With the development of the times and the progress of science and technology, new energy vehicles have been widely promoted due to their many advantages such as energy conservation, environmental protection, and policy support. Now more and more people choose to buy new energy vehicles. New energy vehicles not only meet the daily travel needs of people, but also play an important role in protecting the natural environment and reducing exhaust emissions. The battery end plate of new energy vehicles generally chooses aluminum alloy, which has a long service life, excellent flame retardant, smokeless, non-toxic, explosion-proof and anti-aging properties. Through the development and research of battery end plates, production can be expanded more reasonably and the speed of technology research and development can be improved.
The traditional low-pressure casting process can flexibly adjust the pouring pressure and filling speed to ensure the smooth filling of the molten metal, so that the castings produced by low-pressure casting have a smooth surface, dense structure, excellent mechanical properties, and are economical and efficient. However, the low-pressure casting process involves many process parameters, and due to people’s increasing pursuit of aesthetics, the design of some parts is becoming more and more complex. Therefore, in the absence of an optimization method, it is difficult for researchers to obtain reasonable process parameters.
In response to the above problems, this paper takes the aluminum alloy battery end plate of a new energy vehicle as the research object, uses ProCAST software to conduct numerical simulation analysis of its low-pressure casting process, and conducts multi-objective optimization of process parameters based on orthogonal experiments and signal-to-noise ratio analysis, aiming to obtain a set of standardized process design parameters to provide an important reference for the research and actual production of the low-pressure casting process of aluminum alloy battery end plates for new energy vehicles.
1. Initial Process Analysis
1.1 Establishment of the Numerical Simulation Model
The three-dimensional model of the end plate with the pouring system is shown in Figure 1. The battery end plate has a rectangular structure with a maximum contour size of 558 mm × 244 mm × 40 mm, a volume of 0.003 m³, and a mass of 7.3 kg. The overall shape is relatively regular, the wall thickness is relatively uniform, and the average wall thickness is 31 mm. Four slag traps are added to the casting to facilitate the solidification and feeding of the surrounding areas. The design requirements of the low-pressure casting pouring system are to ensure the stable filling of the molten metal in the cavity of the casting, avoid any splashing and eddy currents, and be able to achieve sequential solidification to obtain the best feeding effect. Therefore, a bottom-pouring single-sided runner pouring method is adopted, the appropriate gate location is selected, and the number of gates is determined. The three-dimensional model with the pouring system is established using the CATIA modeling software, and then the model is imported into the MESH module of PROCAST for mesh division.
1.2 Material and Process Parameter Settings
The material of the battery end plate is A356 aluminum alloy, and its thermophysical parameters are shown in Table 1. The mold material is H13 steel. According to Pascal’s principle and empirical formulas, the pressure curve during the process is set as shown in Figure 2. After comparing the results of multiple simulations, the initial pouring temperature is selected as 710 °C, and the mold preheating temperature is 330 °C. The heat transfer coefficient between the casting, the pouring system, and the mold is set as 2000 W/(m²·K), and the heat transfer coefficient between the mold and the atmosphere is set as 10 W/(m²·K).
| Density / (kg·m³) | Liquidus Temperature / °C | Solidus Temperature / °C | Latent Heat / (kJ·kg⁻¹) | Thermal Conductivity / (W·m²·K) |
|---|---|---|---|---|
| 2430 | 630 | 568 | 430.518 | 70 |
2. Low Pressure Casting Process Parameter Optimization
The process parameters of the low-pressure casting process mainly include the lifting pressure, lifting time, filling pressure, filling time, pouring temperature, and mold preheating temperature. Different combinations of process parameters have a huge impact on the forming quality of the battery end plate, but due to the different values of each parameter, various parameter combinations need to be considered. In this paper, the orthogonal experiment method is used to select three process parameters: pouring temperature, mold preheating temperature, and filling time, and a three-factor and four-level experimental scheme is set, as shown in Table 2.
The evaluation indicators include the volume value of shrinkage porosity, solidification time, and the size of the secondary dendrite spacing. Shrinkage porosity defects are an important factor affecting the mechanical properties and fatigue life of castings. When the volume value of shrinkage porosity at a certain point of the casting is greater than 1, shrinkage porosity defects will occur at that point, and the larger the volume value, the greater the defect. The actual production efficiency of the casting will be affected by the solidification time. The shorter the solidification time, the higher the production efficiency. The solidification time of the casting is closely related to the size of the secondary dendrite spacing. The faster the solidification speed of the molten metal, the better the performance of the casting, and the smaller the secondary dendrite spacing. Therefore, in actual production, the alloy performance can be improved and enhanced by appropriately shortening the solidification time.
| Level | Pouring Temperature / °C | Mold Preheating Temperature / °C | Filling Time / s |
|---|---|---|---|
| 1 | 690 | 330 | 8 |
| 2 | 700 | 340 | 10 |
| 3 | 710 | 350 | 12 |
| 4 | 720 | 360 | 14 |
The concept of “signal-to-noise ratio” is an evaluation parameter introduced by Dr. Taguchi Genichi in the Taguchi experiment method to measure the goodness of the combination of parameters. It has three types of quality characteristics: larger is better, smaller is better, and nominal is best. In this paper, by optimizing the low-pressure casting process parameters of the battery end plate, the smallest volume value of shrinkage porosity and the secondary dendrite spacing, as well as the shortest solidification time, are obtained. Therefore, the “smaller is better” characteristic is adopted, and the calculation formula is as follows:
S / N = -10 log (1 / m ∑_(i = 1)^m y_i²)
where y is the test value of a certain evaluation indicator of the casting in the i-th experiment, and m is the number of experiments for this factor combination (in this paper, m = 1).
Using the orthogonal table L₁₆ (4³), based on the ProCAST software, the test values of the volume value of shrinkage porosity, the secondary dendrite spacing, and the solidification time are obtained, and their signal-to-noise ratios are calculated according to the above formula (1), and the final results are shown in Table 3.
2.1 Mean and Range Analysis
Through the results of the above experiments, the mean and range analysis of the signal-to-noise ratios of the three evaluation indicators is carried out to compare the influence weights of each factor on the evaluation indicators and formulate the optimal combination of process parameters, as shown in Table 4.
It can be seen from the mean and range analysis table that the influence of the three factors on the volume value of shrinkage porosity is: filling time > pouring temperature > mold preheating temperature (i.e., C > A > B). According to the optimal level of each factor, the process combination scheme to obtain the smallest volume value of shrinkage porosity is A4B3C3 (Scheme 1). The factor that has the greatest impact on the secondary dendrite spacing is the mold preheating temperature, and the optimal level of the mold preheating temperature is B1; followed by the filling time, and the optimal level of the filling time is C4; the pouring temperature has the least impact on the secondary dendrite spacing, and its optimal level is A4. According to the optimal level of each factor, the process combination scheme to obtain the smallest secondary dendrite spacing is A4B1C4 (Scheme 2). The factor that has the greatest impact on the solidification time is the mold preheating temperature, followed by the pouring temperature, and the filling time has the least impact on the solidification time. According to the optimal level of each factor, the process combination scheme to obtain the optimal solidification time is A1B1C1 (Scheme 3).
In addition, it is noted that in the orthogonal experiment table 3, the shrinkage porosity test value of the 12th group is 0. In the actual casting process, the first requirement of the process scheme is to ensure that the casting does not have shrinkage porosity defects. According to the analysis of the impact of different choices of process parameters on the evaluation results of shrinkage porosity, this process combination is the optimal one. Therefore, the process combination A3B4C2 is taken as Scheme 4 for comparison.
| Experiment Number | Test Results | Volume Value of Shrinkage Porosity / cm³ | Secondary Dendrite Spacing / μm | Solidification Time / s | |||||
|---|---|---|---|---|---|---|---|---|---|
| A | B | C | Test Value | Signal-to-Noise Ratio | Test Value | Signal-to-Noise Ratio | Test Value | Signal-to-Noise Ratio | |
| 1 | 690 | 330 | 8 | 0.830 | 1.618 | 43.94 | -32.857 | 140.6 | -42.960 |
| 2 | 690 | 340 | 10 | 0.837 | 1.545 | 44.93 | -33.051 | 148.2 | -43.417 |
| 3 | 690 | 350 | 12 | 0.630 | 4.013 | 45.45 | -33.151 | 156.8 | -43.907 |
| 4 | 690 | 360 | 14 | 0.633 | 3.972 | 46.39 | -33.328 | 166.2 | -44.413 |
| 5 | 700 | 330 | 10 | 0.835 | 1.566 | 44.42 | -32.952 | 142.6 | -43.082 |
| 6 | 700 | 340 | 8 | 0.841 | 1.504 | 44.93 | -33.051 | 149.1 | -43.470 |
| 7 | 700 | 350 | 14 | 0.633 | 3.972 | 45.91 | -33.238 | 159.7 | -44.066 |
| 8 | 700 | 360 | 12 | 0.633 | 3.972 | 46.80 | -33.405 | 167.3 | -44.470 |
| 9 | 710 | 330 | 12 | 0.628 | 4.041 | 47.33 | -33.503 | 145.8 | -43.275 |
| 10 | 710 | 340 | 14 | 0.632 | 3.986 | 45.42 | -33.145 | 153.7 | -43.733 |
| 11 | 710 | 350 | 8 | 0.632 | 3.986 | 45.89 | -33.234 | 158.7 | -44.012 |
| 12 | 710 | 360 | 10 | 0.000 | 46.83 | -33.410 | 169.1 | -44.563 | |
| 13 | 720 | 330 | 14 | 0.629 | 4.027 | 37.25 | -31.423 | 148.0 | -43.405 |
| 14 | 720 | 340 | 12 | 0.634 | 3.958 | 45.43 | -33.147 | 155.0 | -43.807 |
| 15 | 720 | 350 | 10 | 0.632 | 3.986 | 45.93 | -33.242 | 161.8 | -44.180 |
| 16 | 720 | 360 | 8 | 0.412 | 7.702 | 46.83 | -33.410 | 169.9 | -44.604 |
| Factor | Volume Value of Shrinkage Porosity / cm³ | Secondary Dendrite Spacing / μm | Solidification Time / s | ||||||
|---|---|---|---|---|---|---|---|---|---|
| A | B | A | B | C | A | B | C | ||
| Level 1 Mean | 2.787 | 2.813 | 3.703 | -33.097 | -32.684 | -33.138 | -43.674 | -43.181 | -43.762 |
| Level 2 Mean | 2.754 | 2.748 | 1.774 | -33.162 | -33.099 | -33.164 | -43.772 | -43.607 | -43.811 |
| Level 3 Mean | 3.003 | 3.989 | 3.996 | -33.323 | -33.216 | -33.302 | -43.896 | -44.041 | -43.865 |
| Level 4 Mean | 4.918 | 3.912 | 3.989 | -32.806 | -33.388 | -32.784 | -43.999 | -44.513 | -43.904 |
| Range | 2.164 | 1.241 | 2.222 | 0.517 | 0.704 | 0.518 | 0.325 | 1.332 | 0.142 |
| Optimal Level | A4 | B3 | C3 | A4 | B1 | C4 | A1 | B1 | C1 |
| Weight | 2 | 3 | 1 | 3 | 1 | 2 | 2 | 1 | 3 |
2.2 Optimization Scheme and Experimental Verification
For the four schemes obtained from the above analysis, numerical simulation verification is carried out to determine the optimal combination of process parameters for the low-pressure casting of the aluminum alloy battery end plate, and the numerical simulation results are shown in Table 5.
It can be seen from Table 5 that the volume values of shrinkage porosity of the four schemes are all less than 1, so there are no shrinkage porosity defects. In terms of the size of the secondary dendrite spacing and the solidification time, Scheme 3 is the smallest. Therefore, after comprehensive analysis, Scheme 3 (A1B1C1) is determined as the optimal process parameter combination, that is, the pouring temperature is 690 °C, the mold preheating temperature is 330 °C, and the filling time is 8 s.
The distribution of shrinkage porosity of the optimal process scheme is shown in Figure 3, and the volume value of shrinkage porosity is 0.83 cm³; the distribution of the secondary dendrite spacing is shown in Figure 4, and the maximum value of the secondary dendrite spacing is 43.94 μm; the solidification time is 140.6 s, and the temperature field distribution at the end of solidification is shown in Figure 5.
After the optimization of the battery end plate, there are no macroscopic shrinkage porosity defects in the numerical simulation results. In order to verify the feasibility of this optimized process scheme, production trials are carried out according to the best process scheme, and metallographic samples are extracted at representative positions during the trial production, as shown in points A and B in Figure 6. After a series of treatments such as rough grinding, fine grinding, and polishing, the samples are etched with 5% HF acid by volume, and then rinsed with alcohol and dried. The microstructure of the polished surface observed under the microscope is shown in Figure 7. The observation shows that the internal structure of the aluminum alloy battery end plate is uniform, the grains are fine, and there are no obvious shrink The microscopic structure of the aluminum alloy battery end plate shows that the internal organization is uniform, the grains are fine, and there are no obvious shrinkage porosity defects. This result fully proves the feasibility of the optimized process scheme.
3. Conclusions
(1) Based on the orthogonal experimental design, the influence law of each process parameter on the quality evaluation indicators of the battery end plate is explored. For the indicator of the volume of shrinkage porosity, the most significant influence is the filling time, followed by the pouring temperature and the mold preheating temperature; for the secondary dendrite spacing, the influence of the mold preheating temperature is the most significant, followed by the filling time and the pouring temperature; for the solidification time, the influence of the mold preheating temperature is the most significant, followed by the pouring temperature and the filling time.
(2) Through comprehensive analysis, the optimal process parameter results for the low-pressure casting of the aluminum alloy battery end plate are determined as Scheme 3 (A1B1C1), that is, the pouring temperature is 690 °C, the mold preheating temperature is 330 °C, and the filling time is 8 s.
(3) Under the optimized scheme, the casting has no shrinkage porosity defects, the secondary dendrite spacing is the smallest, and the solidification time is the shortest. Finally, the correctness of the optimized scheme is verified through production trials and metallographic analysis.
In the future research, we can further explore the influence of other process parameters on the quality of the battery end plate, such as the pressure curve during the low-pressure casting process and the cooling rate after casting. Additionally, we can also study the optimization of the gating system and the 渣包 design to further improve the feeding effect and reduce the occurrence of defects. Moreover, the combination of numerical simulation and experimental verification can be further strengthened to improve the accuracy and reliability of the research results.
In summary, the research on the low-pressure casting process parameters of the aluminum alloy battery end plate provides important references for the actual production of new energy vehicle battery end plates. By optimizing the process parameters, the quality and performance of the battery end plate can be improved, which is of great significance for the development of the new energy vehicle industry.
| Project | Scheme 1 | Scheme 2 | Scheme 3 | Scheme 4 |
|---|---|---|---|---|
| Volume Value of Shrinkage Porosity / cm³ | 0.635 | 0.629 | 0.830 | 0.000 |
| Secondary Dendrite Spacing / μm | 45.93 | 44.47 | 43.94 | 46.83 |
| Solidification Time / s | 163 | 148 | 140.6 | 169.1 |
It is worth noting that although the optimized process parameters obtained in this study can effectively improve the quality of the battery end plate, the actual production process is still affected by many factors, such as the stability of the raw materials, the accuracy of the equipment, and the operation skills of the workers. Therefore, in the actual production process, it is necessary to strengthen the control and management of each link to ensure the stability and reliability of the production process.
Furthermore, the development of new materials and new technologies also provides new opportunities and challenges for the low-pressure casting of battery end plates. For example, the application of advanced materials with better performance can further improve the mechanical properties and service life of the battery end plate. At the same time, the development of intelligent manufacturing technology can realize the precise control and optimization of the casting process, improving the production efficiency and quality of the battery end plate.
In conclusion, the research on the low-pressure casting process parameters of the aluminum alloy battery end plate is an ongoing process. We need to continuously explore and innovate to meet the higher requirements of the development of the new energy vehicle industry. I believe that with the continuous progress of technology and the efforts of researchers, the low-pressure casting technology of battery end plates will be more mature and perfect, making greater contributions to the development of the new energy vehicle industry.
