Battery internal temperature information processing method based on AUKF, equipment and medium

Abstract

The invention discloses a battery internal temperature information processing method based on an AUKF, equipment and a medium. The method comprises the following steps of: acquiring initial parameters of an equivalent thermal network model according to offline test data of an offline test of a battery module, and determining an optimal model parameter initial value in the initial parameters based on a multi-objective function fitting method; and determining a first battery internal temperature estimated value and a first model parameter estimated value of the battery of a vehicle at a first moment of actual operation according to the initial AUKF joint vector value of the battery of the vehicle, the first operation data of the battery of the vehicle and the equivalent thermal network model containing the optimal model parameter initial value. According to the battery internal temperature information processing method based on the AUKF, the equipment and the medium, the model parameters of the equivalent thermal network model can be optimized while the internal temperature of the battery is accurately estimated in real time, so that the internal temperature of the battery can be more accurately estimated according to the optimized model parameters, the working condition of the battery is optimized according to the internal temperature of the battery accurately estimated in real time, and the working efficiency of the battery is improved, and the safety of the battery is improved.

Description

technical field [0001] The invention relates to the technical field of battery temperature, in particular to an AUKF (adaptive unscented Kalman filter)-based battery internal temperature information processing method, device and medium. Background technique [0002] As the power of new energy vehicles, there is a common phenomenon of temperature rise in the charging and discharging process, and the heat generation and heat dissipation inside the battery are uneven, so there is a temperature field distribution inside the battery, which causes a large temperature difference between the inside and outside of the battery. , especially in high power demand applications; however, in actual battery thermal management, the battery surface temperature can only be measured in real time on the outer surface of the battery, and the internal temperature of the battery cannot be measured in real time, and the internal temperature of the battery It has a significant impact on the performan...

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Problems solved by technology

[0002] As the power of new energy vehicles, there is a common phenomenon of temperature rise in the charging and discharging process, and the heat generation and heat dissipation inside the battery are uneven, so there is a temperature field distribution inside the battery, which causes a large temperature difference between the inside and outside of the battery. , especially in high power demand applications; however, in actual battery thermal management, the battery surface temperature can only be measured in real time on the outer surface of the battery, and the internal temperature of the battery cannot be measured in real time, and the internal temperature of the battery It has a significant impact on the performance of the battery and is directly related to the safety performance of the battery. Therefore, battery thermal management, especially the estimation of the internal temperature of the battery, has become one of the key and most challenging parts of the battery management system

[0003] In the prior art, among the battery internal temperature estimation methods, the method of estimating the internal temperature of the battery based on the electrochemical impedance spectroscopy test has high requirements for the test system, so the actual vehicle cannot meet its test conditions; based on the internal temperature and The method of estimating the internal temperature of the battery by the functional relationship between the surface temperature, the obtained functional relationship has no actual physical meaning, and it is difficult to adapt to the accurate calculation of the internal temperature of the battery under various complex working conditions; the battery heat transfer model in the prior art will The surface is equivalent to a temperature point method, and the temperature of each point on the battery surface is considered to be the same. The disadvantage of this solution is that because the internal structure and external shape of the battery are not perfectly symmetrical, the heat transfer paths from the inside of the battery to all surfaces are not consistent. , so the temperature at different positions on the battery surface will also be different, so the surface temperature is equivalent to a point will make the final estimated battery temperature error is large

In addition, some existing technologies use offline identification algorithms or online parameter identification methods based on estimators to obtain model parameters. In this scheme, the influence of battery internal temperature estimation errors on parameter identification results cannot be eliminated, which will lead to mismatching of model parameters, further causing Larger internal temperature estimation error

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