Functional Safety Analysis And Fault Diagnosis Of Power Battery Charging

With the growing energy crisis and environmental pollution problems,energy conservation and environmental protection have gradually become the strategic goals of a new era for China's automobile manufacturing industry and industry to pursue sustained,rapid and healthy development.At the critical stage of current electric vehicle development,safety must always be regarded as the most critical indicator of new energy vehicles.In recent years,due to the thermal runaway of the power battery system during charging,electric vehicle fires have occurred repeatedly,which has seriously endangered the life and property safety of the driver,and also restricted the further development of electric vehicles to a certain extent.Therefore,according to the ISO26262 functional safety standard,this paper adopts a model-based design method to realize the development of power battery system charging safety management software,aiming to improve the safety level of electric vehicle charging function.This article first introduces the main content of the road vehicle functional safety standard ISO26262,the development status of electric vehicle power batteries,and the current status of domestic and foreign charging safety technology research.Then take the battery over-voltage,over-temperature and over-current faults as examples during electric vehicle charging,conduct hazard analysis and risk assessment respectively,and obtain the corresponding functional safety goals and ASILC levels,and further refine the functional safety requirements and software Safety requirements,and designed a charging safety management software architecture that includes a state management module,a fault management module,a current limit module,and a relay control module.Finally,the unit design,static verification,unit requirement test,and unit of the software model were completed through Matlab / Simulink Interface testing and software-in-the-loop testing verify that the designed software meets functional safety requirements.Lithium-ion battery system has the characteristics of complexity,nonlinearity and uncertainty,and the faults in its system influence each other.It is difficult to ensure the rapidity and accuracy of diagnosis by relying on the battery management system for online fault diagnosis.Therefore,from the perspective of historical data analysis,this paper introduces Bayesian network to improve the efficiency of battery fault diagnosis during charging.First,according to the fault tree-Bayesian network transformation method,a Bayesian network model of power battery charging faults is generated,and the Bayesian tool Netica is used to perform fault diagnosis and reasoning analysis on the model.The results show that this method can provide a basis for rapid fault location.