Process–Structure Co-Optimization of Glass Fiber-Reinforced Polymer Automotive Front-End Module

TL;DR

This paper introduces a co-optimization method for glass fiber-reinforced polymer automotive parts to improve structural performance and reduce manufacturing defects.

Contribution

A novel process–structure co-optimization approach for GFRP components is proposed, integrating simulation and experimental validation.

Findings

Topology optimization reduced displacement at latch mounting points from 2.254 mm to 1.609 mm.

Optimized process parameters reduced warpage by 41.5%, achieving 1.498 mm.

Mapped injection molding simulations showed high accuracy with low relative error and variance compared to experiments.

Abstract

For automotive GFRP structural components, beyond structural design, the warpage, residual stress/strain, and fiber orientation inevitably induced during the injection molding process significantly compromise their service performance. These factors also diminish the reliability of performance assessments. Thus, it is imperative to develop a process–structure co-optimization approach for GFRP components. In this paper, the performance of a front-end module is evaluated through topological structure design, injection molding process optimization, and simulation with mapped injection molding history, followed by experimental validation and analysis. Under ±1000 N loading, the initial design shows excessive displacement at the latch mounting points (2.254 mm vs. <2.0 mm limit), which is reduced to 1.609 mm after topology optimization. By employing a sequential valve control system, the controls of the melt line and fiber orientation are is superior to thatose of conventional gating systems. The optimal process parameter combination is determined through orthogonal experiments, reducing the warpage to 1.498 mm with a 41.5% reduction compared to the average warpage of the orthogonal tests. The simulation results incorporating injection molding data mapping (fiber orientation, residual stress–strain) show closer agreement with experimental measurements. When the measured displacement exceeded 0.65 mm, the average relative error Er, range R, and variance s2 between the experimental results and mapped simulations were 11.78%, 14%, and 0.002462, respectively, validating the engineering applicability of this method. The methodology and workflow can provide methodological support for the design and performance assessment of GFRP automotive body structures, which enhances structural rigidity, improves control over injection molding process defects, and elevates the reliability of performance evaluation.

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