Method and system for predicting state of charge of power battery of pure electric vehicle

Abstract

The invention relates to a method and a system for predicting a state of charge of a power battery of a pure electric vehicle. The method for predicting the state of charge comprises the following steps of S1, acquiring external characteristic parameters of the power battery; S2, performing data mining on the external characteristic parameters; and S3, establishing a multi-input parameter combination type multiple dynamic decision tree model to obtain a predicted value of the state of charge. According to the method and the system for predicting the state of charge of the battery, the external characteristic parameters are mined by adopting the multiple dynamic decision tree model to obtain effective data, and useless data is removed, so that data redundancy is avoided and the prediction time is shortened; and especially under the condition of considering energy feedback of the battery and continuously changed working condition, the value of the state of charge of the battery still can be predicted accurately in real time, so that the practicality and validity are high.

Description

technical field [0001] The invention relates to a method and system for predicting the state of charge of a power battery of a pure electric vehicle. Background technique [0002] As a key component of the pure electric vehicle power system, the power battery is crucial to the power, safety and economy of the vehicle system. In order to ensure the good performance of the battery and prolong its service life, it is necessary to manage and control the battery reasonably, but the premise must be to obtain the state of charge of the battery accurately and reliably. Just as ordinary vehicles must monitor the capacity of fuel in the fuel tank, pure electric vehicles also need to know the energy of their power batteries, and the state of charge is an important parameter that reflects the energy of the battery. Therefore, how to correctly obtain the state of charge of the power battery has become a pure electric vehicle application important part of. As an internal characteristic ...

AI Technical Summary

Problems solved by technology

[0005] In addition, the external characteristic parameters of the power battery include voltage, current, temperature and internal resistance, etc. In the actual prediction, not all parameters are used for prediction, and better prediction results can be obtained. There will be many combinations of prediction inputs, such as (Voltage, Current), (Voltage, Current, Temperature), (Voltage, Current, Internal Resistance), etc. Different combinations may result in different classification effects, and the accuracy must also be different, so the optimal input combination remains to be determined

[0006] During the driving process of the car, its running state may change. For example, there are many vehicles on the road and congestion occurs, which directly causes the car to change from the cruising state to the deceleration or braking state. At this time, the car does not follow the path of the sequential working conditions. Driving, which will have a great impact on the accurate prediction of the state of charge of the power battery

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