| Investigation of Evolutionary Intelligence Techniques for SoC Estimation of Rechargeable Batteries in Electric Vehicles (EVs) |
| Paper ID : 1078-IUGRC6 (R2) |
| Authors |
|
Hany A Bastawrous *, Abdelwahab Ehab The British University in Egypt |
| Abstract |
| The increase in pollution caused a shift in the industry from combustion engines toward Electrically powered vehicles. The electrification of vehicles, has an enormous impact on the research of batteries and battery management systems. The batteries go through various tests to verify their reliability and their ability to perform in a satisfactory matter, with it being the most suitable battery for the vehicle. Furthermore, the battery management system is the system responsible for overseeing various parameters, with the most important parameter is the SOC of the battery. SOC can be estimated using various technique, but this paper focuses on simulating the battery using an intelligent technique, with the SOC being estimated using neural network and compared with the SOC estimation using Kalman filter. The neural network estimation method, produced valid results with high accuracy in comparison to the estimated extended Kalman filter method, and the values were closer to the real values of the SOC. |
| Keywords |
| Electric Vehicles, Battery Management System, Kalman Filters |
| Status: Accepted |