Simulated Annealing Solver of Power Steering System Based Neural Network

According to different turning energy the steering system can be divided into mechanical steering system and power steering system. Power steering system is increasingly widespread in various vehicles, and has become one of important component in modern automobile steering system. The objective function may be specified that the volume of tooth corona of worm gear in power steering system incline to minimum, so the optimization model including the property and boundary constraints is created. Then the objective function with penalty terms is converted by penalty strategy with addition type, so as to transform the constrained optimization into the unconstrained optimization model. Considering the problem of low efficiency and local optimum caused by standard optimization methods, the simulated annealing algorithm is adopted to solve the optimization model of power steering systems, and neural network method is applied to fit relative coefficient, and BFGS Quasi-Newton method is recalled automatically when the setting working precision is achieved again. So that the optimization process is simplified and global optimum is acquired reliably.