A Relative State of Health Estimation Method Based on Wavelet Analysis for Lithium-Ion Battery Cells
Jun Xu, Xuesong Mei, Xiao Wang, Yumeng Fu, Yunfei Zhao, Junping Wang
Abstract
The state of health (SOH) is essential for the safety and reliability of lithium-ion batteries in different applications. Moreover, the inconsistency of battery cells in battery packs is inevitable. To determine the SOH difference is even more challenging without the calculation of the SOH of each battery cell. To solve the problem, this article proposes a novel relative SOH (rSOH) estimation method based on wavelet analysis, and the SOH differences for series-connected lithium-ion battery cells in the battery pack can be obtained. It should be noted that no battery model is needed in this method. The more accessible battery voltage of each battery cell is sufficient to obtain the SOH differences, without SOH estimation for each battery cell. With the wavelet analysis, more detailed information of the battery cells is obtained. The rSOH is then introduced as the index of the SOH difference, and the estimation procedure is further analyzed. Finally, experimental validations are conducted by different aged battery cells. The different state of charge conditions and different driving cycles are applied to show the robustness of the proposed method. The experimental results show that the rSOH estimation error is limited within 5%, equivalently with less than 1% SOH estimation error, thus proving the effectiveness of the proposed rSOH estimation method.