Multi-material additive manufacturing for lightweight automotive chassis components using topology optimization and hybrid material grading

Project Abstract

This study presents a comprehensive exploration of multi-material additive manufacturing (MMAM) for lightweight automotive chassis components through the integration of topology optimization and hybrid material grading. The research addresses the dual challenges of reducing vehicle mass while maintaining or enhancing structural performance, crash safety, and durability under real-world loading spectra. A hierarchical design framework is developed that couples geometric optimization with material distribution across multiple alloys and functionally graded materials (FGMs), enabling seamless transitions between stiffer, high-strength zones and compliant regions to mitigate stress concentrations and improve energy absorption during impact. The methodology begins with a parameterized finite element model of a representative chassis subassembly subjected to multi-axial load cases, including static, dynamic, and crash scenarios. Topology optimization is employed to identify optimal material layouts that minimize mass while satisfying stiffness, strength, and safety constraints. Concurrently, a material grading algorithm determines spatially varying material properties, leveraging graded Ti-6Al-4V, aluminum-centric alloys, and polymer-derived composites created via directed energy deposition and binder jetting processes. The integration of MMAM with topology optimization yields a hybrid lattice-shell configuration that leverages graded interfaces to reduce delamination risk and improve load transfer. A bespoke process–structure–property (PSP) model is developed to predict manufacturing-induced defects, residual stress, and thermal distortion, enabling design for additive manufacturing (DfAM) with reliable printability. Experimental validation includes manufactured test coupons and subcomponents produced on a multi-material AM platform, followed by mechanical testing to evaluate tensile strength, impact energy absorption, fatigue life, and stiffness. Nondestructive evaluation techniques, such as acoustic emission and high-resolution CT scanning, quantify internal flaws and material continuity across graded regions. A multi-objective optimization framework is used to balance mass reduction against structural performance metrics, crashworthiness, and manufacturing cost, producing a family of feasible designs tailored to different vehicle platforms and safety requirements. Life cycle assessment (LCA) and sensitivity analyses assess environmental impact and parameter robustness to variations in process parameters, material properties, and loading conditions. Key findings reveal that MMAM-enabled hybrid graded chassis components achieve substantial mass reductions (up to 25–35% in targeted subsystems) while maintaining or improving peak load capacity and energy absorption in crash simulations compared to conventional monolithic designs. The graded interfaces demonstrate improved strain distribution and reduced peak stresses, mitigating failure initiation sites. Process windows are established to minimize residual stresses and metallurgical incompatibilities between dissimilar materials, with best practices for orientation, deposition sequences, and post-processing treatments. The work offers a scalable design-and-manufacture paradigm for next-generation lightweight automotive structures, highlighting the potential for rapid customization, enhanced safety performance, and decreased lifecycle emissions through optimized material usage and additive manufacturing.

Project Overview

What This Project Is About

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A plain-language overview of the topic and what the project investigates.

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The Problem It Addresses

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What problem or gap this project tackles and why it matters to the field or society.

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Objectives of the Project

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1. Understand the basics of multi-material additive manufacturing and topology optimization. 2. Explore how combining different materials can reduce weight while maintaining strength. 3. Learn how to grade materials smoothly to improve performance and durability. 4. Develop a small-scale chassis component design and test its behavior virtually. 5. Assess sustainability and potential cost implications of the approach.

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What You Will Do Step by Step

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1. Gather foundational readings on additive manufacturing, topology optimization, and material grading. 2. Create simple, non-technical models of chassis parts to study weight and strength trade-offs. 3. Learn basic software tools for design, simulation, and optimization (with guided tutorials). 4. Run lightweight simulations to compare single-material vs multi-material designs. 5. Analyze results to identify practical design guidelines and limitations.

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Expected Outcome

A clear set of design principles for multi-material chassis parts, plus a basic optimized model and a short report describing benefits, trade-offs, and potential next steps.