Pure electric vehicle frame lightweight method based on nonlinear programming

Abstract

The invention discloses a pure electric vehicle frame lightweight method based on nonlinear programming. The method comprises the following steps of S1, establishing a finite element model of a frame;S2, determining an optimized objective function and an optimized design variable, and solving a mathematical expression of the objective function by means of the Hypermesh software; S3, determining an optimized constraint condition, and collecting the sample data of each constraint response; S4, processing the sample data, performing function fitting on each constraint response by using a second-order response surface model, and solving an approximate agent model of each constraint; and S5, constructing a nonlinear programming model by using the agent model of each constraint and the mathematical expression of the objective function, and solving the optimization model. According to the method, by adopting the nonlinear programming model, and using the Lingo software for solving and optimizing, the optimal solution can be obtained within the extremely short time, and the optimization efficiency is greatly improved. The optimization method has the characteristics of simple principle, high solution rate, high optimization precision and the like.

Description

technical field [0001] The invention belongs to the field of lightweight design of a pure electric vehicle frame, in particular to a method for lightweighting a pure electric vehicle frame based on nonlinear programming. Background technique [0002] The lightweight of electric vehicles is to reduce the total mass of electric vehicles on the premise of ensuring that the passive safety, handling stability, ride comfort, NVH performance and structural strength of the whole vehicle are not affected. Since the frame bears most of the weight of the vehicle and is an important part of the vehicle, the vehicle has high requirements on the structural strength of the frame. The frame also accounts for a relatively large proportion of the weight of the vehicle. The weight reduction of the frame is the focus of reducing the weight of the vehicle and plays a very important role in the weight reduction of the vehicle. The lightweight design of pure electric vehicles in the early stage c...

AI Technical Summary

Problems solved by technology

The current frame lightweight methods mostly use the optimization method combining approximate surrogate model and genetic algorithm, ant colony algorithm, and neural network. This method requires repeated iterative solutions, which is time-consuming and has a large solution error.

Moreover, the existing lightweight methods based on finite element simulation all lighten the frame under one or two simple typical working conditions. These simple typical working conditions are quite different from the actual working conditions. The result of light weight of the frame has a large error

In summary, the current research on frame lightweighting lacks an accurate and efficient optimization method that considers multiple working conditions

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