Linear Quadratic Regulator Control of Vehicle Active Front Steering Considering Aerodynamic Characteristics

This study enhanced the handling stability and driving safety of a special vehicle by developing a vehicle dynamics model using TruckSim 2019. An ideal two-degree-of-freedom vehicle model was established using Simulink. The reference yaw rate and vehicle sideslip angle were derived from the reference model. Fluent simulations were performed on the vehicle to obtain the aerodynamic coefficients as functions of the relative inflow angle. These relationships were fitted to functional expressions and integrated into the aerodynamic module of TruckSim, replacing the default coefficient curves and improving the accuracy of the subsequent simulations. To improve steering performance, an active front steering (AFS) controller based on the linear quadratic regulator (LQR) algorithm was designed, and an AFS control strategy based on sensor feedback was implemented using MATLAB/Simulink 2021b. Finally, simulations were performed to validate the effectiveness of the controller, which showed that under continuous sinusoidal steering, the controller regulated the vehicle. By applying a front-wheel steering angle computed using the LQR algorithm, the actual yaw rate and vehicle sideslip angle closely tracked the reference values. Using the LQR algorithm, the vehicle achieved improved steering performance and a stable body attitude under crosswinds. Thus, the LQR algorithm enhanced the handling stability and driving safety of the vehicle.