A fuzzy sensor fusion sideslip angle estimation algorithm combining inertial measurements with GPS data

The implementation of vehicle safety control systems in modern cars requires accurate vehicle dynamic state estimation. The estimation of the vehicle sideslip angle is essential to improve the performance of current and future Electronic Stability Control (ESC) systems. An innovative approach to estimate the sideslip angle directly from GPS measurements is developed. Given an existent kinematic sideslip estimator, with solved numerical integration issues during straight line driving, a GPS drift-free sideslip estimate improves such kinematic sideslip angle estimate during steady-state cornering conditions. As both methods do not require any tire-road friction nor other vehicle parameters, the two estimators are fused together using a Fuzzy Logic approach. Both require only basic sensors: wheel speeds, Inertial Measurement Unit (IMU) measurements, steering angle, and GPS module. Extensive experimental validation is used to assess the quality of the developed estimators and their robustness to a wide range of driving scenarios.