This study aims to implement the digital twin of a Li-ion battery by using real measurement data and to create a deep learning-based SOC (state of charge) estimation solution. In the case of the SOC estimator, a special type of deep learning, so-called long short-term memory (LSTM), was used to increase the capabilities of the estimator. The digital twin and the SOC estimator were created by using MATLAB and MATLAB/Simulink. As a result, the implemented system can accurately simulate the non-linearities of the Li-ion battery and provide a satisfactory estimation of the SOC of the battery.