Li-Ion batteries are widely preferred in electric vehicles. The charge status of batteries\nis a critical evaluation issue, and many researchers are studying in this area. State of charge gives\ninformation about how much longer the battery can be used and when the charging process will be\ncut off. Incorrect predictions may cause overcharging or over-discharging of the battery. In this study,\na low-cost embedded system is used to determine the state of charge of an electric car. A Li-Ion battery\ncell is trained using a feed-forward neural network via Matlab/Neural Network Toolbox. The trained\ncell is adapted to the whole battery pack of the electric car and embedded via Matlab/Simulink to\na low-cost microcontroller that proposed a system in real-time. The experimental results indicated\nthat accurate robust estimation results could be obtained by the proposed system.
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