Lithium-ion battery (LIB) storage systems are widely deployed as energy and power storage devices for electric vehicles. However, it is rather complex to ensure battery safety and performance. To guarantee lithium-ion batteries’ dependability, safety, and acceptable durability in smart gadgets, and electric vehicles, an extended Kalman filter algorithm is used to provide an accurate SoC estimation. An EKF estimating algorithm is deployed on a MATLAB program to assess the Lithium-ion battery SoC, and the NEDC load profile is taken as a Load profile reference. The MATLAB modeling of systems and EKF algorithms has been deployed. The simulation results provide Ampere-Hour and EKF estimations of Lithium-ion battery SoC, moreover, it demonstrates how EKF outperforms the traditional Ampere-Hour algorithm regarding the accuracy of SoC estimation. Indeed, the proposed SoC estimation method performs better results with RMSE being 0.038 (3.8%).