No abstract

The accuracy of battery state of charge (SOC) is crucial for solving the problems such as overcharge, overdischarge, and mileage anxiety of electric vehicle power battery. In this study, an SOC estimation method using a hybrid method (HM) based on threshold switching is proposed, which combines the advantages of the extended Kalman filter (EKF) and the ampere hour integration (AHI) to improve the estimation accuracy and convergence speed. First, the parameters of the second-order RC equivalent model are identified using the least square. Then, the equation of EKF for updating the state variable is reconstructed by using the identified parameters to solve the problem of multiple iterations caused by the uncertainty of the initial value. Finally, the difference between the estimated voltage and the sampling voltage is used as the threshold value for switching between the AHI and the EKF to estimate the SOC of the battery. Simulation results show that the estimated SOC error of the proposed algorithm is less than 1.6% and the convergence time is within 70 s. Experiments under different SOC initial values are carried out to prove the advantages of the proposed method.

Resolvers are widely used in electric vehicles, trains, and other harsh fields because of their robustness. However, the resolver outputs two orthogonal analog signals, which make the resolver decoding either high hardware cost or poor decoding accuracy. A noise robust resolver decoding method using Hilbert transform and angle-tracking observer (ATO) is proposed in this paper. Firstly, Hilbert transform is employed to obtain the modular envelopes of resolver signals. Next, the modular envelopes are filtered, and their quadrants are recognized by the polarity relation of the resolver signals and the modular envelope extreme point. Then, the ideal demodulating signals are gained through the linearization of the envelope zero point. Finally, the improved ATO is used to obtain the rotor angle by iteratively calculating the demodulating signal. The effectiveness of the proposed method is verified by experiments under various rotor speed conditions and compared with other methods in noise immunity. The results show that the proposed method can control the decoding error within 0.5° when the SNR is 30 dB, which provides a high-precision and low-cost decoding scheme for practical applications.