![]() Finally, this research uses a publicly available dataset from Oxford to demonstrate the effectiveness of the suggested strategy. In addition, the sub-models are fused using the bootstrap aggregating (Bagging) approach to boost accuracy. On this foundation, the temporal convolution network (TCN) is used to create a sub-model of SOH estimation for several typical kinds of segments. This study solves the problem by dividing the whole voltage curve into many typical kinds of segments with equal timescales based on different typical voltage beginning points. In reality, voltage, current, and temperature are frequently presented in segments, leading to the limited flexibility and slow analysis speed of the traditional techniques. However, the majority of approaches are based on entire voltage, current, or temperature curves. Nowadays, most research adopts a data-driven artificial intelligence approach to assess SOH. Research on the state of health (SOH) of batteries is essential for grasping the performance of batteries, better guiding battery health management, and avoiding safety mishaps caused by battery aging. Lithium-ion batteries are widely employed in industries and daily life. 2Guangdong Provincial Key Laboratory of Intelligent Measurement and Advanced Metering of Power Grid, Guangzhou, China.1School of Electric Power Engineering South China University of Technology, Guangzhou, China.Ning Yang 1,2, Tao Yu 1,2*, Qingquan Luo 1,2 and Keying Wang 1,2
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |