Parameter influence law analysis and optimal design of a dual mass flywheel

• Published in: International Journal of Mechanical System Dynamics Vol. 2; no. 2; pp. 165 - 177
• Main Authors: Wu, Guangqiang, Zhao, Guoqiang
• Format: Journal Article
• Language: English
• Published: Nanjing Wiley 01.06.2022; John Wiley & Sons, Inc
• Subjects: Configuration management; Design analysis; Design optimization; Design parameters; dual mass flywheel; Flywheels; Genetic algorithms; Inertia; Mechanical engineering and machinery; Moments of inertia; multiobjective optimization; multiobjective particle swarm optimization; Multiple objective analysis; nondominated sorting genetic algorithm based on an elite strategy; Particle swarm optimization; Powertrain; Resonant frequencies; Sorting algorithms; Systems engineering; TA168; Test vehicles; TJ1-1570; vehicle powertrain system; Vehicles; Vibration analysis; Vibration control; Vibration damping; Wheels
• ISSN: 2767-1399; 2767-1402; 2767-1402
• DOI: 10.1002/msd2.12046

The influence of the dynamic parameters of a dual mass flywheel (DMF) on its vibration reduction performance is analyzed, and several optimization algorithms are used to carry out multiobjective DMF optimization design. First, the vehicle powertrain system is modeled according to the parameter configuration of the test vehicle. The accuracy of the model is verified by comparing the simulation data with the test results. Then, the model is used to analyze the influence of the moment of inertia ratio, torsional stiffness, and damping in reducing DMF vibration. The speed fluctuation amplitude at the transmission input shaft and the natural frequency of the vehicle are taken as the optimization objectives. The passive selection method, multiobjective particle swarm optimization, and the nondominated sorting genetic algorithm based on an elite strategy are used to carry out DMF multiobjective optimization design. The advantages and disadvantages of these algorithms are evaluated, and the best optimization algorithm is selected.