An Enhanced CMM Model for the Accurate Prediction of Steady-State Performance of CVT Chain Drives

Author:

Carbone G.1,De Novellis L.2,Commissaris G.3,Steinbuch M.4

Affiliation:

1. Dipartimento di Ingegneria Meccanica e Gestionale, Politecnico di Bari, viale Japigia 182, 70126 Bari, Italy

2. Dipartimento di Ingegneria Meccanica e Gestionale, Politecnico di Bari, v.le Japigia 182, 70126 Bari, Italy; Department of Mechanical Engineering, Eindhoven University of Technology, Den Dolech 2, 5612 AZ Eindhoven, The Netherlands

3. Gear Chain Industrial b.v., De Huufkes 104, 5674 TM Nuenen, The Netherlands

4. Department of Mechanical Engineering, Eindhoven University of Technology, Den Dolech 2, 5612 AZ Eindhoven, The Netherlands

Abstract

The paper deals with the theoretical and experimental evaluation of the performance of a continuously variable transmission chain drive in steady-state conditions. We propose an enhanced version of the Carbone–Mangialardi–Mantriota (CMM) model, to accurately predict the slip behavior and the traction performance of the variator. To achieve this objective, it is necessary to accurately estimate the elastic displacements of the pulley. The determination of the actual pulley deformation allows to obtain a better estimation of the sliding velocities between the pins and the pulley surfaces and, therefore, to calculate the amount of total slip between the primary and secondary pulleys with a higher degree of accuracy. In contrast to multibody models, the approach presented here has a very simple formulation and results in an easy implementation, which allows a complete and fast evaluation of the variator working points. The theoretical results are discussed and critically compared with experimental data. The comparison confirms the validity of the CMM approach in a large range of clamping forces, speed ratios and torque loads.

Publisher

ASME International

Subject

Computer Graphics and Computer-Aided Design,Computer Science Applications,Mechanical Engineering,Mechanics of Materials

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