation method. Moreover, the WFA model can be applied not only to consider the dimensional tolerance and the flexible deformation during the assembly process, but also to carry out coupling analysis under different loading conditions. The accuracy and efficiency of the proposed method are exhibited through an industrial case study of battery stacked assembly. While maintaining computational accuracy, a significant reduction in time costs is achieved, making it applicable for dimensional distribution predictions that rely on Monte Carlo simulations. The proposed WFA method can be applied to support the design and prediction of battery stacked assembly or other rigid-flexible coupled assembly.