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This article presents an enhanced internal temperature-estimation method for lithium-ion batteries using a 1-D model and a dual Kalman filter (DKF). The cylindrical battery cell is modeled by a 1-D thermal model with three nodes. This model provides a more accurate representation of the temperature distribution, resulting in more detail of the temperature field. With the newly developed 1-D model, an enhanced temperature-estimation method is developed by including the internal resistance identification and SOC estimation in the temperature-estimation process. Experiments and simulations are conducted to evaluate the robustness and accuracy of the temperature estimation. The estimated temperature using the 1-D model with random initial values is compared with the surface temperature from experiments, which shows excellent robustness against random initial values. High estimation accuracy is …