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Transient Thermal Modeling of an Axial Flux Permanent Magnet (AFPM) Machine Using a Hybrid Thermal Model

机译:基于混合热模型的轴向磁通永磁(aFpm)机的瞬态热模拟

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摘要

This paper presents the development of a hybrid thermal model for the EVO Electric AFM 140 Axial Flux Permanent Magnet (AFPM) machine as used in hybrid and electric vehicles. The adopted approach is based on a hybrid lumped parameter and finite difference method. The proposed method divides each motor component into regular elements which are connected together in a thermal resistance network representing all the physical connections in all three dimensions. The element shape and size are chosen according to the component geometry to ensure consistency. The fluid domain is lumped into one region with averaged heat transfer parameters connecting it to the solid domain. Some model parameters are obtained from Computation Fluid Dynamic (CFD) simulation and empirical data. The hybrid thermal model is described by a set of coupled linear first order differential equations which is discretised and solved iteratively to obtain the temperature profile. The computation involved is low and thus the model is suitable for transient temperature predictions. The maximum error in temperature prediction is 3.4% and the mean error is consistently lower than the mean error due to uncertainty in measurements. The details of the model development, temperature predictions and suggestions for design improvements are presented in this paper.
机译:本文介绍了用于混合动力和电动车辆的EVO电动AFM 140轴向通量永磁(AFPM)机器的混合热模型的开发。采用的方法基于混合集总参数和有限差分法。所提出的方法将每个电动机组件划分为规则的元素,这些元素在热阻网络中连接在一起,代表了所有三个维度上的所有物理连接。根据组件的几何形状选择元素的形状和大小以确保一致性。将流体域集中到一个区域中,平均传热参数将其连接到固体域。一些模型参数是从计算流体动力学(CFD)仿真和经验数据获得的。混合热模型由一组耦合的线性一阶微分方程描述,将其离散化并迭代求解以获得温度曲线。所涉及的计算量低,因此该模型适用于瞬态温度预测。由于测量的不确定性,温度预测中的最大误差为3.4%,平均误差始终低于平均误差。本文介绍了模型开发,温度预测和设计改进建议的详细信息。

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