Vehicle parameter identification using population based algorithms

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Gazi University Journal of Science Part A: Engineering and Innovation
Volume:3 Issue:2
Vehicle parameter identification using population based algorithms

Vehicle parameter identification using population based algorithms

Authors : Hakan GÖKDAĞ

Pages : 31-38

View : 67 | Download : 6

Publication Date : 2015-07-08

Article Type : Other Papers

Abstract :This work deals with parameter identification of a vehicle using population based algorithms such as Particle Swarm Optimization insert ignore into journalissuearticles values(PSO);, Artificial Bee Colony Optimization insert ignore into journalissuearticles values(ABC); and Genetic Algorithm insert ignore into journalissuearticles values(GA);. Full vehicle model with seven degree of freedom insert ignore into journalissuearticles values(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.
Keywords : Optimization, vehicle parameter identification, particle swarm, artificial bee colony

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