Search Results (2)

This study employs four metaheuristic optimization methods to optimize the dimensional synthesis of Ackermann steering mechanisms for three-axle, six-wheeled vehicles with front-axle steering mode and reverse-phase steering mode. The employed optimization methods include Particle Swarm Optimization (PSO), Hybrid Particle Swarm Optimization (HPSO), Differential Evolution with golden ratio (DE-gr), and Linearly Ensemble of Parameters and Mutation Strategies in Differential Evolution (L-EPSDE). With a front-wheel steering angle range of 70 degrees, two hundred optimization experiments were conducted for each method, and statistical analyses revealed that DE-gr and L-EPSDE methods outperformed PSO and HPSO methods in terms of standard deviation, mean value, and minimum error. These two methods exhibited superior convergence stability, faster convergence, and higher accuracy compared to PSO and HPSO. Reverse-phase (K = 1) steering mode outperformed front-axle steering mode, delivering reduced steering errors and turning radii. Considering the transmission ratio of front to rear axle (K) as a design variable in reverse-phase steering mode increased design flexibility and significantly lowered steering errors for the front and rear axle steering mechanisms. However, this comes with a slight increase in the turning radius of the vehicle’s front part compared to when K = 1. The optimized mechanism, designed using the DE-gr method, was validated through kinematic simulations and steering analyses using MSC-ADAMS v2015 software, further confirming the effectiveness and reliability of the proposed design. Full article

Surface initiated rolling contact fatigue (RCF), mainly characterized by cracks and material stripping, is a common type of damage to turnout rails, which can not only shorten service life of turnout but also lead to poor running safety of vehicle. The rail surface initiated RCF of turnouts is caused by a long-term accumulation, the size and distribution of which are related to the dynamic parameters of the complicated vehicle-turnout system. In order to simulate the accumulation of rail damage, some random samples of dynamic parameters significantly influencing it should be input. Based on the three-level unreplicated saturated factorial design, according to the evaluation methods of H, P and B statistic values, six dynamic parameters that influence the rail surface initiated RCF in turnouts, namely running speed of vehicle, axle load, wheel-rail profiles, integral vertical track stiffness and wheel-rail friction coefficient, are obtained by selecting 13 dynamic parameters significantly influencing the dynamic vehicle-turnout interaction as the analysis factors, considering four dynamic response results, i.e., the normal wheel-rail contact force, longitudinal creep force, lateral creep force and wheel-rail contact patch area as the observed parameters. In addition, the rail surface initiated RCF behavior in turnouts under different wheel-rail creep conditions is analyzed, considering the relative motion of stock/switch rails. The results show that the rail surface initiated RCF is mainly caused by the tangential stress being high under small creep conditions, the normal and tangential stresses being high under large creep conditions, and the normal stress being high under pure spin creep conditions. Full article