Battery charge state estimation method based on AEKF and estimation system

A technology for battery state of charge and posterior estimation, applied in the direction of measuring electricity, electrical components, measuring electrical variables, etc., can solve problems such as difficulty in implementation, high application cost, and lack of advantages

Inactive Publication Date: 2016-07-06
OPTIMUM BATTERY CO LTD
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Problems solved by technology

The direct method refers to directly measuring the remaining power of the battery through experimental equipment; the indirect method mainly uses the internal physical and chemical characteristics of the battery, and requires high-precision equipment in the estimation process, so it is difficult to achieve in practice
The ampere-hour integration method, open-circuit voltage method, and internal resistance method are indirect methods. The ampere-hour integration method will produce cumulative errors during the calculation process, which will cause the calculated SOC to increase with the increase of charge and discharge time. At the same time, the ampere-hour integration method The accuracy of calculating the initial valu

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  • Battery charge state estimation method based on AEKF and estimation system
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  • Battery charge state estimation method based on AEKF and estimation system

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[0038] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

[0039] The present invention provides a battery state of charge (StateofCharge, SOC) estimation method based on AEKF (adaptive extended Kalman filter algorithm). The general idea of ​​this method is to initialize each estimated parameter firstly, mainly including t 0 Initialize the SOC state, covariance and noise matrix (process noise, observation noise) at each moment, then update the process variables, proceed recursively according to the above-mentioned Kalman filter algorithm, and then determine the weighting coefficient based on the forgetting factor , and then determine its forgetting factor, update the parameters in the algorithm, and finally get the estimated value of SOC. By repeating the whole process to iterate, the optimal SOC estimati...

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Abstract

The invention relates to the battery electrical testing technology, especially relates to a battery charge state estimation method based on AEKF and an estimation system. Battery SOC can be estimated by adopting the self-adaption expansion Kalman filtering algorithm, and the parameter self-adaption adjusting way of the Kalman filtering algorithm can be changed by additionally providing the weighting coefficient based on the forgetting factor, and then the influence of the parameter initial value setting on the whole algorithm is small, and the phenomena of the inaccurate battery SOC initial value calculated by adopting the original ampere-hour integral method and the accumulated error can be overcome, and in addition, the battery SOC can be estimated accurately and reliable. The battery charge state estimation method and the estimation system are advantageous in that the convergence performance is good, the convergence speed is fast, the algorithm transplantability is good, and the use stable and reliable; the estimation method and the estimation system can be used for the electric vehicle battery management field, and can be used for the SOC estimation of the electric vehicle storage battery, and therefore the endurance mileage of the electric vehicle can be calculated accurately, the control of the driver over the vehicle can be facilitated; the estimation method and the estimation system are more suitable for the electric vehicle environment having the strong current fluctuation.

Description

technical field [0001] The invention relates to battery electrical testing technology, in particular to an AEKF-based battery charge state estimation method and estimation system. Background technique [0002] At present, methods for estimating the state of charge (SOC) of a battery are mainly divided into two categories: a direct method and an indirect method. The direct method refers to directly measuring the remaining power of the battery through experimental equipment; the indirect method mainly uses the internal physical and chemical characteristics of the battery, and requires high-precision equipment in the estimation process, so it is difficult to implement in practice. The ampere-hour integration method, open-circuit voltage method, and internal resistance method are indirect methods. The ampere-hour integration method will produce cumulative errors during the calculation process, which will cause the calculated SOC to increase with the increase of charge and discha...

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Application Information

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IPC IPC(8): G01R31/36H03H17/02
CPCG01R31/3648G01R31/388H03H17/0202H03H2017/0205
Inventor 孔满关海盈
Owner OPTIMUM BATTERY CO LTD
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