Hybrid Genetic Algorithm Optimization of Vehicle Major Reducer

The function of vehicle major reducer is to increase the input torque and decrease rotational speed correspondingly. The performance parameters of major reducer can greatly affect the dynamics and economy of vehicle, therefore it is very important to optimize the vehicle major reducer. Considered the boundary and performance constraints, the objective function is specified to create optimization model of vehicle major reducer. Global algorithms are known for their slower convergence to the true global optimum once the optimum region is found. This drawback of the genetic algorithm can be overcome by combining it with local gradient-based algorithms, which are known for their faster convergence. The results demonstrate that the hybrid approach is an effective tool to deal with the uncertainties present in design optimization and can provide more realistic solutions. So that the optimization process is simplified and global optimum is acquired reliably.