Incremental Capacity Analysis on Commercial Lithium-Ion Batteries using Support Vector Regression: A Parametric Study
Abstract
:1. Introduction
2. Experimental
3. Methodology
3.1. The Canonical Form of the Support Vector Regression
3.2. Double σ to Enhance the Quality of Curve Fitting
3.3. Criterion for Evaluating the Quality of Curve Fitting by SVR
3.4. Changing the Cost Functions to Improve the Accuracy of Incremental Capacity Analysis
4. Result and Discussions
4.1. The Influence of the Data Length on the Performances of the SVR Algorithm
4.2. The Influence of the σ in the Gaussian Kernel on the Performance of the SVR Algorithm
4.3. Double σ to Enhance the Accuracy of the SVR Algorithm
4.4. Changing the Cost Function to Improve the Accuracy of ICA Using the SVR Algorithm
4.5. ICA for Characterizing the Degradation of Lithium-ion Batteries Using the SVR Algorithm
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Cell | Cathode | Anode | Capacity (Ah) | Voltage (V) | Current | Institute | Refference |
---|---|---|---|---|---|---|---|
A | LFP | C | 1.1 | 3.0–3.55 | 1/2 C CHA | UoM | [35] |
B | NCM | C | 48 | 3.0–4.2 | 1/3 C CHA | THU | [26] |
C | LFP | C | 60 | 2.75–3.6 | 1/3 C CHA | THU | [26] |
D | NCM + LMO | C | 20 | 2.5–4.2 | 1/2 C DIS | THU | [36] |
Algorithm | Fitting Accuracy | y = f(x) | y’ = f’(x) | Further Aging ICA | |
---|---|---|---|---|---|
σ | Cost Function | ||||
Single σ | #1 | Fair | Explicit | Explicit | Not Recommended |
Single σ | #2 | Better | No | Explicit | Recommended |
Double σ | #1 | Good | Explicit | Explicit | Recommended |
Double σ | #2 | Better | No | Explicit | Recommended |
Cell | Cathode | SOH | Characteristic Peak | |||||||
---|---|---|---|---|---|---|---|---|---|---|
Reference IC (Linear Approximation) | Relative Error | |||||||||
SVR Single σ Cost Function #2 | SVR Double σ Cost Function #1 | SVR Double σ Cost Function #2 | ||||||||
Location /V | Height /V−1 | Location | Height | Location | Height | Location | Height | |||
A | LFP | 100% | 3.388 | 8.205 | 0% | −0.23% | +0.09% | −14.45% | 0% | +0.04% |
99.7% | 3.388 | 7.344 | +0.03% | +0.07% | +0.12% | −16.60% | +0.03% | −0.07% | ||
97.8% | 3.388 | 6.328 | +0.06% | +0.03% | +0.09% | −14.84% | +0.06% | −0.30% | ||
95.7% | 3.392 | 5.573 | +0.18% | −4.25% | 0% | −9.54% | +0.15% | −4.19% | ||
B | NCM | 100% | 3.655 | 3.953 | +0.03% | +1.24% | +0.08% | +3.92% | +0.03% | +2.93% |
97.6% | 3.655 | 3.731 | +0.05% | +2.68% | +0.08% | +4.90% | 0% | +3.03% | ||
90.5% | 3.660 | 3.563 | +0.08% | +0.93% | +0.11% | +4.15% | 0% | +0.28% | ||
78.8% | 3.675 | 3.117 | +0.03% | +0% | +0.05% | +2.44% | 0% | +0.19% | ||
C | LFP | 100% | 3.394 | 11.02 | +0.03% | +0.73% | +0.09% | +15.70% | +0.09% | +6.62% |
91.1% | 3.390 | 10.77 | +0.06% | +3.25% | +0.15% | −6.78% | +0.24% | −0.74% | ||
85.3% | 3.390 | 8.873 | +0.18% | +8.58% | +0.21% | −1.78% | +0.09% | +5.42% | ||
78.7% | 3.398 | 6.344 | −0.15% | +5.74% | 0% | −6.45% | −0.09% | −6.76% | ||
D | NCM+LMO | 100% | 3.990 | 1.875 | +0.23% | +1.39% | +0.13% | −0.32% | +0.28% | −2.29% |
95.5% | 3.990 | 1.931 | +0.20% | +0.73% | +0.13% | −1.40% | +0.25% | −1.50% | ||
93.3% | 3.990 | 1.823 | +0.18% | +1.43% | +0.25% | −1.26% | +0.25% | +0.66% | ||
79.8% | 3.916 | 1.670 | −0.08% | +0.72% | −0.38% | −2.51% | +0.20% | −0.30% |
Cell | Cathode | SOH | Integrated Area Near the Peak | SVR Single σ + Cost Function #2 Relative Error | SVR Double σ + Cost Function #1 Relative Error |
---|---|---|---|---|---|
A | LFP | 100% | [3.380, 3.400] V | +0.61% | −9.96% |
99.7% | [3.380, 3.400] V | −0.76% | −9.89% | ||
97.8% | [3.380, 3.400] V | −0.90% | −8.65% | ||
95.7% | [3.380, 3.400] V | +1.85% | −10.65% | ||
B | NCM | 100% | [3.620, 3.750] V | −0.34% | −0.15% |
97.6% | [3.620, 3.750] V | −0.52% | −0.14% | ||
90.5% | [3.620, 3.750] V | 0.39% | +0.10% | ||
78.8% | [3.620, 3.750] V | 0.68% | +0.21% | ||
C | LFP | 100% | [3.380, 3.410] V | +0.40% | +0.78% |
91.1% | [3.380, 3.410] V | −0.33% | −2.62% | ||
85.3% | [3.380, 3.410] V | −1.99% | −3.45% | ||
78.7% | [3.380, 3.410] V | −2.76% | −5.29% | ||
D | NCM+LMO | 100% | [3.910, 4.050] V | +0.49% | +0.04% |
95.5% | [3.910, 4.050] V | +0.25% | +0.19% | ||
93.3% | [3.910, 4.050] V | −0.14% | −0.21% | ||
79.8% | [3.880, 4.020] V | −0.82% | −0.31% |
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Feng, X.; Weng, C.; He, X.; Wang, L.; Ren, D.; Lu, L.; Han, X.; Ouyang, M. Incremental Capacity Analysis on Commercial Lithium-Ion Batteries using Support Vector Regression: A Parametric Study. Energies 2018, 11, 2323. https://doi.org/10.3390/en11092323
Feng X, Weng C, He X, Wang L, Ren D, Lu L, Han X, Ouyang M. Incremental Capacity Analysis on Commercial Lithium-Ion Batteries using Support Vector Regression: A Parametric Study. Energies. 2018; 11(9):2323. https://doi.org/10.3390/en11092323
Chicago/Turabian StyleFeng, Xuning, Caihao Weng, Xiangming He, Li Wang, Dongsheng Ren, Languang Lu, Xuebing Han, and Minggao Ouyang. 2018. "Incremental Capacity Analysis on Commercial Lithium-Ion Batteries using Support Vector Regression: A Parametric Study" Energies 11, no. 9: 2323. https://doi.org/10.3390/en11092323