Variable steering ratio design and handling stability research for steer-by-wire forklift

Abstract

For the TFC35 steer-by-wire forklift, a linear 3-degree-of-freedom forklift model is given, which provides a verification model for variable steering ratio design. The concept of ideal steering ratio is expounded. The variable steering ratio algorithm based on constant yaw rate gain and the variable steering ratio algorithm based on constant lateral acceleration gain are studied. A variable steering ratio algorithm based on two kinds of gain combination is proposed. The advantages and disadvantages of the above three static variable steering ratio algorithms based on constant gain are simulated and analyzed. Aiming at complex working conditions, a dynamic variable steering ratio control scheme based on fuzzy neural network is proposed. The definition, implementation steps, and adjustment algorithms of each layer of fuzzy neural network are given. The final experiment results show that the dynamic variable steering ratio method based on fuzzy neural network is more resistant to the disturbance of its own parameters and can be used in complex dynamic conditions, which helps to improve the handling stability of the forklift.