Optimal Fast Charging of Lithium Ion Batteries: Between Model-Based and Data-Driven Methods

Abstract

Delivering lithium ion batteries capable of fast charging without suffering from accelerated degradation is an important milestone for transport electrification. Recently, there has been growing interest in applying data-driven methods for optimising fast charging protocols to avoid accelerated battery degradation. However, such data-driven approaches suffer from a lack of robustness, explainability, and generalisability, which has hindered their wide-spread use in practice. To address this issue, this paper proposes a method to interpret the fast charging protocols of data-driven algorithms as the solutions of a model-based optimal control problem. This hybrid approach combines the power of data-driven methods for predicting battery degradation with the flexibility and optimality guarantees of the model-based approach. The results highlight the potential of the proposed hybrid approach for generating fast charging protocols. In particular, for fast charging to 80% state-of-charge in 10 minutes, the proposed approach was predicted to increase the cycle life from 912 to 1078 cycles when compared against a purely data-driven approach.