Experimental assessment and model development of cycling behavior in Li-ion coin cells

A Novel Health Factor to Predict the Battery’s State-of-Health Using a Support Vector Machine Approach

The maximum available capacity is an important indicator for determining the State-of-Health (SOH) of a lithium-ion battery. Upon analyzing the experimental results of the cycle life and open circuit voltage tests, a novel health factor which can be used to characterize the maximum available capacity was proposed to predict the battery’s SOH. The health factor proposed contains the features extracted from the terminal voltage drop during the battery rest. In real applications, obtaining such health factor has the following advantages. The battery only needs to have a rest after it is charged or discharged, it is easy to implement. Charging or discharging a battery to a specific voltage rather than a specific state of charge which is difficult to obtain the accurate value, so the health factor has high accuracy. The health factor is not dependent on the cycle number of the cycle life test of the battery and it is less dependent on charging or discharging current rate, as a result, the working conditions have less effect on the health factor. Further, the paper adopted a support vector machine approach to connect the healthy factor to the maximum available battery capacity of the battery. The experimental results show that the proposed method can predict the SOH of the battery well.

Synergistic Effect between LiNi0.5Co0.2Mn0.3O2 and LiFe0.15Mn0.85PO4/C on Rate and Thermal Performance for Lithium Ion Batteries

A blend cathode has been prepared by mixing both LiNi_0.5Co_0.2Mn_0.3O₂ (NCM523) of high energy density and high specific capacity and LiFe_0.15Mn_0.85PO₄/C (LFMP/C) of excellent thermal stability via a low-speed ball-milling method. The lithium ion batteries using the blend cathode with LFMP/C of optimum percent exhibit better capacity retention after 100 cycles than those using only single NCM523 or LFMP/C. Both theoretical simulation and experimental rate performances demonstrate that the electrochemical property of blend cathode materials is predictable and economical. In addition, the thermal behaviors of blend cathodes are studied by using differential scanning calorimetry analysis. The thermal stability of blend cathode materials behaves better than that of the bare NCM523 accompanied with an electrolyte. It is found that the outstanding rate and thermal performance of the blend cathode is due to the prominent synergistic effect between NCM523 and LFMP/C, and 10% LFMP/C in the blend cathode materials is the most adaptable as considering both electrochemical and thermal properties simultaneously.