Road roughness estimation using an improved Kalman filter with discrete trapezoidal load

Accurate estimation of road roughness is crucial for vehicle dynamics analysis and road performance evaluation. To enhance the accuracy of estimating road roughness, this study introduces an estimation method utilizing the improved Kalman filter (KF) with discrete trapezoidal load. Firstly, the theoretical formulation of the vehicle response under road roughness load is derived, and the system equation is derived in a continuous time state-space form. Next, the vehicle system equation is discretized and an improved KF algorithm with trapezoidal load is proposed, along with the derivation of the structural state estimation formula. Then, a vehicle model with seven degrees of freedom (DOFs) is established for numerical calculation, with the improved KF algorithm is utilized to estimate road roughness based on the vehicle response. Finally, the estimation accuracy of the proposed method is verified via field tests involving the vehicle driving through bumps and driving on a rough road.