Crashworthiness and Lightweight Design Optimization of Electric Vehicle Components Using Finite Element Analysis

Assessment 

Introduction

International initiatives to achieve environmentally friendly transportation have boosted the use and implementation of Electric Vehicles (EVs). Although EVs come with a wide range of ecological benefits, the unique architectural design of these vehicles poses new technical difficulties, especially in the field of structural design and construction. Increased driving range can only be achieved by reducing the mass of the vehicle, but this process requires very high crash resistance to protect occupants and the energy storage system, which is a large, high-voltage battery pack. Therefore, the pursuit of light weight and crashworthiness often involves competing performance requirements. Physical prototypes and full-scale crash tests are traditionally used to validate the product empirically and are time-consuming and expensive. The automotive industry is responding by using more computational methods, the most prominent of which is Finite Element Analysis (FEA). Finding a solution to the challenge of lightweight materials and safety performance, FEA aims to fill the gap between the emerging materials and the safety performance by enabling engineers to simulate complex crash conditions, predict material behavior, and optimize structural design in a virtual environment. The successful implementation of this study can help to reduce prototyping costs and shorter design cycles in the faster development of future EVs that are safer and more energy efficient at the same time.

Scope of the Project

This thesis focuses on a particular, essential structural element: the B-pillar. This research is defined by the following primary objectives:

• Crashworthiness Analysis: To examine the structural performance of the B-pillar during a side-impact collision, emphasizing the optimization of energy absorption and the reduction of incursion into the passenger and battery compartments.
• Lightweight Design: To engineer and enhance a multi-material B-pillar using innovative lightweight materials, Carbon Fiber Reinforced Polymers (CFRPs) and Fiber Metal Laminates (FMLs), aimed at minimizing total mass while maintaining structural integrity.
• Progressive Failure Prediction: To utilize sophisticated progressive damage models, such as the Hashin and Puck criteria, to accurately predict the failure mechanisms (e.g., fiber breakage, delamination) of the composite materials, providing a more realistic and predictive simulation than traditional models.
• Occupant Safety Metrics: To link the structural performance of the B-pillar directly to occupant safety by incorporating a virtual crash dummy and evaluating key injury metrics, thereby ensuring that structural optimization also translates to enhanced occupant protection.

This project will employ a purely computational approach, using FEA software, to achieve these objectives and demonstrate the feasibility of designing an optimized EV component that excels in both lightweight and crashworthiness performance.

Structure of the Report

This interim report is structured to provide a comprehensive overview of the project's foundation, progress, and future plan.

• Section 1: Introduction: This section introduces the project's background, motivation, and scope. 
• Section 2: Literature Review: This section synthesizes recent developments in EV structural design, lightweight materials, composite failure modeling, and occupant safety assessments, emphasizing the need to bridge component-level performance with injury prediction. 
• Section 3: Research Question and Project Plan: This section defines the project’s aim—to develop a lightweight, crash-optimized B-pillar using advanced composites and hybrid materials. It outlines the suggested solution and experimental approach, presents a project timeframe, and addresses the essential resources and skill enhancement needed. 
• Section 4: Project Dependent Preparations: Details of training, early findings from baseline model construction, and a thorough risk assessment are all part of the foundational groundwork documented in this section.

Literature Review

Overview of Crashworthiness in Electric Vehicles

Crashworthiness in electric vehicles (EVs) is not merely a design consideration but a fundamental challenge shaped by the need to safeguard large, sensitive battery systems. Unlike internal combustion engine vehicles, EVs introduce unique structural burdens due to the considerable mass and fragility of high-voltage battery packs. While traditional structural frameworks are being adapted, many current approaches underestimate the complexity of integrating both occupant and battery protection without imposing significant weight penalties [1, 2]. The emphasis on limiting structural intrusion often overlooks trade-offs between structural rigidity and energy absorption efficiency, particularly under high-impact scenarios [3]. Although carbon fiber-reinforced composites are frequently promoted for their superior strength-to-weight ratios, their crash performance remains insufficiently validated in dynamic impact environments, especially in large-scale battery enclosures [4]. Moreover, while Finite Element Analysis (FEA) is widely employed for predicting crash responses, its reliance on idealized boundary conditions raises concerns about its robustness in simulating real-world crash complexities [5].

Importance of Crashworthiness in EVs

In the context of EV design, crashworthiness extends beyond occupant safety to encompass the critical integrity of battery packs. While the risks of thermal runaway and electric arcing in side or underride collisions are wellacknowledged, many current design strategies inadequately address the localized impact dynamics that trigger such failures [6]. A design methodology based on simulation and experimental validation is necessary for the optimization of EV structures. It is worthwhile to note that, in the case of advanced composite materials, especially Kabilan Suresh Kumar, Thesis Progress Report 6 CFRP, numerical modeling can provide one with a complete idea of complicated failure mechanisms that are very difficult to characterize experimentally.experimentally.

Assessment Summary and Mentor-Guided Approach

The assessment required the student to prepare a research-based report focusing on the crashworthiness and lightweight design optimization of Electric Vehicle (EV) components using Finite Element Analysis (FEA). The key objective was to critically analyze and simulate the structural performance, material optimization, and occupant safety in EV design — particularly emphasizing the B-pillar structure during side-impact collisions.

The assessment tasks were organized into multiple sections, each serving a unique purpose:

• Introduction: Explain the background, need, and motivation behind lightweight and crashworthy EV structures.
• Literature Review: Analyze recent research on EV crashworthiness, lightweight materials (like CFRP and FML), and progressive failure prediction models.
• Research Question and Project Plan: Define the study’s aim, proposed methodology, simulation tools, and timeline.
• Project-Dependent Preparations: Document preliminary simulations, baseline model construction, training requirements, and risk assessment strategies.

The expected outcome was a computationally validated research plan that demonstrates how FEA-based simulations can improve both safety and weight efficiency in EV component design, aligning with sustainability and innovation goals in automotive engineering.

Step-by-Step Academic Mentor Guidance and Approach

The academic mentor guided the student through a structured and analytical process to ensure each section was developed methodically and aligned with academic research standards.

Step 1: Understanding the Core Objective

The mentor first discussed the importance of linking theory to real-world application — in this case, how lightweight design principles intersect with safety requirements in EVs. The student was guided to define a clear problem statement: achieving the optimal balance between vehicle mass reduction and structural integrity under crash conditions.

Step 2: Structuring the Introduction

In this phase, the mentor helped the student contextualize the study, emphasizing the relevance of sustainable transport innovations, battery safety, and engineering design trade-offs. The introduction was refined to clearly articulate the rationale behind using Finite Element Analysis (FEA) as a simulation-based approach to replace traditional, costly crash testing.

Step 3: Conducting the Literature Review

The mentor provided stepwise guidance on conducting a targeted literature review — focusing on:

• Recent developments in EV structural design and composite materials,
• Theoretical and computational approaches in crashworthiness analysis, and
• Integration of occupant safety metrics using virtual crash dummy models.
  The student was also advised to critically evaluate existing research limitations, such as boundary condition assumptions in FEA or gaps in material failure validation.

Step 4: Formulating the Research Question and Plan

Under mentor supervision, the student refined the research aim to focus on developing a multi-material B-pillar using CFRP and FMLs, assessed through progressive damage models like Hashin and Puck criteria. The mentor guided the creation of a project timeline, outlining simulation phases, data collection points, and model validation steps.

Step 5: Preparing Project Dependencies

The mentor ensured the student completed essential preparatory steps, including:

• Familiarization with the FEA software tools,
• Establishing baseline models for comparison, and
• Conducting a risk assessment related to data accuracy and simulation limitations.
  This stage emphasized research integrity, safety protocols, and adherence to engineering ethics.

Final Outcome and Learning Achievements

Through this guided process, the student successfully:

• Developed a comprehensive understanding of FEA in EV design optimization,
• Identified and evaluated key material and structural parameters affecting crash performance,
• Demonstrated the ability to translate theoretical knowledge into computational simulation, and
• Aligned the project outcomes with sustainability, safety, and innovation objectives in engineering practice.

The learning objectives achieved through this assessment included:

• CLO1: Applying engineering and analytical reasoning to solve modern EV design challenges.
• CLO2: Evaluating complex systems using computational tools like FEA.
• CLO3: Integrating safety and material optimization principles into real-world engineering contexts.
• CLO4: Developing research, critical thinking, and documentation skills aligned with professional engineering standards.

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