WIT Press


An Integrated Model For Crankshaft Optimal Design

Price

Free (open access)

Volume

80

Pages

9

Published

2005

Size

466 kb

Paper DOI

10.2495/OP050291

Copyright

WIT Press

Author(s)

A. M. Shariff & N. K. Jha

Abstract

A computational capability is developed for the optimal design of a crankshaft to satisfy deflection, fatigue, vibration, and balancing requirements using 3-D modelling and finite element analysis. The model shape is optimised based on the results of the mathematical programming used to find the minimum weight of the crankshaft. The optimal results are compared for geometric programming and the GRG program. The finite element analysis predicts deflection, principal stresses, shear stresses and fatigue life. All of these values are below the critical value. Keywords: optimal design, crankshaft, geometric programming, generalised reduced gradient, solid modelling, finite element method, sum of squares of error. 1 Introduction Today’s automotive industries are faced with a number of issues, which require them to be responsive in order to be competitive. To be competitive, one has to produce components with low cost and high quality. The advent of high performance computers, CAD tools and Optimisation techniques has helped realize the demand of global market. With the help of Optimisation techniques and numerical methods, one can design a component, create a solid model using CAD tools, simulate the operating conditions and find out if the component meets the expectations and feasibility before starting the actual production, thereby saving time and resources. The general considerations [1] in designing a crankshaft are; type of loads and stresses caused by it, selection of material, motion of parts or kinematics of the crankshaft, form and size of parts, convenient and economical features like minimization of wear, and use of standard parts. Failure of the Crankshaft will result in the failure of the engine. A

Keywords

optimal design, crankshaft, geometric programming, generalised reduced gradient, solid modelling, finite element method, sum of squares of error.