Simulation of health assessment model for thermal management system of lithium-ion battery based on fuzzy clustering algorithm

Abstract

Considering the inadequate assessment of the factor decline index in the thermal management system for lithium-ion batteries, which has a negative impact on their efficient utilization, a fuzzy clustering algorithm is suggested to create a simulation model for evaluating the health of the lithium-ion battery thermal management system. In the process of restoring characteristic data by the fuzzy clustering algorithm, according to the characteristic parameters of energy signal and power signal, the decay characteristic results of the lithium-ion battery thermal management system are extracted. Taking the minimum attenuation as a reference, the evaluation function is calculated, the health trend of the lithium-ion battery thermal management system is evaluated, the health grade is established, and the health evaluation model of the lithium-ion battery thermal management system is constructed. The experimental results show that the prediction of the remaining service life of five kinds of lithium-ion batteries by this model is consistent with the actual value, and the average absolute error is always within 0.02, which is superior in health assessment.