Comparison of Multi-step Prediction Models for Voltage Difference of Energy Storage Battery Pack Based on Unified Computing Operation Platform

Abstract

The voltage difference of battery pack is a very important index for the state evaluation of energy storage battery. When the voltage difference is too large inside the battery pack, it may cause a series of safety problems. By predicting the voltage difference of battery pack, potential dangerous situations can be detected as early as possible, and necessary measures can be taken to ensure the safety of the energy storage battery, so as to realize the reliability improvement, efficiency improvement, and safety guarantee of the energy storage system. Through the multi-step prediction for the voltage difference of the energy storage battery pack, the variation trend of the voltage difference can be predicted in advance, so as to warn the possible voltage difference over-limit fault. At present, there are many methods for multi-step prediction of time series data, but which one is most suitable for predicting the voltage difference of the energy storage battery pack is still lack of research. In this paper, the stationarity and correlation of energy storage battery pack’s voltage difference data are analyzed and processed, and different multi-step prediction algorithms are used to predict the voltage difference of energy storage battery pack. The prediction results generated by different models are compared and analyzed, and the most suitable model selection for predicting the voltage difference of energy storage battery pack is discussed.

Keywords

• voltage difference prediction of energy storage battery pack
• time series data prediction
• unified computing operation platform
• voltage difference over-limit fault