The rapid growth of the EV car industry has intensified the demand for high-performance soft magnetic materials, particularly non-oriented silicon steel, which serves as a core component in the electromagnetic circuits of drive motors for EV cars. As governments worldwide, including China’s “Dual Carbon” strategy, push for the adoption of EV cars to reduce carbon emissions, the development of advanced materials with optimized electromagnetic properties, mechanical strength, and thinner dimensions has become critical. In EV cars, the efficiency of energy conversion in motors heavily relies on the magnetic performance of silicon steel, where thickness reduction is a common strategy to enhance high-frequency iron loss characteristics while balancing other properties. This study focuses on investigating how thickness variations influence the microstructure, texture, inclusions, magnetic properties, and mechanical behavior of high-alloy silicon steel specifically designed for EV cars. By comparing 0.20 mm and 0.25 mm thicknesses, we aim to provide insights that can guide the optimization of silicon steel for the evolving needs of EV cars, ensuring better performance in applications such as electric vehicle powertrains.
In the context of EV cars, silicon steel must exhibit low iron loss, high magnetic induction, and sufficient mechanical strength to withstand the operational stresses in motors. The trend toward thinner gauges, such as 0.20 mm to 0.25 mm, is driven by the need to reduce eddy current losses at high frequencies, which are prevalent in the fast-switching inverters used in EV cars. However, thickness reduction can lead to trade-offs, such as increased hysteresis loss and altered texture development, which may affect overall motor efficiency. This research employs techniques like XRD and EBSD to analyze these aspects, with a particular emphasis on how they impact the performance of silicon steel in EV cars. The findings are expected to contribute to the material science community by elucidating the thickness-dependent behavior, ultimately supporting the mass production of superior silicon steel for the next generation of EV cars.
The experimental materials used in this study are high-alloy silicon steel sheets with a chemical composition tailored for EV cars, as summarized in Table 1. The composition includes elements like silicon and manganese, which enhance magnetic properties and strength, crucial for the demanding environments in EV cars. The manufacturing process involved industrial-scale steps: steelmaking, refining, continuous casting, hot rolling, normalization annealing at 850°C for 140 seconds, cold rolling through a 20-stand mill in six passes to achieve the target thicknesses of 0.20 mm and 0.25 mm, and final annealing at 950°C for 100 seconds followed by insulation coating. This replicates the production conditions for silicon steel used in EV cars, ensuring practical relevance.
| Element | C | Si | Mn | P | S | Als | Sn |
|---|---|---|---|---|---|---|---|
| Content | 0.001 | 3.3 | 0.50 | ≤0.020 | ≤0.004 | 0.85 | 0.05 |
For the analysis, samples were prepared and labeled as shown in Table 2. The 0.20 mm and 0.25 mm thick samples were subjected to microstructure examination using electron backscatter diffraction (EBSD), macro-texture detection via X-ray diffraction (XRD), and magnetic property measurements with an Epstein frame. Magnetic properties, including iron loss at low frequency (P1.5/50) and high frequency (P1.0/400), as well as magnetic induction (B50), were evaluated based on a standard density of 7.65 g/cm³, which is typical for silicon steel in EV cars. Mechanical properties such as yield strength (Rp0.2), tensile strength (Rm), and elongation (A50) were also measured to assess suitability for EV car applications. The use of these methods ensures a comprehensive understanding of how thickness affects the material’s performance in EV cars.
| Sample ID | Thickness (mm) | Microstructure State |
|---|---|---|
| 1# | 0.20 | Recrystallized Annealed |
| 2# | 0.25 | Recrystallized Annealed |
The microstructure of the annealed silicon steel samples, as observed through EBSD, revealed significant differences between the two thicknesses. For the 0.20 mm sample (1#), the grain structure was more uniform with an average grain size of approximately 71 μm, whereas the 0.25 mm sample (2#) exhibited a less homogeneous structure with a larger average grain size of about 78 μm and the presence of numerous smaller grains. This grain refinement in thinner samples is attributed to higher cold rolling reduction, which increases stored energy and promotes recrystallization during annealing. In EV cars, such microstructural characteristics can influence magnetic domain movement and loss mechanisms. The relationship between grain size (D) and hysteresis loss (P_h) can be expressed using the formula: $$P_h \propto \frac{1}{D}$$, indicating that smaller grains lead to higher hysteresis loss due to increased grain boundary density. This is particularly relevant for EV cars, where low-frequency performance is critical for motor efficiency.
Texture analysis using XRD showed that both thicknesses predominantly exhibited {114}〈481〉 and {223}〈362〉 textures, with the 0.20 mm sample displaying stronger {111}〈112〉 texture components and weaker α-fiber texture intensity. The 0.25 mm sample had relatively weaker {111}〈112〉 texture. These texture variations arise from differences in cold rolling reduction; higher reduction in thinner samples enhances the stability of γ-fiber textures, which can detrimentally affect magnetic induction. The orientation distribution function (ODF) plots confirmed these findings, with texture intensities ranging from 0.7 to 4. For EV cars, texture control is essential as it directly impacts magnetic anisotropy and core loss in motors. The volume fraction of desirable textures can be modeled as: $$f(\text{texture}) = \frac{I_{\text{texture}}}{\sum I}$$, where I represents intensity, highlighting how texture evolution in silicon steel influences the electromagnetic behavior in EV cars.
Inclusion analysis indicated that both samples had similar types and sizes of inclusions, primarily Al-based compounds, with sizes concentrated between 1.0 μm and 5.0 μm, and a majority in the 1.0–3.0 μm range. The 0.20 mm sample contained a higher number of smaller inclusions, while the 0.25 mm sample had more inclusions larger than 5 μm. The distribution and composition of inclusions, as summarized in Table 3, show that oxides and minor Ca/Mn-based inclusions were present, but their impact on magnetic properties was comparable. In EV cars, inclusions act as pinning sites for magnetic domains, increasing hysteresis loss and potentially reducing mechanical integrity. The effect of inclusion size (d) on coercivity (H_c) can be described by: $$H_c \propto \frac{1}{d}$$, implying that finer inclusions contribute to higher coercivity and thus greater iron loss, which is a key consideration for silicon steel used in high-efficiency EV cars.
| Sample ID | Inclusion Size Range (μm) | Predominant Type | Relative Quantity |
|---|---|---|---|
| 1# | 1.0–3.0 | Al-based compounds | High for small inclusions |
| 2# | 1.0–5.0 | Al-based compounds | High for large inclusions |
Magnetic property measurements, detailed in Table 4, demonstrated that reducing thickness from 0.25 mm to 0.20 mm resulted in an increase in low-frequency iron loss P1.5/50 by approximately 0.11 W/kg (from 2.12 W/kg to 2.23 W/kg) and a decrease in high-frequency iron loss P1.0/400 by about 1.27 W/kg (from 12.82 W/kg to 11.56 W/kg). Magnetic induction B50 decreased by 0.32 T (from 1.67 T to 1.64 T). These changes are critical for EV cars, as high-frequency operations are common in motor drives. The separation of iron loss into hysteresis and eddy current components, as shown in Table 5, reveals that for the 0.20 mm sample, eddy current loss accounted for 9.9% of P1.5/50 and 35.5% of P1.0/400, whereas for the 0.25 mm sample, it was 14.8% and 45.4%, respectively. This highlights the advantage of thinner gauges in reducing eddy current losses at high frequencies, which is beneficial for EV cars. The total iron loss (Ptotal) can be expressed as: $$P_{\text{total}} = P_h + P_e = k_h f B_m^n + k_e f^2 B_m^2 t^2$$, where P_h is hysteresis loss, P_e is eddy current loss, f is frequency, B_m is maximum flux density, t is thickness, and k_h, k_e, n are material constants. For EV cars, minimizing P_e through thickness reduction is essential for improving efficiency.
| Sample ID | Density (g/cm³) | Magnetic Induction B50 (T) | Iron Loss P1.5/50 (W/kg) | Iron Loss P1.0/400 (W/kg) |
|---|---|---|---|---|
| 1# | 7.65 | 1.64 | 2.23 | 11.56 |
| 2# | 7.65 | 1.67 | 2.12 | 12.82 |
| Sample ID | Loss Type | P1.5/50 (W/kg) | P1.0/400 (W/kg) | Eddy Loss Percentage |
|---|---|---|---|---|
| 1# | Eddy Loss | 0.22 | 4.10 | 9.9% for P1.5/50, 35.5% for P1.0/400 |
| Hysteresis Loss | 2.01 | 7.45 | – | |
| 2# | Eddy Loss | 0.31 | 5.82 | 14.8% for P1.5/50, 45.4% for P1.0/400 |
| Hysteresis Loss | 1.81 | 7.00 | – |
Mechanical properties, as presented in Table 6, showed minimal differences between the two thicknesses. The 0.20 mm sample had a yield strength Rp0.2 of 447 MPa, tensile strength Rm of 570 MPa, and elongation of 18.5%, while the 0.25 mm sample exhibited values of 450 MPa, 580 MPa, and 21.0%, respectively. This similarity indicates that thickness reduction does not significantly compromise mechanical integrity, which is vital for the structural demands of EV cars, where components must endure vibrations and stresses. The relationship between thickness and strength can be approximated by: $$\sigma = \sigma_0 + k t^{-1/2}$$, where σ is strength, σ_0 is a constant, k is a material parameter, and t is thickness. For EV cars, maintaining high strength alongside good magnetic properties ensures durability and reliability in motor cores.
| Sample ID | Yield Strength Rp0.2 (MPa) | Tensile Strength Rm (MPa) | Elongation A50 (%) |
|---|---|---|---|
| 1# | 447 | 570 | 18.5 |
| 2# | 450 | 580 | 21.0 |
Discussion of the results emphasizes the trade-offs in silicon steel performance for EV cars. The reduction in thickness to 0.20 mm improves high-frequency iron loss due to decreased eddy current losses, as thinner dimensions reduce the path for circulating currents. This is mathematically represented by the eddy current loss formula: $$P_e = \frac{\pi^2 f^2 B_m^2 t^2}{6\rho}$$, where ρ is resistivity, confirming that P_e is proportional to the square of thickness. Thus, for EV cars operating at high frequencies, thinner silicon steel is advantageous. However, the increase in low-frequency iron loss and decrease in magnetic induction are drawbacks, attributed to finer grain sizes and stronger {111}〈112〉 textures, which hinder domain wall motion. In EV cars, this could affect motor efficiency at lower speeds, necessitating a balance in material design.
Furthermore, the uniformity of microstructure in thinner samples enhances magnetic consistency, which is crucial for the precise control required in EV car motors. The role of alloying elements like silicon and tin in stabilizing the microstructure and improving resistivity cannot be overlooked; for instance, silicon content increases electrical resistivity, thereby reducing eddy currents. This aligns with the needs of EV cars for materials that minimize energy losses. The comprehensive analysis underscores that while thickness reduction benefits high-frequency performance, it requires careful optimization of processing parameters to mitigate adverse effects on other properties. Future work could explore intermediate thicknesses or alternative annealing strategies to further enhance silicon steel for EV cars.
In conclusion, this study demonstrates that reducing the thickness of silicon steel from 0.25 mm to 0.20 mm significantly influences its properties, with implications for EV car applications. The thinner material exhibits a finer and more uniform grain structure, stronger {111}〈112〉 texture, and improved high-frequency iron loss performance, albeit with a slight increase in low-frequency iron loss and reduction in magnetic induction. Inclusion characteristics and mechanical properties remain relatively unchanged, ensuring that thinner gauges are viable for EV cars. These findings highlight the importance of thickness control in tailoring silicon steel for the specific demands of EV cars, where high efficiency and reliability are paramount. As the EV car industry continues to evolve, ongoing research into material innovations will be essential to drive advancements in motor technology and support the global transition to sustainable transportation.