基于平均电压快速识别锂离子电池老化模式

In-operation diagnosis method for degradation modes of lithium-ion battery based on average voltage

锂离子电池在老化过程中表现为非线性衰退,这会危及新能源汽车或储能系统的安全。提出了一种基于实车使用或储能系统使用的原位快速识别老化模式的方法,该方法仅需要80%放电深度(DOD)区间的电压、电流数据。通过建立的老化模型模拟了27种老化模式,该模型可通过扩展平均电压与容量衰退的轨迹快速识别非线性衰退的老化模式。证明了电池的非线性衰退与负极材料损失或锂离子损失增加有关,并且扩展平均电压的轨迹可判断正极材料损失是否加速衰退。采用正负极匹配的无损老化模式诊断验证了方法的准确性。

Li-ion batteries exhibit nonlinear degradation during aging,which can endanger the safety of new energy vehicles or energy storage systems.An in-operation diagnosis method for degradation modes was proposed for vehicle or energy storage systems,which only required voltage and current within 80%DOD.27 aging modes were simulated by the established aging model,which could quickly identify the non-linearly degradation aging mode by the extended average voltage and capacity degradation trajectory under the condition of linear increase of internal resistance.It's demonstrated that the nonlinear degradation of the battery is related to the increase of anode material loss or lithium ion loss,and that the trajectory of the extended average voltage can determine whether the cathode material loss accelerates the degradation.The accuracy of the method was verified by the undamaged daging mode diagnosis with cathode and anode matching.