Multi-parameter and multi-objective optimisation of articulated monorail vehicle system dynamics using genetic algorithm

ABSTRACT

In some researches of vehicle system dynamics, it’s necessary to optimise various of vehicle parameters to meet the requirements of different objectives. In this paper, an articulated monorail dynamic model together with a genetic algorithm is developed to optimise the curving dynamics of the articulated monorail vehicle. The articulated monorail is modelled as a rigid multi-body dynamic model consisting of six car bodies and seven straddle-type bogies, in which each straddle-type bogie is comprised of two driving wheels, four guide wheels and two stable wheels. The Magic tire model is used to model the nonlinearities in the driving wheels, guide wheels and stable wheels. The validity of the proposed monorail vehicle model is demonstrated through comparing the car body acceleration responses with those obtained in a field test. The genetic algorithm considering 50 individuals and the mutation probability of 0.01 is developed and further combined with the monorail vehicle dynamic model to serve as a multi-parameters and objective optimisation platform. This optimisation platform is employed to optimise the suspension parameters in the monorail vehicle to improve the ride comfort of the vehicle and minimise the wheel unload, overturning coefficients and wear generation in the tire.

KEYWORDS:

• Articulated monorail
• vehicle dynamic performance
• genetic algorithm
• multi-parameter and multi-objective optimisation

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Key R&D Program of China on Research on the key technology of bogie [grant number 2016YFB1200506].