Lithium-ion battery SOC estimation method

Abstract

The invention discloses a lithium-ion battery SOC estimation method. According to analysis on experimental data of the lithium-ion battery rebound voltage at high or low temperature, a lithium-ion battery residual capacity prediction model of a self-adaption nerve fuzzy inference system is built. The rebound voltage and environment temperature are determined as input of the lithium-ion battery residual capacity prediction model while the lithium-ion battery residual capacity is determined as output. In the platform of MATLAB, according to the experimental data, the lithium-ion battery residual capacity prediction model of the self-adaption nerve fuzzy inference system is trained and verified. The obtained model is applied to predication and verification of the residual capacity of different battery packs. According to the method, the model is adaptable to being embedded into the existing battery management systems at present to realize accurately estimating the residual capacity of the battery so as to prevent overcharge and overdischarge of the battery; and thus, service life of the battery is prolonged, cost of users is lowered and the method has great economic benefit and social benefit.

Description

technical field [0001] The invention relates to a method for estimating the SOC of a lithium ion battery, in particular to a method capable of accurately estimating the remaining capacity of the lithium ion battery. Background technique [0002] Lithium-ion batteries have been widely used in various fields. Due to the complexity of the reaction process, a complete battery management system is required, and accurate estimation of SOC is very important. A large number of researchers have done a lot of work around the problem of accurate SOC estimation in lithium-ion battery applications. The safety and energy utilization efficiency during use are effectively improved. Research institutions and universities at home and abroad have carried out a lot of research and experiments on the SOC estimation of lithium-ion batteries. An important part of battery management is remaining capacity estimation, and remaining capacity estimation has always been one of the more difficult issue...

AI Technical Summary

Problems solved by technology

[0016] To sum up, there is no comprehensive and effective solution in the research of lithium-ion battery SOC estimation. The multivariate parameter estimation method based on battery equivalent model purchase and construction has become a development trend, but it is necessary to find the best solution between improving accuracy and reducing calculation load. Find the best balance to continuously optimize and improve the estimation method

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