Lithium ion health state estimation method based on charging process

Abstract

The invention discloses a lithium ion health state estimation method based on a charging process. Experimental data such as voltage, current and time are obtained through a lithium ion circular chargeand discharge experiment in an off-line state, feature vectors are extracted from a constant current charging process, and the feature vectors are time intervals (times required for the voltage to flow from Va to Vb during the constant current charging) of local voltage intervals [Va, Vb] in the constant current charging process. The extracted feature vectors are filtered by grey relational analysis and a Gaussian process regression model to obtain a voltage interval to which the optimal feature vector belongs and a training model thereof. In an online state, the time interval of the voltageintervals obtained in the offline state is obtained to serve as an input feature vector and it input into the trained Gaussian process regression model to obtain battery SOH. According to the lithiumion health state estimation method disclosed by the invention, no complex equivalent circuit model needs to be established, the battery SOH can be estimated online via a data driving method, and the accuracy is very good.

Description

technical field [0001] The invention belongs to the field of lithium ion batteries, and in particular relates to a method for estimating the state of health of lithium ions based on a charging process. Background technique [0002] Lithium-ion batteries are used in mobile phones, laptops, balance cars, electric vehicles, aerospace and other fields due to their advantages such as high voltage, low self-discharge rate, high energy density, high cycle life, no pollution and no memory effect. However, during the long-term use of the battery, due to abuse or aging, a series of electrochemical reactions will occur inside the battery, which will cause the capacity to decline, the internal resistance to increase, and may cause catastrophic consequences such as fire and explosion. In order to ensure the normal and efficient operation of the battery, the battery management system (BMS) is essential, and the battery state of health (SOH) is one of the core functions of the BMS. Accura...

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Problems solved by technology

The empirical model has the advantages of easy modeling and convenient use, but it is too dependent on the battery type and empirical parameters, and its application range is limited; the electrochemical model contains many equations and a large number of internal parameters, as well as boundary conditions, the calculation is complicated, and it is not easy to analyze it. Solve it; the model parameters in the equivalent circuit model will change with the ambient temperature, and there will be large estimation errors in specific applications

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