Differential steering control strategy of distributed hybrid all-terrain vehicles based on improved genetic algorithm optimization

Aiming at the steer-by-wire systems of wheel-driven electric vehicles, this study designs an output torque distribution factor of fuzzy control rule base, with steering wheel angle and vehicle speed used as inputs. An improved genetic algorithm is used to solve the optimal fuzzy rule table of a fuzzy logic controller. To avoid steering danger and consider steering sensitivity, the yaw rate difference is introduced, and a fuzzy controller is established with a torque distribution factor. On the basis of the dynamic correction factor, a drive-by-wire control strategy that is suitable for high and low-speed conditions is proposed. Simulation and test results demonstrate that the yaw rate difference-modified differential steering control strategy based on an improved genetic algorithm can reduce driving and in-situ steering radius by 12.26% and 9.3%, respectively, while considering steering sensitivity and steering stability.