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In order to estimate the state of charge (SOC) for mine-used battery exactly and real-time, the weighted statistical linear regre esion method was used to achieve the linearization of model function, and the technique of sampling points Kalman filter was applied to the state of charge estimation for mine-used battery. Aiming at the limited resource of the battery management system, the nonlinear filtering algorithm that combined standard Kalman filter and sampling point Kalman filter was proposed based on the linear characteristic of the state equation and the nonlinear characteristic of the observation equation of the battery model. In order to achieve the strong tracing ability of forced condition and the robustnees of the model inaccuracy, the singular value decomposition was introduced, and the eeror covariance matrix was replaced by the characteristic covariance matrix, and suboptimal fading factor was introduced based on the principile of strong tracing. The simulation results indicate that the state of charge estimation algorithm based on improved sampling point Kalman filter for mine-used battery takes the filtering accuracy and the amount of computation into account, and has the strong tracing ability to deal with the forced condition and the robustness to deal with the inaccuracy of model, and is totally applicable to the state of charge estimation for mine-used battery whose resource is limited. Therefore, the new algorithm has good practical value. [ABSTRACT FROM AUTHOR]

To enhance the robustness and accuracy of the calculation, the treatment method for preconditioned characteristic boundary and preconditioned backflow boundarys are derived from the characteristics of preconditioned Euler equations. The preconditioned boundary treatment methods are obtained from the characteristic relation of preconditioned Euler equations, and in subsonic inlet and outlet boundaries, the backflow boundary treatment methods are acquired from the characteristic equations. Through numerical simulation, it is found that the backflow boundary treatment method converges more than 1.5 times faster, while the computational accuracy is similar to SIMPLE method; in the calculation of outlet with backflow, its pressure error is 68.3% lower than Fluent software. Thus the preconditioned backflow boundary treatment method has higher accuracy and better robustness, and is valuable in practical engineering calculation. [ABSTRACT FROM AUTHOR]