During the high-speed forming processes, the metallic sheets are usually deformed under the biaxial tensile condition. The strain rate of metallic sheets often exceeds 10² s^− 1. It is essential to determine the strain-rate-sensitive hardening model of metallic sheets for accurate numerical simulation of the high-speed forming processes. Thus, an electromagnetic hydraulic bulge experiment is proposed to determine the strain-rate-dependent hardening model of metallic sheets under the biaxial tensile condition with the strain rate of 10² s^− 1. It is convenient to numerically simulate the electromagnetic hydraulic bulge processes. Hence, the strain-rate-dependent hardening models of metallic sheets can be determined by the inverse identification procedure of updating the numerical simulation. The electromagnetic hydraulic bulge experiments of SUS304 stainless steel sheet and AA5052-O aluminum alloy sheet were performed for the inverse identification of Johnson-Cook hardening model. The discrepancy between the experimental results and numerical simulation was minimized by optimizing the parameters of strain-rate-dependent hardening models. The dynamic flow stress curves of SUS304 stainless steel sheet and AA5052-O aluminum alloy sheet were higher than the static ones. However, the AA5052-O aluminum alloy sheet exhibits more significant strain-rate hardening effect than the SUS304 stainless steel sheet. The inverse identification of strain-rate-dependent hardening model of metallic sheet was validated by comparing the simulated and experimental results of electromagnetic micro-hydroforming of micro-channel.

在高速成形过程中，金属板通常在双轴拉伸条件下发生变形。金属板的应变率通常超过 10 ²  s ^{− 1}。确定金属板材的应变率敏感硬化模型对于高速成形过程的精确数值模拟至关重要。^{因此，提出了一种电磁液压膨胀实验，以确定在应变率为 10 2}  s ^{− 1}的双轴拉伸条件下金属板的应变率相关硬化模型. 数值模拟电磁液压膨胀过程很方便。因此，金属板材的应变率相关硬化模型可以通过更新数值模拟的逆识别过程来确定。对SUS304不锈钢薄板和AA5052-O铝合金薄板进行了电磁液压胀形实验，对Johnson-Cook硬化模型进行了反演识别。通过优化应变率相关硬化模型的参数，最大限度地减少了实验结果与数值模拟之间的差异。SUS304不锈钢板和AA5052-O铝合金板的动态流变应力曲线高于静态。然而，AA5052-O铝合金板材表现出比SUS304不锈钢板材更显着的应变率硬化效应。通过对比微通道电磁微液压成形的仿真结果和实验结果，验证了金属板材应变率相关硬化模型的反辨识。