Method for estimating residual capacity of batteries in battery management systems
A technology of battery remaining capacity and battery management system, applied in the direction of measuring electrical variables, measuring electricity, measuring devices, etc., can solve the problems of inaccurate SOC and low precision, and achieve the effect of reducing accumulated errors
Inactive Publication Date: 2018-02-13
CHINA UNIV OF MINING & TECH +1
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Problems solved by technology
[0003] The purpose of the present invention is to provide a method for estimating the battery remaining capacity in the battery management system, to solve the inaccuracy of the SOC estimated by the ampere-hour integral method, and the accuracy of the extended Kalman filter algorithm in the process of gradually increasing or decreasing the SOC. will become less and less problematic
Method used
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Embodiment 1
[0031] Embodiment 1 is a battery management system based on a ternary lithium battery. The structure of the battery pack is 8 in parallel and 12 in series, 8 batteries in parallel are a group, the capacity of each battery is 3.4AH, and the capacity of each battery pack is 27.2AH. The object of SOC estimation is 12 battery packs. The ampere-hour integration method used in the process is shown in formula (1),
[0032]
[0033] where C N is the battery capacity, and η is the charge-discharge efficiency. In this example C N =27.2AH, η=1.
[0034] The battery model used by the EKF algorithm in this example is as follows figure 1 shown. For the battery model, the state equation and output equation of the extended Kalman filter algorithm are shown in equations (2) to (3). then according to figure 2 The EKF algorithm flow shown can calculate the EKF algorithm estimation result S of each battery pack 1 .
[0035]
[0036] U(k)=U oc (k)-U 1 (k)-U 2 (k)-R 0 I(k) (3) ...
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The invention discloses a method for estimating residual capacity of batteries in battery management systems, and belongs to methods for estimating residual capacity of batteries. The method includessimultaneously referring to Extended Kalman Filter (EKF) algorithms and ampere-hour integral processes; processing results S1 of the EKF algorithms and results S2 of the ampere-hour integral processesto obtain ultimate estimated values S of SOC (state of charge). The method has the advantages that values of the ampere-hour integral processes are repeatedly updated by the aid of the results of extended Kalman filter processes for characteristics of the ampere-hour integral processes and the extended Kalman filter processes under a plurality of conditions of accurate extended Kalman filter processes, and accordingly cumulative errors of the ampere-hour integral processes can be obviously reduced; the results of the ampere-hour integral processes are used as judgment standards, different SOCvalue processes are formulated at different phases of electric quantities, weights of results of two types of algorithms can be automatically adjusted according to the precision of battery models, and accordingly errors can be obviously reduced when the models are inaccurate; as shown by verification, the algorithms are high in accuracy and reliability.
Description
technical field [0001] The invention relates to a method for estimating the remaining capacity of a battery, in particular to a method for estimating the remaining capacity of a battery used in a battery management system. Background technique [0002] With the popularity of electric vehicles, it is more and more important to accurately estimate the remaining battery capacity (State of Charge, SOC). At present, the scheme adopted by the automobile industry is mainly the ampere-hour integral method, which is corrected through the OCV-SOC curve. This method is simple in principle and is suitable for most batteries. However, due to inaccurate current sampling, large accumulated errors of the ampere-hour integration method, and untimely correction, the current SOC estimated by the industrial solution is not accurate. The Extended Kalman Filter algorithm (Extended Kalman Filter, EKF) is a closed-loop algorithm based on the battery model. When the model is established accurately,...
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CPCG01R31/367
Inventor 周娟化毅恒樊晨王江彬刘刚杨新哲丁勇良闫东升魏琛原亚雷蔡明哲刘凯校乾坤常文宇
Owner CHINA UNIV OF MINING & TECH