An improved ant colony algorithm to optimize the particle filter soc prediction method of lithium battery

Abstract

The invention specifically relates to a method for predicting the SOC of a lithium battery by improving the ant colony algorithm to optimize particle filtering, which comprises the following steps: conducting a discharge test on the lithium battery under different working conditions and currents, and preprocessing the experimental data; The parameters are identified, and the state equation is constructed according to the ampere-hour integration method combined with the SOC prediction influencing factors; the measurement equation of the battery theoretical prediction model is established according to the second-order Thevenin equivalent model; the improved ant colony algorithm is used to optimize the particle filter; Filter to predict battery SOC changes. The prediction method provided by the invention improves the situation that the traditional ant colony algorithm is easy to fall into the local optimal solution; and uses the improved ant colony algorithm to optimize the particle filter, and solves the problem of low particle diversity and particle diversity when the particle filter algorithm estimates the SOC. The problem of poverty, overcoming the complex and low accuracy of lithium battery SOC estimation methods, effectively improves the estimation accuracy.

Description

technical field [0001] The invention belongs to the field of battery energy management systems, relates to a lithium battery state-of-charge prediction technology, and in particular relates to a lithium battery SOC prediction method using an improved ant colony algorithm to optimize particle filtering. Background technique [0002] With the increasingly serious problems such as energy shortage and environmental pollution, people are gradually turning to the research field of technology with low energy consumption and environmental protection. Among them, the research and use of electric vehicles are favored by people, and have received strong support from national policies. develop. Lithium-ion batteries are widely used in electric vehicles due to their high energy ratio, long life and low self-discharge rate. With the aging of the lithium battery, the capacity and stability of the battery will gradually decrease. Therefore, in order to ensure the safe use of the battery, i...

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Problems solved by technology

[0004] The purpose of the present invention is to solve the above-mentioned problems existing in the prior art, and proposes a lithium battery SOC prediction method using an improved ant colony algorithm to optimize particle filtering, which can overcome the complex and low-accuracy lithium battery SOC estimation method, and effectively Improved estimation accuracy

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