A method based on fusion ofmultiple features is proposed to assess and accurately describe the performance degradation of lithiumion\nbatteries in this paper. First, the discharge voltage signal of lithium-ion batteries under real-time monitoring is analyzed from\nthe perspective of time domain and complexity to obtain the values ofmultiple features.Then, the multi-feature parameters undergo\na spectral regression process to reduce the number of dimensions and to eliminate redundancy, and on the basis of this regression,\na Gaussian mixture model is established to model the health state of batteries.Thus, the degree of lithium-ion battery performance\ndegradation can be quantitatively assessed using the Bayesian inference-based distance metric. A case calculation experiment is\ncarried out to verify the effectiveness of the method proposed in this paper.The experimental results demonstrate that, compared\nwith other assessment methods, the performance degradation assessment method proposed in this paper can be used to monitor\nthe degradation process of lithium-ion batteries more effectively and to improve the accuracy of condition monitoring of batteries,\nthereby providing powerful support for making maintenance decisions.
Loading....