Zine, BachirYahmedi, SaidBecherif, MohamedMarouani, Khoudir2019-05-232019-05-232018-12-10https://dspace.univ-eloued.dz/handle/123456789/1380International Symposium on Mechatronics and Renewable Energies El-Oued 10- 11 December 2018One of the most difficult problems in battery pack management aboard an electrical vehicle is the estimation of the state of charge (SOC). However, the state of charge gives information about how much longer the battery can be used and when the charging process will be cut off. This paper presents the experimental comparison study of different state of charge estimation methods (discharge voltage method, coulomb counting method and artificial neural networks method) in electric vehicles batteries. For state of charge (SOC) estimation we require voltage, current and temperature, all these data are nonlinear function of SOC and are depends on charge and discharge operation. Also, experimental results are carried out in order to validate this studyenState of Charge, Discharge Voltage, Artificial Neural Networks, Coulomb CountingOther