Distributed computing based on AI algorithms in battery early warning and SoH prediction of the intelligent connected vehicles

Abstract

The foremost task of the battery management system is to estimate the end-of-life batteries, their capacity and internal resistance, which are commonly used to evaluate the State of Health (SoH) for the battery cells and packs. The SoH for batteries plays a vital role in intelligent connected vehicles. To evaluate the warning conditions of battery life units, this paper suggests the artificial intelligence-assisted particle swarm optimization for the SoH prediction of the intelligent connected vehicles. The key elements of this method include the battery ageing cycle, identifying the SoH and battery health forecasting based on the gradual changing processes of the battery. Besides, several accelerated test results are reported for intelligent connected vehicles, using battery mode packages. To validate the concept of the SoH prediction method, a simulation test-bed is developed and test results indicate that the idea is projected with a higher prediction rate.