Vehicle sideslip angle observation based on SF-ADKF considering signal delay for electro-mechanical-brake system

Electro-mechanical-brake (EMB) system is an important safe component of intelligent vehicles. Accurate and reliable vehicle sideslip angle is the key signal of lateral stability control in EMB system. Hence, a shadow following and adaptive double Kalman filter fusion (SF-ADKF) method considering signal delay is proposed, which improve accuracy of the vehicle sideslip angle observation. On the basis of the seven-degree-of-freedom model of the vehicle, magic formula is added to construct the dynamic framework. Then, considering signal delay SF-ADKF is introduced, including a shadow following algorithm and adaptive double Kalman filter algorithm to observe vehicle sideslip angle. Finally, the vehicle sideslip angle is applied to the lateral stability control of EMB. Both simulation and experimental results show that this method improve the accuracy of vehicle sideslip angle observation and the lateral stability control performance. The error under SFADKF is reduced by 37.5% compared with normal control, which effectively improve the driving safety.