Non-destructive magnetic controls are increasing in the industrial field. In this domain, the expectation for simulation tools able to anticipate the magnetic signature, improve the understanding and avoid fastidious and uncertain experimental pre-characterizations is high. Among different methods, the magnetic Barkhausen noise (MBN) control is one of the most popular. MBN raw signal is stochastic, not reproducible, and complex to exploit. MBNenergy, which is obtained by integrating the square of the MBN voltage signal with respect to the time axis is a much more stable indicator. Although the so-called MBNenergy is not, strictly speaking, an energy, it is connected to the domain wall motions and to their kinetic energy. By plotting MBNenergy as a function of H (the tangent surface excitation field), hysteresis cycles are observed. After a rescaling step, B(H) and MBNenergy(H) hysteresis cycles can be compared. They look similar for materials with high magnetocrystalline anisotropy (i.e. when the domain wall contribution is dominant over the magnetization rotation one during the magnetization process). In this study, a multiscale model is used to simulate a virtual anhysteretic behavior of a ferromagnetic steel with a magnetization process limited to the domain wall contribution. By using this anhysteretic contribution in the Jiles-Atherton model and running an inverse procedure, a MBN envelop can be obtained. By modulating the amplitude of an alternating, high frequency signal using this envelop, an accurate simulation of the raw Barkhausen noise is obtained.