Online Multi Chemistry SoC Estimation Technique Using Data Driven Battery Model Parameter Estimation †
Abstract
:1. Introduction
2. Data Driven Battery Models
2.1. Battery Models
2.2. Parameter Identification Method
3. Methods
3.1. Cell Specifications and Testing
3.2. Validation Process
4. Results and Discussion
4.1. Comparison of the Battery Model Electrical Performance
4.2. State of Charge Estimation
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Appendix A
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NMC | LFP | LTO | |
---|---|---|---|
Cathode Material | Li(NiCoMn)O | LiFePO | NiCoMn |
Nominal Capacity | 20 Ah | 14 Ah | 5 Ah |
Nominal Voltage | 3.65 V | 3.2 V | 2.2 V |
Charging/Discharging cut-off voltage | 4.15 V/2.5 V | 3.65V/2.0V | 2.80 V/1.50 V |
Energy Density | 174 Wh/kg | 120 Wh/kg | 42 Wh/kg |
Power Density * | 2300 W/kg | 2500 W/kg | 2250 W/kg |
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De Sutter, L.; Nikolian, A.; Timmermans, J.-M.; Omar, N.; Van Mierlo, J. Online Multi Chemistry SoC Estimation Technique Using Data Driven Battery Model Parameter Estimation. World Electr. Veh. J. 2018, 9, 16. https://doi.org/10.3390/wevj9020016
De Sutter L, Nikolian A, Timmermans J-M, Omar N, Van Mierlo J. Online Multi Chemistry SoC Estimation Technique Using Data Driven Battery Model Parameter Estimation. World Electric Vehicle Journal. 2018; 9(2):16. https://doi.org/10.3390/wevj9020016
Chicago/Turabian StyleDe Sutter, Lysander, Alexandros Nikolian, Jean-Marc Timmermans, Noshin Omar, and Joeri Van Mierlo. 2018. "Online Multi Chemistry SoC Estimation Technique Using Data Driven Battery Model Parameter Estimation" World Electric Vehicle Journal 9, no. 2: 16. https://doi.org/10.3390/wevj9020016