Automobile side collision optimization design method based on coevolution algorithm

Through a collaborative evolution algorithm, multi-objective optimization model is constructed, combined with occupant injury, vehicle body deformation and weight models, the problems of multi-objective and complex constraints in vehicle side collision design are solved, and an optimized design solution that meets safety and performance requirements are generated.

CN120296877APending Publication Date: 2025-07-11XI'AN POLYTECHNIC UNIVERSITY
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Patent Information

Application Number
CN202510392130.2
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-03-31
Publication Date
2025-07-11

AI Technical Summary

Technical Problem

The existing automotive side collision optimization design methods are difficult to ensure safety performance while taking into account the lightweight, cost control and manufacturability of the body structure, and traditional methods are difficult to deal with multiple complex constraints.

Method used

A multi-objective optimization design method based on co-evolution algorithm is adopted to construct occupant injury model, vehicle body deformation model and weight model. Combined with co-evolution algorithm, it is optimized to the unconstrained Pareto frontier through dual-population co-evolution and dynamic archive updates, and handle multi-objective and complex constraints.

Benefits of technology

It realizes the balance of global and local search in side collisions of cars, generates optimized design solutions that meet actual requirements, meet multiple requirements such as safety, performance and weight, and provides more reliable and diverse solutions.

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Abstract

The invention discloses a coevolution algorithm-based automobile side collision optimization design method, which comprises the following steps of: firstly, constructing a passenger injury model, an automobile body structure deformation model and an automobile body weight model based on an injury mechanism in a collision accident, and providing a basis for subsequent optimization; through a multi-objective optimization model, objectives of passenger safety, a vehicle body structure, lightweight design and the like are considered, and strict constraint conditions are set. And a coevolution algorithm is utilized, and coevolution of the main population and the auxiliary population is combined. By combining the constraint processing technology, it is ensured that the design scheme meets the actual collision safety requirement. And finally, through optimization, an optimal automobile structure design scheme which not only meets the safety requirement but also has good performance can be output.
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