Design and Optimization of a Novel Microchannel Battery Thermal Management System Based on Digital Twin
Abstract
:1. Introduction
2. The Microchannel Battery Thermal Management System and Digital Twin-Based Design
2.1. Introduction and Analysis of the Microchannel Battery Thermal Management System
2.2. Digital Twin-Based Design of the Microchannel Battery Thermal Management System
3. Virtual Calculation and Simulation Model
3.1. Governing Equations of the Digital Twin Virtual Model
3.2. Cell Heat Generation of the Digital Twin Virtual Model
- (a)
- The material of the cell is evenly distributed and isotropic.
- (b)
- The material property will not change with the temperature and SOC (state of charge).
- (c)
- The heat source is distributed uniformly in all of the areas of the cell.
3.3. Initial and Boundary Conditions of the Digital Twin Virtual Model
3.4. Experiment and Validation of the Digital Twin Virtual Model
4. Digital Twin Virtual Model Based Optimization of the BTMS
4.1. Gaussian Process Regression of the Digital Twin Virtual Model Based Optimization
4.2. Orthogonal Design of the Digital Twin Virtual Model Based Optimization
4.3. NSGA-II Method of the Digital Twin Virtual Model Based Optimization
5. Results and Discussions
5.1. Streamline Analysis of Microchannel Structure
5.2. Orthogonal Analysis Based on Digital Twin Virtual Model
5.3. Gaussian Process Regression Analysis Based on Digital Twin Virtual Model
5.4. Multi-Objective Optimization and Comparison Based on Digital Twin Virtual Model
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
Num | Factors | Test Index | Num | Factors | Test Index | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
d1 | d2 | l | V | E1 | E2 | Tmax | ΔT | d1 | d2 | l | V | E1 | E2 | Tmax | ΔT | ||
1 | 2 | 0 | 4 | 0.8 | 1 | 1 | 35.22 | 9.07 | 14 | 3 | 3 | 8 | 0.8 | 2 | 2 | 42.1 | 15.84 |
2 | 2 | 1 | 6 | 1.4 | 5 | 2 | 34.27 | 8.5 | 15 | 3 | 4 | 5 | 1.4 | 1 | 3 | 44.75 | 17.8 |
3 | 2 | 2 | 8 | 1 | 4 | 3 | 49.57 | 23.1 | 16 | 3.5 | 0 | 6 | 1.6 | 2 | 3 | 33.79 | 7.7 |
4 | 2 | 3 | 5 | 1.6 | 3 | 4 | 51.23 | 24.48 | 17 | 3.5 | 1 | 8 | 1.2 | 1 | 4 | 32.62 | 6.43 |
5 | 2 | 4 | 7 | 1.2 | 2 | 5 | 53.11 | 16.18 | 18 | 3.5 | 2 | 5 | 0.8 | 5 | 5 | 36.58 | 10.15 |
6 | 2.5 | 0 | 8 | 1.4 | 3 | 5 | 33.25 | 7.47 | 19 | 3.5 | 3 | 7 | 1.4 | 4 | 1 | 32.15 | 6.47 |
7 | 2.5 | 1 | 5 | 1 | 2 | 1 | 33.26 | 7.15 | 20 | 3.5 | 4 | 4 | 1 | 3 | 2 | 42.47 | 15.56 |
8 | 2.5 | 2 | 7 | 1.6 | 1 | 2 | 36.75 | 10.69 | 21 | 4 | 0 | 5 | 1.2 | 4 | 2 | 34.93 | 8.65 |
9 | 2.5 | 3 | 4 | 1.2 | 5 | 3 | 45.95 | 19.15 | 22 | 4 | 1 | 7 | 0.8 | 3 | 3 | 35.5 | 9.2 |
10 | 2.5 | 4 | 6 | 0.8 | 4 | 4 | 42.63 | 16.06 | 23 | 4 | 2 | 4 | 1.4 | 2 | 4 | 34.15 | 7.61 |
11 | 3 | 0 | 7 | 1 | 5 | 4 | 34.75 | 8.73 | 24 | 4 | 3 | 6 | 1 | 1 | 5 | 36.61 | 9.98 |
12 | 3 | 1 | 4 | 1.6 | 4 | 5 | 30.95 | 4.88 | 25 | 4 | 4 | 8 | 1.6 | 5 | 1 | 38.3 | 11.6 |
13 | 3 | 2 | 6 | 1.2 | 3 | 1 | 35.71 | 9.69 |
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Parameter | Rated Voltage (V) | Rated Capacity (mAh) | Cut-Off Voltage (V) | Mass (kg) | Dimension (mm) |
---|---|---|---|---|---|
Value | 3.7 | 10,000 | 3.0–4.2 | 0.23 | 132 × 67 × 12 |
Materials | Thermal Conductivity (W/m·K) | Density (kg/m3) | Specific Heat (J/kg·K) |
---|---|---|---|
Cell body | 3.27 | 2543.92 | 1679 |
Copper (negative pole) | 388 | 8978 | 381 |
Aluminum (positive pole) | 202 | 2719 | 871 |
Discharge Rate | 1 C | 2 C | 3 C |
---|---|---|---|
Maximum temperature (°C) | 27.8 | 31.3 | 34.5 |
Temperature deviation (°C) | 0.7 | 0.9 | 0.1 |
Index | Factors | |||
---|---|---|---|---|
d1 | d2 | l | V | |
RTmax | 9.158 | 10.932 | 3.548 | 4.75 |
RΔT | 9.004 | 10.208 | 3.26 | 4.45 |
MSj(Tmax) | 68.17 | 108.07 | 9.14 | 15.47 |
Fj(Tmax) | 4.47 | 7.09 | \ | \ |
MSj(ΔT) | 67.28 | 95.00 | 8.36 | 13.48 |
Fj(ΔT) | 4.92 | 6.95 | \ | \ |
Significance 1 | *** | **** | * | ** |
F(4,16) | α0.005 = 5.64 | α0.01 = 4.77 | ||
α0.025 = 3.73 | α0.05 = 3.01 |
Parameter | d1 | d2 | l | V | Tmax | ΔT |
---|---|---|---|---|---|---|
Initial structure | 2 | 0 | 4 | 0.8 | 35.2 | 9.07 |
Orthogonal optimization | 3.5 | 1 | 6 | 1.4 | 31.8 | 5.76 |
Gaussian regression optimization | 3.14 | 0.8 | 6.2 | 1.6 | 30.6 | 4.68 |
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Xu, Z.; Xu, J.; Guo, Z.; Wang, H.; Sun, Z.; Mei, X. Design and Optimization of a Novel Microchannel Battery Thermal Management System Based on Digital Twin. Energies 2022, 15, 1421. https://doi.org/10.3390/en15041421
Xu Z, Xu J, Guo Z, Wang H, Sun Z, Mei X. Design and Optimization of a Novel Microchannel Battery Thermal Management System Based on Digital Twin. Energies. 2022; 15(4):1421. https://doi.org/10.3390/en15041421
Chicago/Turabian StyleXu, Ziming, Jun Xu, Zhechen Guo, Haitao Wang, Zheng Sun, and Xuesong Mei. 2022. "Design and Optimization of a Novel Microchannel Battery Thermal Management System Based on Digital Twin" Energies 15, no. 4: 1421. https://doi.org/10.3390/en15041421