Year: 2015
Type: article
Abstract: This work deals with parameter identification of a vehicle using population based algorithms such as Particle Swarm Optimization (PSO), Artificial Bee Colony Optimization (ABC) and Genetic Algorithm (GA). Full vehicle model with seven degree of freedom (DoF) is employed, and two objective functions based on reference and computed responses are proposed. Solving the optimization problem vehicle mass, moments of inertia and vehicle center of gravity parameters, which are necessary for later applications such as vehicle control and performance analysis, are obtained. It is demonstrated the proposed approach achieves to determine unknown parameters with negligible relative errors in spite of noise interference.
Source: DergiPark (Istanbul University)
Author: Hakan Gökdağ
Institution: Bursa Technical University
Language: English
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2397719797