A Continuously Variable Transmission (CVT) provides a continuum of gear ratios between desired limits. CVT is a promising automotive technology and a sundry of models has been researched to realize the potential benefits of a CVT. CVT, being a highly nonlinear system, has a definite operating regime where it is able to maximize the torque transmission. The numerical model presented in this paper is difficult to solve because of its sensitivity with respect to the initial operating conditions such as initial belt tension, axial forces, and driven preload. The present research focuses on using Genetic Algorithms (GA) to identify these operating conditions and to understand the various dynamic interactions in a metal pushing V-belt CVT. This paper uses continuous Coulomb friction approximation theory to model friction between the belt and the pulleys. The computational scheme, the mathematical models, and the results corresponding to different loading scenarios are discussed.
Using Genetic Algorithms to Identify Initial Operating Conditions for a Transient CVT Model
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Srivastava, N, Blouin, VY, & Haque, IU. "Using Genetic Algorithms to Identify Initial Operating Conditions for a Transient CVT Model." Proceedings of the ASME 2004 International Mechanical Engineering Congress and Exposition. Dynamic Systems and Control, Parts A and B. Anaheim, California, USA. November 13–19, 2004. pp. 317-328. ASME. https://doi.org/10.1115/IMECE2004-61999
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