This paper discusses a continuous-time system identification of the battery for electric vehicles (EVs). Although it is important to know a state of charge (SOC) and parameters of the battery to maximize its efficiency and safety, there are still some difficulties in estimating them. The development of the battery model suffers from the battery physicochemical complexity and nonlinearity. To address such issues, this paper proposes a continuous-time system identification method using the battery model in consideration of temperature characteristics. This approach is verified by performing a construction of a model of the battery using experimental data with an EV.