Elbows of Internal Resistance Rise Curves in Li-Ion Cells

The degradation of lithium-ion cells with respect to increases internal resistance (IR) has negative implications for rapid charging protocols, thermal management and power output cells. Despite this, IR receives much less attention than capacity in Li-ion cell research. Building on recent developments ‘knee’ identification curves, we propose the new concepts ‘elbow-point’ ‘elbow-onset’ rise a robust algorithm those variables. We report relations between capacity’s knees, IR’s elbows end life large dataset study. enhance our discussion two applications. use neural network techniques build independent state health predictor models achieving mean absolute percentage error (MAPE) 0.4% 1.6%, respectively, an overall root squared below 0.0061. A relevance vector machine, using first 50 cycles data, is employed early prediction elbow-points elbow-onsets MAPE 11.5% 14.0%, respectively.