Lithium-ion batteries have become the mainstream power source for electric vehicles because of their excellent performance.However,lithium-ion batteries still experience aging and capacity attenuation during usage.It ...Lithium-ion batteries have become the mainstream power source for electric vehicles because of their excellent performance.However,lithium-ion batteries still experience aging and capacity attenuation during usage.It is therefore critical to accu-rately predict battery remaining capacity for increasing battery safety and prolonging battery life.This paper first adopts the metabolism grey algorithm and a simplified electrochemical model to predict battery capacity under different operating conditions.To improve the prediction performance where the capacity changes nonlinearly,a decoupling analysis of battery capacity loss is then conducted based on the simplified electrochemical model.Finally,an adaptive fitting method is devel-oped for capacity prediction,aiming at improving the prediction accuracy at the inflection point of battery capacity diving.The prediction results indicate that the developed adaptive fitting method can achieve high prediction accuracy under battery capacity attenuation at different discharge stages with errors lower than 2.2%.And the battery capacity decay shows linear variation,and the proposed method effectively forecast the inflection point of battery capacity diving.展开更多
基金supported by China Postdoctoral Science Foundation(2021M690740)the Weihai Scientific Research and Innovation Funds(2019KYCXJJYB09).
文摘Lithium-ion batteries have become the mainstream power source for electric vehicles because of their excellent performance.However,lithium-ion batteries still experience aging and capacity attenuation during usage.It is therefore critical to accu-rately predict battery remaining capacity for increasing battery safety and prolonging battery life.This paper first adopts the metabolism grey algorithm and a simplified electrochemical model to predict battery capacity under different operating conditions.To improve the prediction performance where the capacity changes nonlinearly,a decoupling analysis of battery capacity loss is then conducted based on the simplified electrochemical model.Finally,an adaptive fitting method is devel-oped for capacity prediction,aiming at improving the prediction accuracy at the inflection point of battery capacity diving.The prediction results indicate that the developed adaptive fitting method can achieve high prediction accuracy under battery capacity attenuation at different discharge stages with errors lower than 2.2%.And the battery capacity decay shows linear variation,and the proposed method effectively forecast the inflection point of battery capacity diving.
