According to lithium battery pack equalization control algorithm, this paper proposes a novel control scheme for lithium battery pack that can realize energy equalization. The design of fuzzy-PI is represented in detail, including the controller’s inputs and outputs, fuzzy logic rules base and the set of PI parameters. PI control is introduced into fuzzy control to form fuzzy-PI control, which integrates the advantage including fast response of fuzzy-PI, having no steady-state static error of PI and so on, the equalization efficiency and precision are improved. Experimental results show that this scheme can improve the problem that the control precision of fuzzy control application is poor in battery charging and discharging energy equilibrium process, and realize more efficient equalization.
Aiming at the coupling relationship among electronic equipment’s feature parameters, a hybrid Support Vector Regression(SVR) based fault prediction model is proposed in the paper, both the time relativity and space relativity of the feature parameter are taken into account, and it designes the algorithm process of hybrid SVR which improves the prediction accuracy by fusing the vertical historical state data and the horizontal correlation parameter together, applying D-S evidence theory. Experimental results show that, compared with vertical SVR or horizontal SVR, the proposed method is more accurate, and is capable of performing fault prognosis on the complicated electronic equipment effectively.
The point cloud normal vector calculation is sensitive to distribution density, and the calculation error is big in sharp border presently. In order to solve this problem a method of normal vector calculation based on Self Organization Map(SOM) is presented. The geometrical and topological information on scattered point cloud are employed to estimate the normal vector. A sphere SOM is trained to approximate the sampled surface with triangular meshes. Point cloud is clustered on the nodes of SOM, after that plane fitted by the k-neighbor points gives an estimation of the point normal. And the estimated point cloud normal vectors are aligned by adjusting patch normal. Experimental results show that the relative error is less than 0.08 and the standard deviation is 0.009. The method has high calculation precision.
For the universal adapter problem between Enterprise Digital Rights Management(E-DRM) system and reader software which is caused by wide ranges of them, this paper proposes an E-DRM universal adapter model. This model is high level hierarchical abstraction of E-DRM system and reader software, and completes unified management of rights by right control level. The model implements lasting security by monitor of reader and priority management of levels. Experimental result shows this model has good universal adaptation ability and lasting security.