Reliable model parameter identification is a key index for battery management systems. To ensure the sustainability of lithium-ion battery under unknown measurement noise, an effective lithium-ion battery model with updated parameters should be developed. To soften the impact of measurement noise from the transducer, an improved equivalent circuit model using current noise as the compensation factor is introduced into the lithium-ion battery. Based on the suppression of parameter disturbances in the equivalent circuit model, a double extended Kalman filter algorithm is used to recursively identify model parameters. Finally, the federal urban driving schedule (FUDS) is loaded on the lithium-ion battery to test the effectiveness of the improved method. The experimental results demonstrate the effectiveness of the model and identification method in the identification of lithium-ion battery parameters.