Optimization of a Double Wishbone Torsion Bar Spring Suspension System for a Hub Motor-Driven Vehicle

Abstract

This paper analyzes and optimizes the kinematics of a double-wishbone torsion bar suspension for in-wheel motor EVs, addressing performance degradation due to hard point changes. A parametric model was built in ADAMS/Car. Parallel wheel travel simulation generated curves for toe, camber, caster, and kingpin inclination angles versus wheel travel. Results showed the initial toe angle exceeded its ideal range, and the kingpin inclination failed to stay within the 7~13° design specification, indicating a need for optimization. Using Adams/Insight, sensitivity analysis identified the upper/lower control arm and tie rod inner hard points as critical. DOE and multi-objective optimization were applied to these hard points. Post-optimization results confirm effective improvement: caster angle variation was reduced by 35.9% with a 0.09° downward shift; kingpin inclination variation decreased by 13.6%, its minimum value increased by 0.42°, achieving a more desirable range. This work enhances suspension performance and delivers a systematic optimization method for similar suspension systems.