Accurate and Efficient Estimation of Lithium-Ion Battery State of Charge with Alternate Adaptive Extended Kalman Filter and Ampere-Hour Counting Methods
Abstract
:1. Introduction
2. Battery Model and Parameters Identification
2.1. Battery Model
2.2. Parameters Identification
3. AHI Method, AEKF Method, and Alternate Method
3.1. AHI Method
3.2. AEKF Method
- Update the state and error covariance matrix at the step k by using the state and error covariance matrix at the step (k−1) (k = 2, 3 ...):
- Update the Kalman filter gain matrix calculation formula by:
- Update the state and error covariance matrix at the step k with the output error by:
- The mean and covariance of the process noise and the observed noise are given by:
3.3. Alternate Method
3.3.1. AEKF Switching to AHI
3.3.2. AHI Switching to AEKF
4. Experimental Results
4.1. Influence of Current and Voltage Measurement Errors on SOC Estimation
4.2. Comparisons of Different SOC Estimation Methods under the NEDC Condition
5. Conclusions
Author Contributions
Acknowledgments
Conflicts of Interest
References
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Battery Chemistry | LMO-LNO/Graphite |
---|---|
Nominal capacity (Ah) | 130 |
Upper cut-off voltage (V) | 4.2 |
Lower cut-off voltage (V) | 2.5 |
Voltage (mV) | −25 | −20 | −15 | −10 | −5 | 0 | 5 | 10 | 15 | 20 | 25 |
Current (%) | −25 | −20 | −15 | −10 | −5 | 0 | 5 | 10 | 15 | 20 | 25 |
Estimation group | Figure number | Voltage drift (mV) | Current drift (%) |
---|---|---|---|
1 | Figure 13a,b | +6 | −8 |
2 | Figure 13c,d | +6 | +8 |
3 | Figure 13e,f | −6 | −8 |
4 | Figure 13g,h | −6 | +8 |
Estimation group | Estimation method | MAE (%) | MAXE (%) | RMSE (%) | STDE (%) | Calculation time (s) |
---|---|---|---|---|---|---|
1 | AHI | 3.54 | 7.25 | 4.10 | 2.07 | 10.00 |
1 | AEKF | 1.49 | 3.77 | 1.74 | 0.89 | 49.00 |
1 | Alt | 2.68 | 3.68 | 2.74 | 0.54 | 12.00 |
2 | AHI | 3.53 | 7.24 | 4.09 | 2.07 | 10.00 |
2 | AEKF | 1.00 | 2.69 | 1.18 | 0.63 | 49.00 |
2 | Alt | 1.12 | 2.69 | 1.28 | 0.63 | 11.00 |
3 | AHI | 3.54 | 7.25 | 4.10 | 2.07 | 10.00 |
3 | AEKF | 1.02 | 2.99 | 1.19 | 0.61 | 49.00 |
3 | Alt | 1.17 | 3.48 | 1.49 | 0.91 | 12.00 |
4 | AHI | 3.53 | 7.24 | 4.09 | 2.07 | 10.00 |
4 | AEKF | 1.79 | 4.47 | 2.23 | 1.32 | 49.00 |
4 | Alt | 3.25 | 4.56 | 3.41 | 1.03 | 11.00 |
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Liu, Z.; Li, Z.; Zhang, J.; Su, L.; Ge, H. Accurate and Efficient Estimation of Lithium-Ion Battery State of Charge with Alternate Adaptive Extended Kalman Filter and Ampere-Hour Counting Methods. Energies 2019, 12, 757. https://doi.org/10.3390/en12040757
Liu Z, Li Z, Zhang J, Su L, Ge H. Accurate and Efficient Estimation of Lithium-Ion Battery State of Charge with Alternate Adaptive Extended Kalman Filter and Ampere-Hour Counting Methods. Energies. 2019; 12(4):757. https://doi.org/10.3390/en12040757
Chicago/Turabian StyleLiu, Zhongxiao, Zhe Li, Jianbo Zhang, Laisuo Su, and Hao Ge. 2019. "Accurate and Efficient Estimation of Lithium-Ion Battery State of Charge with Alternate Adaptive Extended Kalman Filter and Ampere-Hour Counting Methods" Energies 12, no. 4: 757. https://doi.org/10.3390/en12040757