This paper presents a study on the state of charge observation of lithium-Ion batteries for energy management in embedded applications. The knowledge of the state of charge is fundamental for the safety and optimal usage of these batteries. The study focuses on the development and implementation of a Kalman filter-based observer algorithm on a Spartan 6 FPGA that can accurately estimate the state of charge of a battery, even if it is initialized differently from its actual state. In this paper we have focused on the opportunities of FPGA for fast calculation which allow to use the FPGA as a slave component in a BMS and allow to observe the SOC a great deal of cells with a low cost. The implementation of this observer on a low-cost FPGA can lead to cost reduction for battery management systems in various applications, such as electric cars and any other systems requiring the observation of the state of charge of a battery pack. The observer model was validated through simulations and real-time testing. This study presents a promising approach to accurately estimate the state of charge of Lithium-Ion batteries for efficient energy management in various applications.