Model Predictive Control for Lithium-Ion Battery Optimal Charging
Artikel i vetenskaplig tidskrift, 2018

Charging time and lifetime are important performances for lithium-ion (Li-ion) batteries, but are often competing objectives for charging operations. Model-based charging controls are challenging due to the complicated battery system structure that is composed of nonlinear partial differential equations and exhibits multiple time-scales. This paper proposes a new methodology for battery charging control enabling an optimal tradeoff between the charging time and battery state-of-health (SOH). Using recently developed model reduction approaches, a physics-based low-order battery model is first proposed and used to formulate a model-based charging strategy. The optimal fast charging problem is formulated in the framework of tracking model predictive control (MPC). This directly considers the tracking performance for provided state-of-charge and SOH references, and explicitly addresses constraints imposed on input current and battery internal state. The capability of this proposed charging strategy is demonstrated via simulations to be effective in tracking the desirable SOH trajectories. By comparing with the constant-current constant-voltage charging protocol, the MPC-based charging appears promising in terms of both the charging time and SOH. In addition, this obtained charging strategy is practical for real-time implementation.

Battery fast charging

Lithium-ion battery

state-of-health (SOH)

model predictive control (MPC)

state-of-charge (SOC)


Changfu Zou

Chalmers, Elektroteknik, System- och reglerteknik, Reglerteknik

Chris Manzie

University of Melbourne

Dragan Nesic

University of Melbourne

IEEE/ASME Transactions on Mechatronics

1083-4435 (ISSN)

Vol. 23 947-957




Datavetenskap (datalogi)