Joint Estimation of Driving State and Road Adhesion Coefficient for Distributed Drive Electric Vehicle

Obtaining accurate vehicle driving state and road adhesion coefficient information is of great significance to many aspects the vehicle. This paper takes distributed drive electric vehicles as research object designs a joint estimation method based on theory federated-cubature Kalman filter. The corresponding nonlinear three-degree-of-freedom dynamics model established space equation obtained. Multi-source fusion low-cost sensor signals carried out by using technology, an algorithm estimator built theory. Select typical experimental conditions apply Simulink build co-simulate with CarSim for verification. results show that proposed can improve accuracy stability estimation.