Undergraduate Capstone Project

Design & Fabrication of ATV Suspension

Optimizing vehicle dynamics for the SAE BAJA competition using Lotus Shark, SolidWorks, and ANSYS.

Motivation & Objectives

The SAE BAJA competition challenges engineering students to design and build an All-Terrain Vehicle (ATV) capable of surviving severe punishment on rough terrain. The tracks include rock crawls, steep gradients, and suspension-shattering drops.

The core motivation was to move beyond a simple "survival" design to a performance-oriented system. We needed to maximize the contact patch of the tire during cornering (handling) and minimize the unsprung mass (acceleration), while adhering to strict rulebook constraints regarding width and safety. The objective was to design a Double Wishbone system that decouples vertical wheel motion from camber changes, offering superior tunability over MacPherson struts.

Methodology

01

Kinematic Design

Using Lotus Shark software, we iteratively adjusted hardpoint locations (chassis and knuckle points).

  • Target: < 0.5° Bump Steer
  • Target: Negative Camber gain in bump
  • Optimization of Roll Center height
02

CAD Modeling

3D modeling in SolidWorks. Designed custom knuckles to accommodate the specific KPI and Caster angles derived from kinematics.

  • Clearance checks for steering (Ackermann)
  • Shock mounting for 0.7 Motion Ratio
  • Parametric design for quick edits
03

FEA & Fabrication

Static structural analysis in ANSYS. Material selected: AISI 4130 (Chromoly) for its high strength-to-weight ratio.

  • Load Case: 3G Bump (Vertical)
  • Load Case: 1G Braking + 1G Cornering
  • TIG Welding for final assembly

Theoretical Framework

Ride Frequency ($f_n$)

We selected a higher natural frequency for the rear to ensure pitch stability over bumps (flat ride concept).

$$ f_n = \frac{1}{2\pi} \sqrt{\frac{K_{ride}}{M_{sprung}}} $$

Spring Rate Calculation

The spring rate ($K_s$) is derived from the wheel rate ($K_w$) and the motion ratio ($MR$) squared.

$$ K_{s} = \frac{K_{w}}{(MR)^2} = \frac{4\pi^2 f_n^2 M_{sprung}}{(MR)^2} $$

Results: Kinematic Optimization

The graph below illustrates our optimized Camber Gain. As the suspension compresses (positive travel), the camber becomes more negative. This is critical: as the car rolls in a turn, the outside tire (which carries the load) loses camber relative to the chassis. By designing camber recovery into the geometry, we keep the tire flat on the ground.

Optimized Design
Standard Baseline

Detailed Project Report

Access the full documentation including calculation sheets, complete BOM, cost analysis, and detailed DVP (Design Validation Plan).

Read Full Report

Applications & Impact

The principles of kinematics applied here are not limited to racing. They are critical in:

  • Military Tactical Vehicles: Where terrain adaptability is a matter of survival.
  • Planetary Rovers: Where independent suspension allows traversal of unknown alien topography.

The project achieved a 15% weight reduction in unsprung mass compared to the previous iteration, directly improving acceleration and suspension response.

References

  • [1] Milliken, W.F. & Milliken, D.L. (1995). Race Car Vehicle Dynamics. SAE International.
  • [2] Smith, Carroll. (1978). Tune to Win. Aero Publishers.
  • [3] Gokhale, N. et al. (2008). Practical Finite Element Analysis. Finite To Infinite.