Development of simulation approach for CVT tuning using dual level genetic algorithm

Presented work aims to develop Genetic Algorithm (GA) based simulation approach for tuning of Continuously Variable Transmission (CVT). This study uses force balance to model the behaviour of CVT in MATLAB and employs dual level GA to optimize the tuning variables for desired output from CVT i.e. engagement of belt and sheaves at peak of engine torque curve, start of shifting at peak of engine power curve and keeping constant engine RPM (peak of power curve) during shifting. The variables for tuning are flyweight mass, primary and secondary spring stiffness and profile of primary and secondary cam. The results obtained from simulation are validated through experimental testing. The simulation results show good coherence with experiments in terms of engagement and shift starting RPM and also most of the shifting occurs at constant RPM. Also, the behaviour of CVT tuned by simulation is compared with the traditional method of experimental tuning and results obtained show that the simulation method is comparable to the traditional method in terms of accuracy. This study concludes with strong confidence in the potential of GA simulations for tuning.