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：In order to improve the control performance of distributed drive electric vehicle (EV) a more comprehensive vehicle state and parameter estimation method is proposed. For the problem that it is difficult to measure the vehicle states and parameters in real time, the distributed EV is considered as the object, and a method of vehicle states and parameters estimation based on unscented Kalman filter (UKF) is discussed. Firstly, the 7-DOF time-varying parameter vehicle model is established; secondly, taking the longitudinal acceleration, lateral acceleration, yaw angular velocity and wheel speed which are easy to be measured as the measured variables, a combined observer of vehicle states and system parameters is designed using the UKF algorithm to estimate longitudinal velocity, lateral velocity, lateral tire forces, vehicle mass, center position and inertia moment by extending the dimension of state variables. Finally, the combined observer is simulated and analyzed on Simulink/Carsim platform. The results show that the observer can estimate vehicle state and system parameters effectively, and has a good convergence effect.

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