Life Prediction of Large Lithium-Ion Battery Packs with Active and Passive Balancing

Conference · Mon Jul 03 04:00:00 EDT 2017

DOI:https://doi.org/10.23919/ACC.2017.7963682· OSTI ID:1378881

Shi, Ying ^[1]; Smith, Kandler A ^[1]; Zane, Regan ^[2]; Anderson, Dyche ^[3]

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1. National Renewable Energy Laboratory (NREL), Golden, CO (United States)
2. Utah State University
3. Ford Motor Company

Lithium-ion battery packs take a major part of large-scale stationary energy storage systems. One challenge in reducing battery pack cost is to reduce pack size without compromising pack service performance and lifespan. Prognostic life model can be a powerful tool to handle the state of health (SOH) estimate and enable active life balancing strategy to reduce cell imbalance and extend pack life. This work proposed a life model using both empirical and physical-based approaches. The life model described the compounding effect of different degradations on the entire cell with an empirical model. Then its lower-level submodels considered the complex physical links between testing statistics (state of charge level, C-rate level, duty cycles, etc.) and the degradation reaction rates with respect to specific aging mechanisms. The hybrid approach made the life model generic, robust and stable regardless of battery chemistry and application usage. The model was validated with a custom pack with both passive and active balancing systems implemented, which created four different aging paths in the pack. The life model successfully captured the aging trajectories of all four paths. The life model prediction errors on capacity fade and resistance growth were within +/-3% and +/-5% of the experiment measurements.

• Research Organization: National Renewable Energy Laboratory (NREL), Golden, CO (United States)
• Sponsoring Organization: U.S. Department of Energy, Advanced Research Projects Agency-Energy (ARPA-E)
• DOE Contract Number: AC36-08GO28308
• OSTI ID: 1378881
• Report Number(s): NREL/CP-5400-68030
• Country of Publication: United States
• Language: English

Related Subjects

25 ENERGY STORAGE
active life balancing strategy
battery chemistry
capacity fade
life prediction
lithium-ion batteries
prognostic life model
resistance growth
state of health estimate