Multi-material Structural Optimization And Lightweight Design Of Vehicle Power Battery Pack

The battery cells,modules,electrical components and management system are arranged in limited space of power battery pack,which need to operate safely under complex vehicle working conditions.So structural design for battery pack must meet a variety of performance requirements,such as resisting structural deformation,avoiding resonance damage,vibration shock and collision safety.At the same time,the weight of battery pack accounts for near 20% of entire vehicle,which restricts the driving mileage of the electric car and improvement of vehicle performance.The ideal battery pack's structural design should meet various performance requirements and minimize weight.The combination of multi-material design and structural optimization is an effective way.However,battery pack has complex structure and highly non-linear performance,resulting in a long optimization process and low design efficiency.Researching on multi-material structural optimization and lightweight design of battery pack has high practical value for improving design efficiency and lightweight level of power battery pack.After summarizing structural design's tasks and lightweight approaches of battery pack's different design stages,it's found that the detailed design stage of battery pack's structural design is a key link to meet structural performance requirements.The comprehensive use of various lightweight materials and structural extreme designs can effectively improve battery pack's lightweight level.To this end,battery pack's structural performance requirements and index evaluation methods are summarized.Battery pack's multi-material structural optimization process method under performance constraints is established.Battery pack's lightweight structural design system with different performance weights is established.Lightweight design of a vehicle power battery pack is combined with structural design under dynamic and static characteristics.First,a finite element model of battery pack is established,verified using modal tests.The structural strength and deformation of battery pack under static limit load conditions,low-order modal characteristics and lightweight level are analyzed.Battery pack's performance indicators are established,which provide support for performance constraints.Then,use sensitivity analysis to select components that have a significant effect on battery pack's performance as design variables,and use the optimal Latin hypercube test design to obtain a sample data set of combination schemes of material and structure of battery pack.Support Vector Machines has features of small sample learning and high-dimensional non-linear prediction with high accuracy,which is introduced into prediction of battery pack's performance response to replace the time-consuming finite element analysis,improving optimization efficiency.Using the genetic algorithm optimize the support vector machine's parameters to obtain best prediction accuracy.Finally,a optimization model of battery pack's material and structure under multiple performance constraints is established.The NSGA-II algorithm is used to optimize the multiperformance Pareto set.The Pareto set is ranked based on grey correlation analysis to obtain battery pack's structure under different performance priorities.Optimizing battery pack's mass and deformation under low-order modal constraints achieve a weight reduction of 10.5kg without reducing performance of battery pack.Compared with original structure,the weight reduction rate is 29.1%,and battery pack integration efficiency is improved by 4.1%.Researching on battery pack's multi-material structural optimization method and establishing battery pack's lightweight structural design under multiple performance constraints provides a reference for improving structural reliability and lightweight of power battery packs.