Journal
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
Volume 69, Issue 8, Pages 8055-8065Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIE.2021.3108715
Keywords
Batteries; Estimation; Computational modeling; Sensors; Battery charge measurement; Aging; Current measurement; Balancing current ratio (BCR); electric vehicle; lithium-ion battery pack; state-of-health (SoH) estimation
Categories
Funding
- Guangdong Scientific and Technological Project [2017B010120002]
- Guangzhou Scientific and Technological Project [202002030323]
- Hong Kong Research Grants Council CERG project [16207717, 16208520]
- High Value Manufacturing Catapult [160080 CORE]
- Shenzhen Science and Technology Innovation Commission under the Grant Shenzhen-Hong Kong Innovation Circle Category D Project [SGDX 2019081623240948]
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This article proposes a solution based on balancing current ratio to estimate the state-of-health (SoH) of all cells within a battery pack. By incorporating voltage-based active balancing, the proposed solution achieves lower estimation error and improved robustness.
The inevitable battery ageing is a bottleneck that hinders the advancement of battery-based energy storage systems. Developing a feasible health assessment strategy for battery pack is important but challenging due to the joint requirements of the computational burden, modeling cost, estimation accuracy, and battery equalization. This article proposes a balancing current ratio (BCR) based solution to achieve reliable state-of-health (SoH) estimations of all series-connected cells within a pack while significantly reduce the overall reliance on cell-level battery models. Specifically, after employing BCR to describe the properties of the balancing process, the voltage-based active balancing is combined into the SoH estimator design for the first time, leading to a weighted fusion strategy to effectively estimate SoHs of all cells within a pack. Hardware-in-the-loop experiments show that even if a parameter-fixed open-circuit-voltage-resistance model is used for modeling, the typical estimation error of our proposed solution can still be bounded by only 1.5%, which is 70% lower than that of the benchmarking algorithms. Due to the model-free nature of the integrated voltage-based balancing, the robustness and flexibility of the proposed pack SoH estimation solution are also significantly improved.
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