Closed-Loop Optimization of Battery Fast Charging Procedures

Wednesday, 6 March 2019
Areas Adjacent to the Forum (Scripps Seaside Forum)
P. Attia, A. Grover, N. Jin (Stanford University), K. Severson (Massachusetts Institute of Technology), B. Cheong, J. Liao, M. H. Chen, N. Perkins, Z. Yang (Stanford University), P. H. Herring, M. Aykol (Toyota Research Institute), S. J. Harris (LBNL), R. D. Braatz (Massachusetts Institute of Technology), S. Ermon (Stanford University), and W. C. Chueh (Materials Science & Engineering, Stanford University)
Fast charging protocols for lithium-ion batteries are critical for widespread adaptation of electric vehicles. However, a limited understanding of degradation modes during fast charging and the large manufacturing variability of commercial lithium-ion batteries are major challenges to the development of high-performing fast charging protocols. In this work, we optimize a six-step charging protocol for commercial 18650 lithium-ion batteries that achieves 80% state of charge in ten minutes. We employ two key elements to reduce the optimization cost: early prediction of failure, which uses cycling data from the first 100 cycles to predict cycle lives that reach up to 1200 cycles, and adaptive Bayesian optimal experimental design, which reduces the number of experiments required. We identify promising fast charging protocols with identical charging times but high lifetimes out of a candidate pool of 224 protocols. This method can be extended to accelerate development of other tasks in battery manufacturing and deployment, such as formation cycling and state-of-health estimation.