Equalization Control Strategy And BMS Fault Diagnosis Of LiFeO₄ Battery Pack

Recycling is an obvious advantage for rechargeable batteries. Once made in use process will not cause damage to the natural environment. Especially in the regular grid to reach and the electricity of power has unique advantages and use value. Cell as a new type of battery, lithium iron phosphate has high safety coefficient and circulating more, monomer, large capacity, no memory effect and obvious advantages, very suitable for outdoor electric fields with large power demand. Subject to the lithium iron phosphate monomer battery capacity constraints, monomer can’t meet the demand of electricity of power, the battery together to obtain further to obtain high power in the form of high pressure. And monomer battery due to inconsistencies in the manufacture and use the link to the lithium iron phosphate battery monomer battery in disequilibrium. Equilibrium strategy research is to found a way to make up for the imbalance between monomer battery. Balancing strategy based on voltage parameters while convenient and simple, but can’t guarantee balanced control efficient and accurate. Based on the equilibrium strategy is limited by the capacity of parameters not directly obtained in practice is not workable. Therefore, urgent need a equilibrium strategies can be both effective and feasible.This article from the lithium iron phosphate electromotive force (EMF-SOC) charged state curve, this paper designed a new type of equilibrium strategies. The equilibrium strategies not only can in low monomer battery remaining power, pressure difference is larger to ensure balanced intervention, but also in the platform area of the voltage change of battery pack with equilibrium.In the laboratory of lithium iron phosphate battery was verified by means of experimental platform have relatively good balancing effect.Fault diagnosis method of Bayesian networks (Bayesian Network) method is a kind of statistical method for fault diagnosis.Early failure for lithium iron phosphate battery management system has the characteristics of uncertainty and the network structure is not complete. First according to the operation data and expert domain knowledge, history and troubleshooting record for lithium iron phosphate battery management system is established the bayesian networks.And follow historical operating data and maintenance records in constantly update and optimize the bayesian fault diagnosis network, gradually increase the battery management system of fault diagnosis and maintenance decision-making ability, improve the system efficiency of maintenance. As well as to find weak link in the system, to optimize the design of the battery management system to fundamentally improve the system stability.