Multi-objective optimization method for thickness of anti-collision beam of automobile composite bumper

Abstract

The invention discloses a multi-objective optimization method for the thickness of an anti-collision beam of an automobile composite bumper, and the method comprises the following steps: 1, respectively determining the value ranges of the layer thickness of an upper plate, a lower plate, a front plate, a rear plate and a rib plate of the anti-collision beam, and the layer sequence corresponding to each layer thickness; 2, generating an initial sample data set, and determining an objective function f (x) and a constraint function g (x) of anti-collision beam paving layer thickness optimization; 3, according to the objective function and the constraint function, setting an initial parameter of a Gaussian random process kernel function, and training to obtain a GPR model; 4, obtaining a Pareto front solution set through a GPR model, screening out a new sample from the Pareto front solution set, and adding the new sample into the initial sample data set; and step 4, repeating the step 2 to the step 4 until the number of iterations is met, obtaining an optimized Pareto front solution set, and obtaining the optimized layer thickness of the upper plate, the lower plate, the front plate, the rear plate and the rib plate of the anti-collision beam according to the optimized Pareto front solution set.

Description

technical field

[0001] The invention belongs to the technical field of automobile passive safety research, in particular to a multi-objective optimization method for the thickness of an automobile composite material bumper anti-collision beam. Background technique

[0002] At present, multi-objective optimization is mostly based on the optimization method of the surrogate model. Before optimization, a surrogate model with sufficient accuracy must be established. Usually, the accuracy of the surrogate model can only be accurate and credible when the accuracy of the surrogate model reaches above 0.9. However, for high-dimensional and highly nonlinear mathematical models, such as car crashes, it is necessary to use hundreds or even thousands of groups of Design of Experiments (DOE) for simulation and simulation. The price is unbearable. In addition, most traditional proxy models do not directly reflect the uncertainty of the model, resulting in large deviations in the optimiza...

Examples

Embodiment Construction

[0039] The present invention will be further described in detail below in conjunction with the accompanying drawings, so that those skilled in the art can implement it with reference to the description.

[0040] The invention provides a multi-objective optimization method for the thickness of an automobile composite bumper anti-collision beam, and the specific process is as follows:

[0041] Such as figure 1 As shown, set the design variable x 1 represents the thickness of the anti-collision beam rear plate 110, x 2 represents the thickness of the front panel 120 of the anti-collision beam, x 3 Represents the thickness of the anti-collision beam rib 130, x 4 Represents the thickness of the lower plate 140 of the anti-collision beam, x 5 Represents the thickness of the upper plate 150 of the anti-collision beam, and defines the thickness of the upper and lower plates to be the same; the design variable adopts a discrete value method, and the value interval is 0.5.

[0042]...

technical field

[0001] The invention belongs to the technical field of automobile passive safety research, in particular to a multi-objective optimization method for the thickness of an automobile composite material bumper anti-collision beam. Background technique

[0002] At present, multi-objective optimization is mostly based on the optimization method of the surrogate model. Before optimization, a surrogate model with sufficient accuracy must be established. Usually, the accuracy of the surrogate model can only be accurate and credible when the accuracy of the surrogate model reaches above 0.9. However, for high-dimensional and highly nonlinear mathematical models, such as car crashes, it is necessary to use hundreds or even thousands of groups of Design of Experiments (DOE) for simulation and simulation. The price is unbearable. In addition, most traditional proxy models do not directly reflect the uncertainty of the model, resulting in large deviations in the optimiza...

Examples

Embodiment Construction

[0039] The present invention will be further described in detail below in conjunction with the accompanying drawings, so that those skilled in the art can implement it with reference to the description.

[0040] The invention provides a multi-objective optimization method for the thickness of an automobile composite bumper anti-collision beam, and the specific process is as follows:

[0041] Such as figure 1 As shown, set the design variable x 1 represents the thickness of the anti-collision beam rear plate 110, x 2 represents the thickness of the front panel 120 of the anti-collision beam, x 3 Represents the thickness of the anti-collision beam rib 130, x 4 Represents the thickness of the lower plate 140 of the anti-collision beam, x 5 Represents the thickness of the upper plate 150 of the anti-collision beam, and defines the thickness of the upper and lower plates to be the same; the design variable adopts a discrete value method, and the value interval is 0.5.

[0042]...

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