New Hybrid Genetic Algorithm for Pitch Sequence Optimization of CVT Variator Chain

Paper #:
  • 2017-01-1120

  • 2017-03-28
  • 10.4271/2017-01-1120
Tsutsumi, K., Miura, Y., Kageyama, Y., and Miyauchi, A., "New Hybrid Genetic Algorithm for Pitch Sequence Optimization of CVT Variator Chain," SAE Int. J. Veh. Dyn., Stab., and NVH 1(2):137-144, 2017, doi:10.4271/2017-01-1120.
A CVT variator chain system is superior in transmission efficiency to a belt system because of its lower internal friction. However, a chain produces more noise than a belt due to the long pitch length of contact between the pulleys and rocker pins. This study focuses on optimization of the pitch sequence for reducing chain noise. The previous pitch sequence was suitably combined of links of different lengths to improve noise dispersibility for reducing chain noise. First, the object function was defined as the reduction of the peak level of 1st-order chain noise combined with a well-balanced the levels on the low and high frequency sides. Interior background noise consisting of road noise and wind noise have the characteristic that they increase as the frequency decreases. Therefore, the object function was aimed at reducing the peak level of 1st-order chain noise by shifting the chain noise energy from the vicinity of the 1st-order band to the low frequency side in consideration of the masking effect of low-frequency background noise. Next, clustering clarified the characteristics of the pitch sequence design space as a multimodal space. Finally, “Hybrid genetic algorithm”, combining a genetic algorithm and local search was developed in order to search widely and deeply in the multimodal space for global optimal solutions. Hybrid-GA found global optimal solutions from a very large design space of 380 patterns. This pitch sequence was reduced the peak level of 1st-order chain noise by 2.8 dB compared with that of the previous pitch sequence.
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