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In this research the effect of temperature rising on battery performances such as depth of discharge and electricity generation efficiency had been conducted. After that temperature data acquired from data acquisition process is used as training data and test data to predict temperature using Holt-s Double Exponential Smoothing. The results show that at 0.7C, cells temperatures inside module reached 35.40C, rising about 4.90C. The temperature rising is greater than single cell that rose 30C to 29.70C. Then at 1.4C the module temperature reached 38.60C rising about 8.30C. Single cell temperature at 1.4C reached 35.70C, rising 9.40C. At 2.1C, single cell reached 45.10C with temperature increasing of 18.50C. Module temperature at 2.1C reached 480C with 190C increasing. Efficiency of electricity generation of single cell at 0.7C is 92.58%. The efficiency reduced to 84.48% at 1.4C rate. Then at 2.1C rate, single cell only capable of generated energy about 23.3Wh with 76.82% efficiency. Module at 0.7C has electricity generation efficiency of 91.58%. At 1.4C, the efficiency reduced to 83.38%. At 2.1C rate, the efficiency was getting smaller to 72.9%. Predictions conducted show that Holt-s Double Exponential Smoothing can predict the temperature rising in single cell. In module temperature predictions, training data was taken from one cell only to predict the rest of the cells. At 0.7C, Holt methods can predict six out of eight cells well. Five out of eight cells could also be predicted well at 1.4C. However at 2.1C, just four cells could be predicted well. The predictions accuracy of Holt-s Double Exponential Smoothing decreased when the temperature uniformity in module decreased as the C-rate increased