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MULTI-OBJECTIVE PARAMETER OPTIMIZATION OF SYNCHRONIZER BASED ON IMPROVED PARTICLE SWARM OPTIMIZATION ALGORITHM
To meet the requirements of shorter synchronization time and higher life for the synchronizer in transmission, mathematical models aiming at synchronization time and synchronizer life were established separately based on Newton’s second law and adhesive wear theory, M-B fractal contact model. The evaluation function was constructed by ideal point method to establish a multi-objective parameter optimization model with the two objectives. Using the AHP to determine weight value of the target in the multi-objective optimization model, and using the improved particle swarm algorithm to optimize the multi-objective parameter optimization model. The results show that the synchronization time is reduced by 8% and the synchronizer life is increased by 9% compared with that before optimization, the two objectives are improved better. The using of the improved particle swarm algorithm improves the performance of the synchronizer, and the application of the ideal point method effectively avoids the problem that the high order of magnitude dominates the multi-objective optimization.
MULTI-OBJECTIVE PARAMETER OPTIMIZATION OF SYNCHRONIZER BASED ON IMPROVED PARTICLE SWARM OPTIMIZATION ALGORITHM
To meet the requirements of shorter synchronization time and higher life for the synchronizer in transmission, mathematical models aiming at synchronization time and synchronizer life were established separately based on Newton’s second law and adhesive wear theory, M-B fractal contact model. The evaluation function was constructed by ideal point method to establish a multi-objective parameter optimization model with the two objectives. Using the AHP to determine weight value of the target in the multi-objective optimization model, and using the improved particle swarm algorithm to optimize the multi-objective parameter optimization model. The results show that the synchronization time is reduced by 8% and the synchronizer life is increased by 9% compared with that before optimization, the two objectives are improved better. The using of the improved particle swarm algorithm improves the performance of the synchronizer, and the application of the ideal point method effectively avoids the problem that the high order of magnitude dominates the multi-objective optimization.
MULTI-OBJECTIVE PARAMETER OPTIMIZATION OF SYNCHRONIZER BASED ON IMPROVED PARTICLE SWARM OPTIMIZATION ALGORITHM
WANG ChunHua (author) / GUO ZhiWei (author)
2019
Article (Journal)
Electronic Resource
Unknown
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