Accelerated Test Verification of Cycle Life of Ternary Lithium Batteries
Different temperatures were selected as acceleration factors,and the inherent relationship between the cycle life decay was derived through capacity decay data.A method for accelerating test-ing and evaluating battery capacity decay was established.The specific process is as follows:1)Apply machine learning ridge regression method to fit the obtained data with cubic polynomial,quadratic poly-nomial,first-order polynomial,and different regularization forces,and determine the fitting equation suitable for the current data;2)Based on the Arrhenius model,an accelerated lifespan model was es-tablished to predict single point lifespan with the capacity retention rate corresponding to 500 and 1000 cycles of the battery as the lifespan feature.An accelerated lifespan model with quadratic polynomial coefficients as the lifespan feature was established to predict the lifespan at any point on the curve and validated.The experimental results indicate that the established accelerated life model can accurately predict the life of ternary lithium batteries,and has certain engineering application significance.
NETL
NSTL
万方数据
维普
