• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.2 s.173
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• pp.319-328
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• 2000

This paper presents a new design method of the 1 generation wheel bearing unit using a numerical optimization technique in order to increase bearing fatigue life. For calculating the fatigue life, a method of load analysis is studied on the automotive wheel bearing system. The design variables selected are ball size, initial contact angle, number of balls, pitch diameter, pre-load, and distance between ball centers. The method of feasible directions in ADS (Automated Design Synthesis) is utilized to automatically find the optimum design variables. To validate the design method, a computer program is developed and applied to a practical passenger car model. The optimum design results demonstrated the effectiveness of the proposed design method showing that the system life of the optimally designed wheel bearing unit is enhanced in comparison with that of the initial ones within the given available design space.

• Transactions of the Korean Society of Automotive Engineers
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• v.9 no.1
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• pp.122-130
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• 2001

In order to improve the efficiency of the design process and the quality of the resulting design, this study proposes a design method for determining design variables of an automotive wheel-bearing unit of double-row angular-contact ball bearing type by using a genetic algorithm. The desired performance of the wheel-bearing unit is to maximize system life while satisfying geometrical and operational constraints without enlarging mounting spae. The use of gradient-based optimization methods for the design of the unit is restricted because this design problem is characterized by the presence of discrete design variables such as the number of balls and standard ball diameter. Therefore, the design problem of rolling element bearings is a constrained discrete optimization problem. A genetic algorithm using real coding and dynamic mutation rate is used to efficiently find the optimum discrete design values. To effectively deal with the design constraints, a ranking method is suggested for constructing a fitness function in the genetic algorithm. A computer program is developed and applied to the design of a real wheel-bearing unit model to evaluate the proposed design method. Optimum design results demonstrate the effectiveness of the design method suggested in this study by showing that the system life of an optimally designed wheel-bearing unit is enhanced in comparison with that of the current design without any constraint violations.