Battery Discharging Temperature Prediction Using Holt’s Double Exponential Smoothing

In this research the discharging process to find the effect of temperature rising on prismatic lithium iron phosphate battery performances such as depth of discharge and electricity generation efficiency had been conducted. Battery discharging system has been built to acquire data such as temperature, voltage and electric current. Discharging temperature data were taken from single cell and module that consists of eight cells at three different C-rates which are 0.7C, 1.4C and 2.1C. After that discharging 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 the depth of discharge of single cell and module were getting smaller as the C-rates increased. The same condition also occurred on electricity generation efficiency. The efficiencies were also getting smaller when the C-rates were getting larger. Temperature predictions conducted show that Holt's Double Exponential Smoothing can nicely 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.