Estimation of Punching Clearance in the Manufacture Process of Iron Cores

Abstract

The iron core of non-oriented electrical steel sheets is manufactured by punching, and the punching clearance greatly affects the amount of iron loss. Empirically, it is known that increasing the punching clearance, while extending the life of the die, introduces greater plastic deformation at the end of the iron core. This plastic deformation increases iron loss and decreases motor performance, making clearance a condition that must be controlled. On the other hand, punching clearance is proprietary information of the manufacturer and is not disclosed unless it is produced in-house. Against this background, we have developed an inspection method for estimating punching clearance, to better control the quality of iron cores. First, ring specimens were prepared using die with different clearances (0.6%–16.4%). Magnetic property evaluation for these ring specimens showed a linear relationship where iron loss increased with increasing clearance. The electron backscattering diffraction (EBSD) analysis pointed to the changes in strain introduction at the machining edge. Discussion of these data resulted in a calibrated relationship between clearance and kernel average misorientation (KAM). In addition, similar tests were performed on several grades of non-oriented electrical steel sheets to obtain a versatile calibration curve that takes in to account the effect of hardness. The results and discussion of this study demonstrate a new estimation technique that is expected to contribute to motor production management.

1. Introduction

The electrification of various products is being promoted to build a decarbonized society. Even today, electric motors use almost 50% of the global electricity production [1]. The demand for motors with higher efficiency and lower energy loss is increasing. One of the main components of an electrical motor is the iron core. The iron core basically consists of laminated electrical steel sheets, and its energy loss is classified as iron loss [2, 3]. The iron loss of an iron core is usually larger than that expected from the iron loss of the electrical steel sheets used [4]. Plastic strain, residual stress, interlaminar short circuits, etc. during manufacture have been reported as causes [5–7]. Since the iron loss degradation that occurs during the manufacturing of these products is a drag on motor efficiency improvement, a lot of research has been conducted in the past [8–17]. For example, cores such as stators and rotors are manufactured by punching from the standpoint of productivity. On the other hand, punching causes plastic deformation, such as rollovers and burrs, of the stator and rotor ends [2]. In previous studies [5, 15], the iron loss behavior of electrical steel sheets after shearing or punching has been evaluated, and it has been clarified that the worked layer causes iron loss degradation. The relationship between the ratio of worked layer and iron loss degradation is discussed in the literature [5, 15]. Iron loss behavior has been evaluated under stress in the elastic stress range, and it is also clear that compressive stresses of several tens of MPa can significantly degrade iron loss [6, 17]. By reflecting the changes in the properties of these materials in the electromagnetic field analysis, a more accurate calculation of motor efficiency is expected [4, 18].

From the manufacturing side, effects of clearance between dies, punching speed, and surface treatment of dies, have been reported [19–21]. However, these technological developments have matured as the know-how of punch-out or mold manufactures industrially rather than in the academic field [22]. Under these circumstances, we suggest that the following three points are important for the stable production of high-efficiency motors. The first point is to set punching clearances that take into account iron loss degradation and manufacturability. Qualitatively, a smaller clearance reduces iron loss degradation, but shortens the life of the dies [19]. The second point is to locate a manufacturer that satisfies the manufacturing requirements (this is omitted in the case of in-house production), and the third point is to be able control the quality of the deliverables. The first point is relatively easy to determine from the results of laboratory tests as already reported. On the other hand, it is currently difficult to back-analyze the clearance set during manufacturing from a completed stator or rotor, and quality control has to be done by benchmark testing as a motor. This constraint has resulted in increased costs and timeframes.

Again, from the viewpoint of quality control of stator and rotor, it is desirable to be able to check using a simple method whether both parts are manufactured with the prescribed punching clearance at the time of acceptance. Therefore, we conducted to develop a technique for estimating punching clearance on electrical steel sheets. As a result, we have obtained the ability to estimate the punching clearance by analyzing the plastic strain generated at the machining edge using electron backscatter diffraction. Here, we will report the developed method.

2. Materials and Methods

Three grades of non-directional electrical steel sheets were used as specimens for this study. The grades are 35H210, 35H300 and 35H440, which are classified as high, medium, and low grades respectively in commercially available 0.35 mm thick products. The chemical compositions of these electrical steel sheets are listed in Table 1. Higher grade electrical steel sheets, 35H210, have higher Si and Al content and lower impurity content. In contrast, lower grades have lower Si and Al content and higher impurity content. These electrical steel sheets were punched into ring-shaped specimens using the dies described below to carry out magnetic property evaluations.

Table 1 Chemical compositions (mass%) of the electrical steel sheets for this study.

In this study, a set of upper and lower dies with six levels of clearance was prepared to confirm the effect on the iron loss in the manufacturing process of electrical steel sheets. Clearance is the gap between the lower and upper dies. This gap is in the order of several µm to several tens of µm, causing machining deviations with respect to the design values. Thus, the dimensions of the prepared dies were measured to obtain the actual clearance. Ratio of clearance to sheet thickness CL is treated as follows.

  

\begin{equation} \mathit{CL} = D/t \times 100 \end{equation} (1)

where D is punching clearance and t is thickness of the electrical steel sheets. The thickness of each sample used in this study is 0.35 mm. The CL of the dies ranged from 0.6% to 16.4%. In addition, the outer-inner of the ring specimens were varied to three levels (φ45 mm–φ33 mm, φ100 mm–φ95 mm, and φ45 mm–φ41 mm): the combinations of CL and ring specimen geometry are shown in Table 2. Although the punching speed was varied under two conditions, 30 and 100 spm, no clear differences were obtained, so the discussion in this study is basically without distinction between the two. In addition to punching, φ45 mm–φ33 mm ring specimens were produced by electrical discharge machining (EDM). EDM specimens are used to standardize experimental values for punched specimens, as the introduction of a machining layer by EDM is negligibly small compared to punching.

Table 2 Grade of electrical steel sheets and punching conditions for this study.

The AC magnetic properties of the ring specimens were evaluated at room temperature. In this evaluation, the magnetic flux density and frequency were 0.2 to 1.5 T and 50 to 10000 Hz, respectively. Under some conditions, the experiments were abandoned due to the heat generated by the sample. Only iron losses are covered among the magnetic properties, and no separation into hysteresis losses and eddy current losses is made. The iron loss of the punched samples was normalized by the iron loss of the EDM samples, as follows.

  

\begin{equation} \Delta W = W_{\text{punching}}/W_{\text{EDM}} \end{equation} (2)

where W_punching and W_EDM are iron loss of the punched and EDM samples, respectively.

The cross-sectional microstructures of the punched samples were characterized using an electron backscatter diffraction (EBSD, TSL OIM Data Collection) system attached to a scanning electron microscope (SEM, Hitachi SU5000). SEM-EBSD analysis was conducted at 15 kV with a 5 µm measurement step. Kernel Average Misorientation (KAM) maps were used to estimate the machining layers introduced by punching.

3. Results and Discussion

3.1 Iron loss behavior of punched electrical steel sheets

We prepared total a total of 19 ring-shaped samples by punching or EDM as shown in Table 2. First, the iron loss of each sample was evaluated to confirm the empirically known behavior of increasing iron loss with increasing CL. Figure 1 shows the relationship between iron loss and frequency for several samples, with the vertical direction comparing grades and the horizontal direction comparing CLs. Overall, the iron loss tended to increase with increasing flux density and frequency. Comparing between the steel grades, the 35H210 grade samples had the lowest iron loss. Compared to sample G₂₁₀ prepared by EDM, the iron loss of sample B₂₁₀ and D₂₁₀ prepared by punching was 1.08–1.18 and 1.13–1.66 times higher respectively. This result confirms that the iron loss degradation due to the punching process and the increased degrees of degradation due to increased CL. In similar comparisons, the degree of iron loss degradation of sample B₃₀₀ and sample D₃₀₀ with respect to sample G₃₀₀ was 1.00–1.14 and 1.10–1.47 times higher, and that of sample B₄₄₀ and sample D₄₄₀ with respect to sample G₄₄₀ was 1.05–1.12 and 1.06–1.33 times higher. The degree of degradation was smaller for the lower grade sheet in the range of <3.5% Si and these results are consistent with previous report [23].

Fig. 1

Relationship between iron loss and frequency in (a) sample G₂₁₀, (b) sample B₂₁₀, (c) sample D₂₁₀, (d) sample G₃₀₀, and (e) sample B₃₀₀, (f) sample D₃₀₀, (g) sample G₄₄₀, (h) sample B₄₄₀, and (i) sample D₄₄₀. (online color)

To confirm the effect of the ring width of the specimen, the relationship between iron loss and frequency in samples with similar CL and different ring geometries is shown in Fig. 2. The outer-inner diameters of the ring specimens used are φ45–φ33, φ100–φ95 and φ45–φ41, and the ring widths are 6, 2.5 and 2 mm. Figure 2 shows a trend of increasing iron loss with decreasing the width. This can be attributed to the fact that the proportion of magnetically unfavorable punched layers increases with decreasing width.

Fig. 2

Relationship between iron loss and frequency in (a) sample B₃₀₀, (b) sample E₃₀₀, and (c) sample F₃₀₀. For comparison, Fig. 1(e) is reprinted as Fig. 2(a). (online color)

To clarify relationship between the behavior of iron loss and CL, ΔW under several flux densities (B = 1.0 and 1.5 T) and frequencies (f = 100 and 500 Hz) is shown in Fig. 3. The degradation of iron loss is roughly more pronounced with increasing CL as shown in Fig. 3(a). As pointed out above, in addition to CL, ring width and grade of electrical steel sheets influence degradation. Thus, several increasing trends are observed for CL. This behavior is also observed in Figs. 3(b)–3(d), but the degree of degradation decreases with increasing flux density and frequency. The decrease in the influence of the punching layer due to an increase in flux density and frequency has been noted in the past and is a common behavior [6].

Fig. 3

Change in the iron loss as a function of CL: (a) ΔW_10/100, (b) ΔW_10/500, (c) ΔW_15/100, and (d) ΔW_15/500. Iron loss deteriorates roughly with increasing clearance. Contrary, the same evaluation is difficult for different grade and ring geometries. (online color)

So far, it has been confirmed in this study that CL has a significant influence on the iron loss of electromagnetic steel sheets: the importance of CL management has been reaffirmed. In the following section, an EBSD analysis is performed on ring specimens produced by punching and the possibility of estimating iron loss degradation behavior and CL estimation techniques by microstructure observation will be described.

3.2 Definition of KAM parameters

We conducted an EBSD analysis on a cross-section of each sample to obtain KAM maps in order to quantitatively treat the influence layer introduced by the punching process. Figure 4 shows the representative cross-sectional KAM maps of samples (a) A₃₀₀, (b) C₃₀₀, and (c) D₃₀₀. At both punched ends, areas of higher KAM values were formed due to plastic deformation during processing. These areas tended to increase in size with increasing CL as shown in Fig. 4.

Fig. 4

Cross-sectional KAM maps of (a) sample A₃₀₀, (b) sample C₃₀₀, and (c) sample D₃₀₀. The KAM value at the machining edge increases with increasing CL. (online color)

To quantify these trends, we have defined two new parameters KAM_ot(φ) and KAM_ot-edge(φ). KAM_ot(φ) is a parameter corresponding to the ratio of the punching layer in the cross-section (Fig. 5(a)) as follow.

  

\begin{equation} \mathrm{KAM}_{\text{ot}}(\varphi) = 2\alpha t/wt \end{equation} (3)

where α is the width of the region where the value of KAM is threshold φ or over, w and t is the width and thickness of the electrical steel sheets. In practice, the KAM map is a collection of measurement points. Equation (4) is calculated, using the KAM data in the cross-section, from the total number of measurement points and the number of points at that threshold or over. KAM_ot(φ) is calculated by dividing by the cross-sectional area, so the effect of the width of the ring specimen can be taken into account. In contrast, it is assumed that the width of the specimen does not have a significant effect on the relationship between the area of the layer formed by punching and the CL. However, the area where the working layer is introduced is affected by the thickness of the plate. Senda et al. [5] reported that plastic and elastic strain from shearing generally forms to a width of approximately 1:1 with respect to the thickness of the sheets. Thus, we defined KAM_ot-edge(φ) as the parameter for which only the machining edge is evaluated, as follows.

  

\begin{equation} \mathrm{KAM}_{\text{ot-edge}}(\varphi) = \alpha t/t^{2} \end{equation} (4)

KAM_ot-edge(φ) is the ratio of the punching layer in the square of the sheet thickness (Fig. 5(b)). In practice, eq. (4) is calculated, using the KAM data in thickness squared, from the total number of measurement points and the number of points that threshold or over.

Fig. 5

Schematic image showing the parameters of KAM_ot(φ) and KAM_ot-edge(φ) proposed in this study. (online color)

3.3 Relationship between iron loss degradation and KAM_ot(φ)

As pointed out in Fig. 3 and in previous literature, the degradation of iron loss in the manufacturing process depends on the ratio of the worked layer introduced into the electrical steel sheets. We plot the iron loss degradation due to punching obtained from 35H300 grade electrical steels against KAM_ot(φ) in Fig. 6. In Fig. 6, the thresholds were set at three levels ((a) 1°, (b) 2°, and (c) 3°) to identify a reasonable value. Since the accuracy of indexing by the conventional Hough transform is 0.2°–0.5°, the threshold was verified at 1°–3°.

Fig. 6

Increase in the iron loss as a function of KAM_ot(φ): (a) φ = 1°, (b) φ = 2°, and (c) φ = 3°. Note that the range of the horizontal axis is different in each figure. (online color)

Figures 6(a) and 6(b) show a good linear relationship between iron loss degradation and KAM_ot(φ). In contrast, a threshold value of 3° causes scatter in the relationship. This could be due to a decrease in the number of extracted points as the threshold value increased, resulting in a decrease in accuracy. In particular, the high KAM values at the edges may have been influenced during sample preparation such as polishing. For the same reason, KAM_ot(2°) has a narrower range of 1.0%–3.3%, while KAM_ot(1°) has a range of 2.9%–7.6%. Assuming that iron loss degradation is estimated from KAM_ot(φ), both the threshold values of 1° and 2° have a good liner relationship, but with the threshold value of 2°, the estimated degradation fluctuation is more sensitive to variations in KAM_ot(φ). From the above, we concluded that a threshold value of 1° in KAM_ot(φ) is appropriate.

3.4 Estimation of punching clearance by KAM_ot-edge(φ)

The threshold value was determined to be 1°. Following this, the relationship between KAM_ot-edge(1°) and CL is shown in Fig. 7(a). Figure 7(a) shows a trend of increasing KAM_ot-edge(1°) with increasing CL, which is consistent with the visual confirmation in Fig. 4. In Fig. 7(a), the approximation of 35H440 has a higher intercept than that of 35H210 and 35H300, although the slope is similar. In electrical steel sheets, Si, Al, and Mn contents are controlled to improve iron loss as shown in Table 1. Si and Al provide solid solution strengthening, which results in different hardness in the three grade samples. In fact, the micro-Vickers hardness of 35H210, 35H300, and 35H400 grades were 211, 209, and 158 HV, respectively. In the softer 35H440 grade samples, it was determined that the punching caused greater plastic deformation, resulting in extensively higher KAM values. These indicate that the need to treat KAM_ot-edge(1°) and hardness as variables in the estimation of CL. Thus, we performed multiple regression analysis with KAM_ot-edge(1°) and hardness as variables. The obtained equation is as follows:

  

\begin{equation} \mathit{CL}(\%) = 102\mathrm{KAM}_{\text{ot-edge}}(\varphi) + 0.156HV - 50.7 \end{equation} (5)

Equation (5) is our proposed calibration curve for estimating the ratio of punching clearance to sheet thickness based on EBSD analysis and hardness test for iron cores. With our data, Fig. 7(b) shows the relationship between the measured CL and the value estimated by the eq. (5). The gray dotted lines stand for ±2σ. Although some variation was observed, correspondence between experimental and estimated values was obtained. We expect eq. (5) to be useful for primary sighting of the punching clearances. It is likely that the scatter shown in Fig. 7(b) is due to the fact that the difference in electrical steel sheet grade is expressed only in terms of hardness and that manufacturing parameters such as punching speed are ignored. In general purpose electrical steel sheets, the grain size is coarsened and the solute contents of Si and Al are increased to reduce iron loss. Hardness is determined by the contribution of the grain refinement effect and solid solution strengthening. Even if the hardness is the same value, the grain size and solute content are different, and the formation behavior of the worked layer may be different. Therefore, we plan to add information on material microstructures to the basic concepts from this study, in order to further improve accuracy.

Fig. 7

(a) Relationship between CL and KAM_ot-edge(1°) determined in this study. (b) Plots of measured CL and values estimated by eq. (5) for all data obtained in this study. The gray dotted lines stand for ±2σ. (online color)

4. Conclusion

In this study, we developed a technique for estimating the punching clearance in iron cores as a quality control method in motor manufacturing. In developing the estimation technique, dies with known clearances were prepared and electrical steel sheets were punched. Magnetic property evaluations of these punched samples showed a correlation between iron loss degradation and punching clearance. Moreover, microstructure observations pointed out that as clearance increased, KAM values increased, and the area became more extensive. Based on this observation, we defined two new parameters (KAM_ot(φ) and KAM_ot-edge(φ)) that focused on the area where the KAM varied. The threshold value in these parameters was set at 1° based on the correlation of iron loss degradation. Finally, multiple regression analysis, including KAM_ot-edge(φ), was used to allow estimation of punching clearance. The results and discussion in this study point out that a deeper understanding of microstructure in electrical steel sheets can lead to improved motor quality.

Acknowledgments

The authors thank our colleagues at Mitsubishi Heavy Industries, Ltd., T. Ikemi and M. Sasaki for helpful discussions.

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