Battery capacity forecasting system and forecasting method

Abstract

The invention relates to a battery capacity prediction system and method. The system used to predict the practical capacity of a battery in real time main comprises a controller, a storage module, a signal collection module and a comparison module. The storage module is connected with the controller, and stores a library of correspondence between condition variables and the practical battery capacity in different conditions. The signal collection module is configured to collect the condition variables, and transmit collected information to the control module. The comparison module is connectedwith the controller, and used to compare the obtained collection information with the correspondence library so that the controller calculates the practical capacity of the battery according to a comparison result. The system takes comprehensive consideration of the condition variables that may influence the practical battery capacity, the controller calculates the practical battery capacity according to the comparison result, and thus, a real-time, dynamic, accurate and reliable prediction result of the practical battery capacity can be obtained.

Description

technical field [0001] The invention relates to the technical field of battery management, in particular to a battery capacity prediction system, and at the same time, the invention also relates to a battery capacity prediction method. Background technique [0002] The real-time dynamic, accurate, stable and reliable prediction of battery capacity (capacity, referred to as C) is one of the key links in predicting battery SOC (battery remaining power). The actual capacity of the electric vehicle is prone to fire and explosion; and if the actual capacity of the battery is exceeded during discharge, it is easy to cause irreversible and serious damage to the battery. [0003] At present, the actual capacity of the battery is usually predicted in the following two ways: [0004] (1) Directly use the rated capacity provided by the battery manufacturer or the measured battery capacity of the finished battery to install the electric vehicle when it leaves the factory. The attenuat...

AI Technical Summary

Problems solved by technology

[0004] (1) Directly use the rated capacity provided by the battery manufacturer or the measured battery capacity of the finished battery to install the electric vehicle when it leaves the factory. The attenuation is large. If this method is used to predict, it will seriously affect the prediction accuracy of the subsequent SOC;

[0005] (2) Regularly correct and calibrate the battery capacity. This method does not consider the real-time temperature of the battery during operation, the charging and discharging state of the battery, the charging and discharging current of the battery, and the SOC of the battery and other reversible factors on the actual capacity of the battery. ;

[0006] It can be seen from the above description that the existing predictions only consider the single influence of individual factors on the battery capacity, and cannot fully and accurately predict the actual capacity of the battery, resulting in errors in subsequent SOC predictions, and poor programmability

Images