A novel based-performance degradation Wiener process model for real-time reliability evaluation of lithium-ion battery

Abstract

Real-time reliability evaluation of lithium-ion battery plays a vital role in guaranteeing the safety of energy storage system and its related products. However, it is difficult to predict and evaluate the remaining useful life and reliability of cell with accurate mathematical models, which is related to the complexity and variability of performance degradation during service. In this paper, a novel based-performance degradation Wiener process model is established based on battery degradation data and Bayesian updating algorithm. Firstly, three types of reliability evaluation models are constructed based on Wiener process degradation model, and the laboratory tests of 8 Lithium-ion cells (cylindrical 18650) are carried out to verify the validity and accuracy of the models, the results show that the binary random parameters evaluation model (BRPEM) is able to more accurately describe the degradation process of lithium-ion performance. Then, the Bayesian updating algorithm based on the BRPEM is employed to fuse the degradation data between 100 and 300 cycles of 5# cell in the test and real-time monitoring degradation data, the real-time reliability evaluation of the battery is realized. Finally, the results of life probability density function and reliability function show that the proposed model can achieve scientific and accurate reliability evaluation of Lithium-ion battery.