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SolidWorks MATLAB FEA Vehicle Dynamics GD&T

Suspension Geometry Optimisation — Formula Student Car

Full suspension geometry analysis and optimisation for a Formula Student race car using SolidWorks and MATLAB, achieving a 14% reduction in body roll and improved cornering performance.

Suspension Geometry Optimisation — Formula Student Car screenshot

Overview

This project involved the complete design, analysis, and optimisation of the suspension system for a Formula Student single-seater race car. The goal was to maximise cornering grip and minimise body roll while keeping the assembly within strict weight and packaging constraints.

Key Outcomes

  • 14% reduction in body roll compared to the baseline geometry
  • Improved camber curve — maintained optimal tyre contact patch through full suspension travel
  • Weight reduction of 1.2 kg through topology-optimised uprights
  • Validated against FSAE rulebook packaging constraints

Methodology

1. Geometry Definition

Defined wishbone pickup points and kingpin geometry in SolidWorks. Iterated on roll centre height, anti-dive, and anti-squat percentages using kinematic analysis.

2. Kinematic Simulation

Used MATLAB to script a kinematic solver that swept the suspension through ±50 mm of travel, plotting camber gain, toe change, and roll centre migration.

Parameter Target Achieved
Roll Centre Height 25–40 mm 32 mm
Camber Gain ≥ 0.8°/° 0.95°/°
Anti-dive 20–30% 26%
Body Roll (1g) < 1.5° 1.2°

3. Structural FEA

Performed static and fatigue FEA on the wishbone tubes and uprights using ANSYS Structural. Applied worst-case load cases (3g bump, 2g cornering).

  • Material: 4130 Chromoly steel (wishbones), 6061-T6 aluminium (uprights)
  • Safety factor: 2.5 minimum on all structural members
  • Max von Mises stress: 187 MPa (well below yield of 460 MPa)

4. Manufacturing

Produced detailed engineering drawings with full GD&T callouts. Components were CNC-machined and TIG-welded in-house.

Lessons Learned

Balancing kinematic performance against manufacturability was the biggest challenge. The optimal geometry from simulation had tight tolerances on the pickup points that were difficult to achieve with the available tooling — requiring a design compromise that still hit all performance targets.