Authors: Jianguang Fang; Yunkai Gao; Guangyong Sun; Qing Li
Addresses: School of Automotive Studies, Tongji University, 4800 Cao'an Road Shanghai, 201804, China ' School of Automotive Studies, Tongji University, 4800 Cao'an Road Shanghai, 201804, China ' State Key Laboratory of Advanced Design and Manufacture for Vehicle Body, Hunan University, 1 Yuelu Mountain, Changsha, 410082, China ' School of Aerospace, Mechanical and Mechatronic Engineering, The University of Sydney, 160 City Road, Darlington, Sydney, NSW 2006, Australia
Abstract: Traditional approaches with manual regulation of damping parameters could often be too difficult to yield correct parameters due to high nonlinearity and cross effects between different parameters involved. To tackle the problem, this paper proposes a new approach to the identification of the damping parameters for a shock absorber. In this approach, the parameter identification is modelled as an optimisation problem, in which the discrepancy between simulation and test curves is formulated as the objective function and the damping parameters to be identified are regarded as design variables. The kriging model is updated iteratively and an optimum is sought by the particle swarm optimisation (PSO) algorithm until convergence. The effectiveness and robustness of the proposed platform is validated by correlating the simulation results obtained from the identified damping parameters to the corresponding experimental results in the case of a full vehicle.
Keywords: vehicle dampers; vehicle dynamics; parameter identification; sequential sampling; PSO; particle swarm optimisation; damping parameters; shock absorbers; vehicle vibration; kriging; modelling; simulation.
International Journal of Vehicle Design, 2014 Vol.66 No.3, pp.272 - 296
Available online: 09 Nov 2014 *Full-text access for editors Access for subscribers Purchase this article Comment on this article