Ride comfort optimization of a multi-axle heavy motorized wheel dump truck based on virtual and real prototype experiment integrated Kriging model

• Published in: Advances in mechanical engineering 2015-06, Vol.7 (6), p.1
• Main Authors: Gong, Bian, Guo, Xuexun, Hu, Sanbao, Xu, Lin
• Format: Article
• Language: English
• Subjects: Automotive parts; CAE; Complexity; Computer aided engineering; Computer simulation; Computers; Damping; Design engineering; Design of experiments; Dump trucks; Genetic algorithms; Hydraulic equipment; International conferences; Kriging interpolation; Optimization; Passenger comfort; Performance evaluation; Roads & highways; Suspension systems; Vehicle wheels
• ISSN: 1687-8132; 1687-8140
• DOI: 10.1177/1687814015584257

The optimization of hydro-pneumatic suspension parameters of a multi-axle heavy motorized wheel dump truck is carried out based on virtual and real prototype experiment integrated Kriging model in this article. The root mean square of vertical vibration acceleration, in the center of sprung mass, is assigned as the optimization objective. The constraints are the natural frequency, the working stroke, and the dynamic load of wheels. The suspension structure for the truck is the adjustable hydro-pneumatic suspension with ideal vehicle nonlinear characteristics, integrated with elastic and damping elements. Also, the hydraulic systems of two adjacent hydro-pneumatic suspension are interconnected. Considering the high complexity of the engineering model, a novel kind of meta-model called virtual and real prototype experiment integrated Kriging is proposed in this article. The interpolation principle and the construction of virtual and real prototype experiment integrated Kriging model were elucidated. Being different from traditional Kriging, virtual and real prototype experiment integrated Kriging combines the respective advantages of actual test and Computer Aided Engineering simulation. Based on the virtual and real prototype experiment integrated Kriging model, the optimization results, obtained by experimental verification, showed significant improvement in the ride comfort by 12.48% for front suspension and 11.79% for rear suspension. Compared with traditional Kriging, the optimization effect was improved by 3.05% and 3.38% respectively. Virtual and real prototype experiment integrated Kriging provides an effective way to approach the optimal solution for the optimization of high-complexity engineering problems.