The analysis and optimization of devices with soft magnetic cores, such as inductive sensors and electric machines, rely on a simple and precise modelling of their nonlinear anhysteretic magnetization. The Langevin-Weiss equation of state has the advantages of being physically-based and capable of accurately describing isotropic materials. In fact, it has even been adopted as the backbone of the popular Jiles-Atherton model to describe magnetic hysteresis. However, many studies show the difficulty of retrieving the modelling parameters given an experimental anhysteretic curve, for which stochastic optimization methods are generally used.

In this work, we present a simple and deterministic method for finding the parameters of the Langevin-Weiss model: the saturation magnetization, the temperature dependent $a$ parameter, and the molecular field constants. To this end, we optimize a problem with a nonlinear solver where the fitting variables are instrinsically bounded. We validated the approach by analyzing three widely used soft magnets; a grain-oriented silicon steel, a Mn-Zn soft ferrite, and a Fe-based nanocrystalline alloy with induced anisotropy.

We demonstrate that, contrary to what has previously been assumed, the Langevin-Weiss function can provide a good description of the anhysteretic magnetization of any homogeneous material, even materials with strong transverse uniaxial anisotropy. The key, which seems to have been overlooked, is to allow the Weiss molecular field to be negative.

具有软磁芯的设备（例如电感传感器和电机）的分析和优化依赖于对其非线性非滞后磁化的简单而精确的建模。Langevin-Weiss 状态方程具有基于物理和能够准确描述各向同性材料的优点。事实上，它甚至被用作描述磁滞的流行 Jiles-Atherton 模型的基础。然而，许多研究表明在给定实验非滞后曲线的情况下检索建模参数很困难，通常使用随机优化方法。

在这项工作中，我们提出了一种简单且确定性的方法来寻找 Langevin-Weiss 模型的参数：饱和磁化强度、温度相关 $\mathrm{一种}$参数和分子场常数。为此，我们使用非线性求解器优化了一个问题，其中拟合变量是内在有界的。我们通过分析三种广泛使用的软磁铁来验证该方法；取向硅钢、Mn-Zn软铁氧体和具有诱导各向异性的Fe基纳米晶合金。

我们证明，与先前假设的相反，Langevin-Weiss 函数可以很好地描述任何均质材料的非磁滞磁化强度，即使是具有强横向单轴各向异性的材料。似乎被忽视的关键是让 Weiss 分子场为负。