Cell inconsistency affect battery life and driving safety. In order to solve the accuracy problem of online prediction of cell inconsistency of power battery, battery characteristic analysis based on of vehicle network big data is proceeded, health indicator(HI), based on the cell terminal voltage difference,is proposed through the degradation model; As the similar distribution of cell terminal voltage difference between battery discharge conditions, the health indicator sequence based on SOC(State of Charge) is constructed, and the next health indicator is predicted by Gaussian process regression. The prediction results show that the method requires less training samples and less hardware resources, and the overall prediction accuracy is not less than 85%, which can meet the practical requirements.
The core of the overall fuel cell vehicle control is energy distribution strategy. This study studies fuel cell buses and aims to extend the fuel cell lifespan to guarantee battery lifespan and to enhance the vehicle's overall performance. We proposed a fuzzy method for energy distribution and state of charge feedback and designed a fuel cell bus energy distribution model based on the Takagi–Sugeno fuzzy control. Secondary development based on these results was carried out through the ADVISOR simulation platform. Comparison of simulation results shows that the proposed control strategy not only satisfies the full vehicle dynamic performance requirements, but also enhances the fuel cell lifespan and guarantees the battery lifespan, while remains relatively economically competitive.