Co-simulation study on stability control strategy for super-high-speed vehicles under crosswind

To mitigate crosswind-induced lateral and yaw instability in super-high-speed vehicles, this study develops a CFD-calibrated aerodynamic feedforward model predictive control (MPC) strategy. Conventional ESP and many existing MPC-based crosswind controllers compensate for wind effects mainly through feedback after vehicle-state deviations occur. In contrast, the proposed framework converts aerodynamic yaw angle into lateral force and yaw moment through offline CFD calibration and embeds these loads into the MPC prediction model as feedforward disturbance terms. The aerodynamic coefficient map is generated using ANSYS Fluent and coupled with a Simulink MPC controller and a nonlinear four-wheel CarSim vehicle model for closed-loop verification. Under the sea-crossing bridge scenario at 180 km/h and a 30 m/s crosswind, the uncontrolled vehicle exhibits a lane departure greater than 30 m. Conventional ESP limits the deviation to approximately 2.0 m but requires about 6 s to converge and produces residual oscillations. The proposed controller restricts the peak lateral displacement to 0.44 m, reduces the peak yaw rate by 74.3% relative to ESP, and lowers peak braking pressure by 69%. These results indicate that CFD-informed feedforward prediction can improve anticipatory yaw-stability control while reducing actuator demand under severe crosswind excitation.