Development of a novel identification platform for automotive dampers Online publication date: Tue, 03-Mar-2015
by Jianguang Fang; Yunkai Gao; Guangyong Sun; Qing Li
International Journal of Vehicle Design (IJVD), Vol. 66, No. 3, 2014
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.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Vehicle Design (IJVD):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook