A Multi-Stage Topology Optimization Approach for Lightweight Automotive Upright Design

Lightweight structural design is a critical objective in automotive engineering, particularly for suspension components that directly influence unsprung mass and vehicle dynamics. Although topology optimization is widely used to achieve high stiffness-to-weight ratios, conventional approaches are often limited by single-objective formulations or by a lack of geometric interpretability in multi-objective solutions. This study proposes a multi-stage topology optimization framework for the conceptual design of an automotive suspension upright. The methodology decouples stiffness-driven and stress-driven optimization processes and introduces a parametric synthesis stage in which key structural features from both solutions are systematically integrated into a geometrically interpretable design. The framework is evaluated on a Formula SAE front upright under representative braking and cornering load conditions. The resulting hybrid configuration achieves a 29.44% reduction in mass (from 616.9 g to 435.3 g) while maintaining structural performance, with a maximum von Mises stress of 220.0 MPa, a safety factor of 2.28, and a maximum deformation of 0.88 mm. The results demonstrate that the proposed approach enables a balanced integration of stiffness and stress criteria through feature-based design synthesis. Beyond numerical performance, the methodology provides a reproducible and interpretable workflow that bridges topology optimization and practical engineering design.

Authors

Institutions

Publication Details

Journal
Applied Sciences
Published
2026-04-27
DOI
https://doi.org/10.3390/app16094257
Primary Topic
Topology Optimization in Engineering
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Multi-Stage Topology Optimization Approach for Lightweight Automotive Upright Design

Jorge Yusef Colín-Castillo, Erik Rosado-Tamariz, Carlos D. Garcia-Beltran, Alfonso Campos-Amezcua et al.
Applied Sciences
Topology Optimization in Engineering
article

A Multi-Stage Topology Optimization Approach for Lightweight Automotive Upright Design

Jorge Yusef Colín-Castillo, Erik Rosado-Tamariz, Carlos D. Garcia-Beltran, Alfonso Campos-Amezcua, Rene Davila-De-La-Peña, Rafael Campos-Amezcua
article en

Abstract

Lightweight structural design is a critical objective in automotive engineering, particularly for suspension components that directly influence unsprung mass and vehicle dynamics. Although topology optimization is widely used to achieve high stiffness-to-weight ratios, conventional approaches are often limited by single-objective formulations or by a lack of geometric interpretability in multi-objective solutions. This study proposes a multi-stage topology optimization framework for the conceptual design of an automotive suspension upright. The methodology decouples stiffness-driven and stress-driven optimization processes and introduces a parametric synthesis stage in which key structural features from both solutions are systematically integrated into a geometrically interpretable design. The framework is evaluated on a Formula SAE front upright under representative braking and cornering load conditions. The resulting hybrid configuration achieves a 29.44% reduction in mass (from 616.9 g to 435.3 g) while maintaining structural performance, with a maximum von Mises stress of 220.0 MPa, a safety factor of 2.28, and a maximum deformation of 0.88 mm. The results demonstrate that the proposed approach enables a balanced integration of stiffness and stress criteria through feature-based design synthesis. Beyond numerical performance, the methodology provides a reproducible and interpretable workflow that bridges topology optimization and practical engineering design.

Applied SciencesVol. 16(9)
Centro Nacional de Investigación y Desarrollo Tecnológico (MX), Instituto Nacional de Electricidad y Energías Limpias (MX), Technological University of Mexico (MX)
Affordable and clean energy
Openalex Percentile: Top 7%
Topology Optimization in Engineering
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.