Lithium battery SOC prediction method for improving ant colony algorithm and optimizing particle filter

Abstract

The invention particularly relates to a lithium battery SOC prediction method for improving an ant colony algorithm and optimizing particle filtering, and the method comprises the following steps: carrying out the discharge test of a lithium battery under different working condition currents, and preprocessing the test data; performing parameter identification according to the preprocessed experimental data, and constructing a state equation according to an ampere-hour integral method in combination with SOC prediction influence factors; establishing a measurement equation of a battery theoretical prediction model according to the second-order Thevenin equivalent model; using an improved ant colony algorithm to optimize particle filtering; and predicting the SOC change of the battery through optimized particle filtering. According to the prediction method provided by the invention, the situation that a traditional ant colony algorithm is easy to fall into a local optimal solution is improved; the improved ant colony algorithm is utilized to optimize particle filtering, the problems of low particle diversity and poor particle appearing when the SOC is estimated through the particle filtering algorithm are solved, the problems that a lithium battery SOC estimation method is complex and low in accuracy are solved, and the estimation precision is effectively improved.

Description

technical field [0001] The invention belongs to the field of battery energy management systems, relates to lithium battery state of charge prediction technology, and in particular 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 of energy shortage and environmental pollution, people are gradually turning to the research field of low energy consumption and environmental protection technology. Among them, the research and use of electric vehicles are favored by people, and have received strong support from national policies, and have been rapidly developed. develop. Lithium-ion batteries are widely used in the field of electric vehicles due to their advantages such as high energy ratio, long life and low self-discharge rate. As the lithium battery ages, the capacity and stability of the battery will gradually decrease. Therefore, in order to en...

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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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