The invention relates to the technical field of
lithium batteries, in particular to a
lithium battery SOC prediction method and device, and solves the problems that in the prior art, an SOC prediction result deviates from an actual value, meanwhile, an open-circuit
voltage method is adopted, open-circuit
voltage is closely related to the temperature and the
discharge rate of a battery, and the SOC prediction result is poor. And the open-circuit
voltage SOC curves under different temperatures and
discharge rates may have differences. The invention discloses a
lithium battery SOC prediction method and device, and the device comprises a data collection module which is responsible for collecting the related data, voltage, current and temperature of a
lithium battery, and the data are the basis of SOC prediction. The SOC prediction precision is improved, multi-dimensional data such as voltage, current and temperature of the battery are collected in real time through a high-precision sensor, a comprehensive and accurate information basis is provided for SOC prediction, a prediction model is constructed by adopting advanced algorithms such as Kalman filtering and a neural network, nonlinear characteristics and dynamic changes of the battery can be effectively captured, and the SOC prediction precision is improved. Therefore, the accuracy of SOC prediction is improved.