Lithium-ion battery equalization control method

Abstract

The present invention discloses a lithium-ion battery equalization control method. The method comprises the following steps: (1) determining the evaluation index of battery consistency, and establishing the analysis sequence of m batteries; (2) employing a standardization Euclidean distance formula to calculate the standardization Euclidean distance values of any two batteries to obtain a matrix G; (3) converting the matrix G to obtain an m-row and m-column similarity matrix Wm*m; (4) calculating a diagonal matrix Dm*m; (5) calculating a Laplace matrix; (6) employing an Nomarlized cut method to form normalization processing of the Laplace matrix to obtain a matrix L; (7) obtaining a low-dimensional characteristic matrix E=[e1, ..., ek]; (8) obtaining a battery classification solution; and (9) performing equalization of batteries in a pack with the least number of batteries in the clustering through an equalization module. The lithium-ion battery equalization control method can realize fast making of an equalization scheme and reasonable control of the equalization process, and is suitable for the real-time online equalization of a battery system.

Description

technical field [0001] The invention relates to the technical field of lithium-ion battery balancing, in particular to a method for controlling the balancing of lithium-ion battery packs. Background technique [0002] At present, lithium-ion batteries for large-scale energy storage need to be used in series in groups. In order to maximize the use of battery energy, an energy balancing system must be equipped to improve the consistency of single batteries. Currently, the battery pack equalization control methods commonly used are mostly based on the battery voltage for equalization control, and the equalization effect is poor, and there are false equalization defects. The core of the design of the balance control method is to solve the problem of how to classify the batteries. In fact, battery classification needs to consider various battery state parameters that reflect battery characteristics such as voltage, state of charge, and energy state. Clustering algorithm is an e...

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Problems solved by technology

Clustering algorithm is an effective means to solve the classification problem, but the general clustering algorithm such as K-means clustering algorithm is easy to fall into local extremum when the algorithm is executed, and the global optimal solution cannot be obtained.

Moreover, for multidimensional data, general clustering methods are not easy to handle

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