Research on active steering control strategy based on sideslip angle estimation for a steering‐by‐wire forklift

Abstract

Taking the TFC35 electric forklift as the research object, we analyze the movements and forces of the forklift in three directions: yaw, lateral movement, and roll. Combined with the load transfer formula of the forklift and the nonlinear and linear tire model, the formula for lateral force of the four tires of forklift is deduced, and the nonlinear and linear three‐degree‐of‐freedom (3DOF) forklift dynamics model is established. Because the sideslip angle of the forklift is not easy to measure directly, based on the linear 3DOF forklift model, we take the yaw rate and lateral angle as the observation variables and consider the influence of model error. An adaptive Kalman filter is designed to estimate the sideslip angle of the forklift. In order to improve the accuracy of estimation, an online optimization strategy of the adaptive Kalman filter based on genetic algorithm with an adaptive factor is proposed. Simulation results show the effectiveness of the proposed method. In combination with the forklift reference model, the rear wheel angle of the forklift is corrected by comprehensive proportional feedback of yaw rate and the sideslip angle, and the active steering system for a steering‐by‐wire forklift is designed. Simulation and test results show that the control strategy of forklift's active steering system can improve its driving stability and handling performance. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.