Optimization of Worm Gear Drive for Improving Efficiency Using RCGA

Efficiency is one of the critical issues in designing of worm gear drive with high transmission ratio. Relative sliding motion between the worm gear drives causes reduction in efficiency. Further, unfavorable condition developed due to poor lubrication leads to more friction between the meshing gears. Thus, solving these problems increases the mechanical efficiency as well as the thermal efficiency of gears. Resistance to bending strength, contact strength, contact ratio and deflection along with thermal stability are the design constraints for the proposed mathematical model. This chapter aims at minimizing the power loss in worm gear mechanism using real-coded genetic algorithm (RCGA). A comparison of results obtained using evolutionary optimization algorithms with the experimental findings from the literature is performed for validation. It shows that there is an improvement in overall worm gear efficiency with reduced power loss.