The research on battery SOC estimation within first-order Markov process

State of Charge(SOC) of batteries is one of the most important and the most difficult estimated parameters in battery management Kalman filtering algorithm is widely applied to the battery SOC estimation, but the premise of the application of Kalman filter is that the system model is accurate and system noise is white noise. For the problem that current measurements of electric cars are easily influenced by colored noise interference under the complicated conditions, this thesis focuses on studying the affects which the algorithm based on Extended Kalman Filter (EKF) puts on the battery SOC estimation value, influencing by colored noise in First-order Markov process.