Design and Multi-Objective Kinematic Optimization of 3D Double Wishbone Suspensions Using an Ensemble Optimization Technique

The kinematic behavior of automotive suspension systems, particularly the dynamic control of camber and caster angles, is paramount to achieving desired vehicle handling, stability, and safety characteristics. However, designing complex multi-body systems like the double wishbone suspension presents a high-dimensional, non-linear optimization problem where conventional algorithms are susceptible to premature convergence to suboptimal local minima. This paper introduces a novel, two-stage stacking ensemble optimization framework to overcome this limitation. The underlying kinematic model, including loop-closure and geometric feasibility constraints, is systematically derived using a symbolic mathematics approach to ensure high fidelity and eliminate formulation errors. Through a comparative analysis, the proposed ensemble method is shown to demonstrably outperform standard individual algorithms—Sequential Quadratic Programming (SQP), Interior-Point, and Active-Set—in solution accuracy. The optimized geometry achieves sub-millidegree root-mean-square error in tracking predefined target curves for both camber and caster throughout the suspension's travel. The results validate that this hybrid framework provides a more robust and reliable methodology for the high-fidelity synthesis of complex mechanical systems, offering a powerful tool for modern vehicle design.