Equivalent circuit models (ECM) of lithium ion batteries are used in many applications because of their ease of implementation and low complexity. The accuracy of an ECM is critical to the functionality and usefulness of the battery management system (BMS). The ECM accuracy depends on the parametrization method, and therefore different experimental techniques and model parameter identification methods (PIM) have been widely studied. Yet, how to account for significant changes in time constants between operation under load and during relaxation has not been resolved. In this work a novel PIM and modified ECM is presented that increases accuracy by 77.4% during drive cycle validation and 87.6% during constant current load validation for a large format lithium iron phosphate prismatic cell. The modified ECM uses switching RC network values for each phase, which is significant for this cell and particularly at low state-of-charge for all lithium ion batteries. Different characterisation tests and the corresponding experimental data have been trained together across a complete State-of-Charge (SoC) and temperature range, which enables a smooth transition between identified parameters. Ultimately, the model created using parameters captured by the proposed PIM shows an improved model accuracy in comparison with conventional PIM techniques.

锂离子电池的等效电路模型（ECM）由于易于实现且复杂性低而在许多应用中使用。ECM的准确性对于电池管理系统（BMS）的功能和实用性至关重要。ECM精度取决于参数化方法，因此对不同的实验技术和模型参数识别方法（PIM）进行了广泛的研究。然而，如何解决负载下运行和松弛期间之间的时间常数的重大变化尚未解决。在这项工作中，提出了一种新型的PIM和改进的ECM，可将大型磷酸铁锂棱柱形电池的驱动周期验证期间的准确度提高77.4％，将恒定电流负载验证期间的准确度提高87.6％。修改后的ECM对每个相使用开关RC网络值，这对于该电池非常重要，尤其是在所有锂离子电池的充电状态低的情况下。在完整的荷电状态（SoC）和温度范围内，已经对不同的表征测试和相应的实验数据进行了训练，从而可以在识别出的参数之间进行平滑转换。最终，与传统的PIM技术相比，使用建议的PIM捕获的参数创建的模型显示出更高的模型准确性。这样可以在确定的参数之间进行平滑过渡。最终，与传统的PIM技术相比，使用建议的PIM捕获的参数创建的模型显示出更高的模型准确性。这样可以在确定的参数之间进行平滑过渡。最终，与传统的PIM技术相比，使用建议的PIM捕获的参数创建的模型显示出更高的模型准确性。