Model Based Optimal Control Strategies for Lithium-Ion Batteries -Theoretical Analysis of Performance Gains

Battery Management Systems (BMS) monitor and control the energy flow of a battery in such a way that the energy is used optimally, while preventing damage and ensuring overall safety (1). For the BMS to function efficiently it is necessary to have knowledge of the internal states of the battery, which can be described by:  the State-of-Charge (SoC), the State-of-Health (SoH) and the remaining runtime (t_r). The accurate determination of these above mentioned parameters are critical for the optimal use of batteries and helps avoid over-engineered batteries.

Physics-based models (2, 3) that incorporate most of the transport and kinetic phenomena affecting the internal states of a lithium ion battery are in the form of coupled nonlinear partial differential equations (PDEs). While these models are accurate in terms of prediction capability, they cannot be employed for online control and monitoring purposes due to their huge computational expense. The reformulated model (4) is capable of predicting the internal states of battery with simulation times in the order of milliseconds without compromising on accuracy for the entire discharge period. This talk will demonstrate the use of the reformulated model for control-relevant real-time applications. Experiments will be performed at wide range of temperature (-17⁰ C to +30⁰ C) to obtain thermal dependence of transport and kinetics parameters. An experimentally validated, reformulated pseudo two dimensional model (4) will be used to derive optimal charging profiles at different temperatures.

Control strategies based on both (1) charging current alone with temperature as a constraint and (2) charging current and temperature/heat flux as a control will be analyzed aiming to quantify performance gains from the model based control strategies.

Acknowledgements

The work presented herein was funded in part by the Advanced Research Projects Agency – Energy (ARPA-E), U.S. Department of Energy, under Award Number DE-AR0000275.

References

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