Accounting for Probabilistic Uncertainties in Fast Charging of Lithium-ion Batteries

Concetti Chiave

Uncertainty in ambient temperature and battery model parameters can lead to violations of voltage, temperature, and lithium-plating constraints during fast charging, necessitating adjustments to charging protocols to ensure reliable and safe operation.

Sintesi

The study analyzes the impact of uncertainty on battery degradation during fast charging using the porous electrode theory (PET) model, which captures various internal phenomena of a lithium-ion battery. The authors apply non-intrusive polynomial chaos expansion (PCE) to quantify the effects of uncertainty in the ambient temperature and 23 PET model parameters on the voltage, temperature, and lithium-plating overpotential during a constant current-constant voltage (CC-CV) charging protocol.
The key findings are:

Uncertainty in ambient temperature can result in violations of the voltage and temperature constraints, leading to accelerated battery degradation or premature charge termination.
Among the 24 uncertain parameters, 11 key parameters were identified that significantly impact the fast charging conditions.
The authors demonstrate that by adjusting the C-rate and charging constraints, the probability of violating the degradation constraints can be kept below a pre-specified value.

The PCE-based approach provides a computationally efficient way to quantify the statistical information of the quantities of interest and identify the critical parameters, enabling the design of fast charging protocols that explicitly account for probabilistic uncertainties.

Statistiche

The nominal model indicates that the charging should be switched to CV mode in about 711 seconds when the voltage reaches the maximum of 4.1 V.
The upper bound of the voltage confidence interval reaches the maximum voltage at about 550 seconds.
The nominal temperature rises to 311.4 K during charging, which does not reach the accelerated degradation condition of 313.15 K, but the confidence interval exceeds this temperature from about 530 to 930 seconds.
Reducing the C-rate from 2.2C to 2.0C increases the total charging time from 1086.2 seconds to 1204.8 seconds, but avoids accelerated degradation.

Citazioni

"Uncertainty propagation in 2.2C CC-CV charging indicates that degradation is accelerated by voltage, or charging is prematurely terminated by reaching temperature constraints."
"Our results indicate that uncertainty during charging should be considered to minimize battery performance degradation."

Approfondimenti chiave tratti da

Accounting for the Effects of Probabilistic Uncertainty During Fast Charging of Lithium-ion Batteries

by Minsu Kim,Jo... alle arxiv.org 05-06-2024

https://arxiv.org/pdf/2405.01681.pdf

Domande più approfondite

How can the proposed uncertainty-aware charging protocol be extended to account for time-varying ambient conditions and dynamic load profiles in real-world applications?

To extend the uncertainty-aware charging protocol to accommodate time-varying ambient conditions and dynamic load profiles, a dynamic model that incorporates these variations would be necessary. This model could include real-time data acquisition systems to continuously monitor ambient temperature and load profiles. By integrating this real-time data into the charging protocol, adjustments can be made on-the-fly to optimize charging parameters and ensure that operational constraints are met under varying conditions. Additionally, machine learning algorithms could be employed to predict future ambient conditions and load profiles, allowing for proactive adjustments to the charging strategy.

What are the potential tradeoffs between fast charging, battery degradation, and energy efficiency when considering probabilistic uncertainties?

When considering probabilistic uncertainties in fast charging, there are several tradeoffs to be mindful of. Fast charging typically leads to increased battery degradation due to higher operating temperatures and stresses on the battery materials. While fast charging improves convenience, it can reduce the overall lifespan of the battery. Energy efficiency may also be compromised during fast charging, as higher charging currents can lead to energy losses in the form of heat. When probabilistic uncertainties are factored in, the tradeoffs become more pronounced as variations in ambient conditions and model parameters can impact the balance between fast charging, degradation, and energy efficiency. Striking the right balance requires careful optimization and tradeoff analysis to ensure optimal performance under uncertain conditions.

How can the insights from this study on critical parameters be leveraged to guide the design and optimization of lithium-ion battery materials and cell architectures?

The insights gained from identifying critical parameters that significantly impact battery degradation during fast charging can be instrumental in guiding the design and optimization of lithium-ion battery materials and cell architectures. By focusing on these key parameters, researchers and engineers can prioritize efforts to improve the performance and longevity of batteries. For instance, targeted research can be conducted to enhance the thermal management systems of batteries to mitigate the impact of ambient temperature variations. Additionally, material scientists can explore new electrode compositions or electrolytes that are less sensitive to the identified critical parameters. Cell architectures can also be optimized to better accommodate the variability in these parameters, leading to more robust and reliable battery designs. Overall, leveraging these insights can drive innovation in battery technology and pave the way for more efficient and durable energy storage solutions.