简介:100piecesof26650-typeLithiumironphosphate(LiFePO4)batteriescycledwithafixedchargeanddischargeratearetested,andtheinfluenceofthebatteryinternalresistanceandtheinstantaneousvoltagedropatthestartofdischargeonthestateofhealth(SOH)isdiscussed.Abackpropagation(BP)neuralnetworkmodelusingadditionalmomentumisbuiltuptoestimatethestateofhealthofLi-ionbatteries.Theadditional10piecesareusedtoverifythefeasibilityoftheproposedmethod.Theresultsshowthattheneuralnetworkpredictionmodelhaveahigheraccuracyandcanbeembeddedintobatterymanagementsystem(BMS)toestimateSOHofLiFePO4Li-ionbatteries.