Aging-Sensitive Fast-Charging for Heavy-Duty Electric Vehicles
Authors: Streb Moritz , Andersson Malin , Prathimala Venu Gopal , Löfqvist Klass Verena , Klett Matilda , Johansson Mikael , Lindbergh Göran 
Published: February 2024

To use lithium-ion cells on-board electric vehicles (EVs) safely and efficiently, a battery management system (BMS) is essential. It monitors the battery’s states and controls utilization by limiting e.g., current and temperature. Advanced BMS increasingly use electrochemical models to assess internal states of battery cells and apply usage constraints based on these [1]. The performance of an electrochemical BMS is closely tied to the performance of the underlying model and the accuracy of its parameters [2]. We employ a novel re-parametrization method to update electrochemically constrained optimal fast-charging procedure to minimize battery degradation. The parameters of electrochemical models are typically identified through a combination of physico-chemical characterization techniques and curve fitting [3]. Since model parameters change with aging [4], there is a need to re-parametrize electrochemical models on-board to conserve model accuracy. As basis for this re-parametrization, we propose a novel reference performance test that can be incorporated into a conventional over-night charge and performed intermittently.

Optimal control has previously been demonstrated for fast-charging in EV applications [1]. However, electrochemical, and mechanical degradation need to be considered to allow optimal fast charging throughout batteries’ lifetimes. Khalik et al. [5] demonstrated how a charging procedure could be designed a-priori for the entire cycle life, considering a direct implementation of the solid-electrolyte-interphase growth and capacity fade due to the associated lithium consumption. Such approaches can extend battery lifetime, but neither yield optimal charging-procedures at every state-of-health nor handle unknown aging modes on the fly. Our proposed approach involves intermittent identification of electrochemical model parameters and subsequent update of the fast-charging protocol such that it adheres to electrochemical constraints throughout the entire battery lifetime.

In this work, summarized in Figure 1, we present this methodology and show results from an experimental study testing the proposed approach vs. conventional charging procedures. The experimental study is performed on state-of-the art automotive cells used in heavy-duty electric vehicles.

Figure caption: Comparison of a conventional electrochemically constrained fast-charging procedure with the aging-sensitive approach proposed in the present work.

References

[1] Y. Li, D.M. Vilathgamuwa, E. Wikner, Z. Wei, X. Zhang, T. Thiringer, T. Wik, C. Zou, Electrochemical Model-Based Fast Charging: Physical Constraint-Triggered PI Control, IEEE Trans. Energy Convers. 36 (2021) 3208–3220. https://doi.org/10.1109/TEC.2021.3065983.

[2] A. Pozzi, D.M. Raimondo, Stochastic model predictive control for optimal charging of electric vehicles battery packs, J. Energy Storage. 55 (2022) 105332. https://doi.org/10.1016/j.est.2022.105332.

[3] M. Andersson, M. Streb, J.Y. Ko, V. Löfqvist Klass, M. Klett, H. Ekström, M. Johansson, G. Lindbergh, Parametrization of physics-based battery models from input–output data: A review of methodology and current research, J. Power Sources. 521 (2022) 230859. https://doi.org/10.1016/j.jpowsour.2021.230859.

[4] M. Streb, M. Andersson, V. Löfqvist Klass, M. Klett, M. Johansson, G. Lindbergh, Investigating re-parametrization of electrochemical model-based battery management using real-world driving data, ETransportation. 16 (2023) 100231. https://doi.org/10.1016/j.etran.2023.100231.

[5] Z. Khalik, H.J. Bergveld, M.C.F. Donkers, Ageing-Aware Charging of Lithium-ion Batteries Using an Electrochemistry-Based Model with Capacity-Loss Side Reactions, in: 2020 Am. Control Conf. ACC, IEEE, Denver, CO, USA, 2020: pp. 2213–2218. https://doi.org/10.23919/ACC45564.2020.9147404.

Figure 1