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Optimal sizing of an electrical machine using a magnetic circuit model: application to a hybrid electrical vehicle

机译:使用磁路模型优化电机的尺寸:在混合动力电动汽车上的应用

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Numerous researches about hybrid electrical vehicles (HEVs) deal with topologies, technologies, sizing and control. These aspects allow reducing transportation costs and environmental impacts. This study focuses on the sizing of the electrical machine (EM) of the HEV, taking into account its surroundings: the hybrid system, the driving cycle and an optimal energy management. In this study, the parallel HEV is the study case. In a classical HEV design process, a scaling factor is usually applied on an efficiency map model to fix the standard power of the EM. The efficiency and the maximum torque power are scaled using a linear dependency on the rated maximum power. However, this method has some disadvantages. This study proposes two formulations of a scaling model based on a magnetic circuit model (MCM) with one or ten parameters. Then, the MCM is involved in a multi-objective optimisation process of the HEV. This process is a global sizing process using dynamic programming as an optimal energy management. Optimal sizings of the hybrid vehicle are then proposed for various driving conditions.
机译:有关混合动力汽车(HEV)的众多研究涉及拓扑,技术,尺寸和控制。这些方面可以降低运输成本和环境影响。这项研究着眼于混合动力系统,混合动力系统,行驶周期和最佳能源管理的环境,着重研究了混合动力汽车的电机(EM)的尺寸。在本研究中,并行HEV是研究案例。在经典的HEV设计过程中,通常将比例因子应用于效率图模型,以固定EM的标准功率。效率和最大转矩功率通过使用线性关系对额定最大功率进行换算。但是,这种方法有一些缺点。这项研究提出了基于具有一个或十个参数的磁路模型(MCM)的缩放模型的两种公式。然后,MCM参与了HEV的多目标优化过程。此过程是使用动态编程作为最佳能源管理的全局调整过程。然后针对各种行驶条件提出了混合动力车辆的最佳尺寸。

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