轮毂电机多物理场耦合分析与协同设计仿真平台数据集

轮毂电机多物理场耦合分析与协同设计仿真平台数据集基于2022-2024年期间在东南大学进行的多物理场平台仿真和商业有限元软件Maxwell仿真生成的数据，以及2024年9月由湖南机动车检测技术有限公司与浙江尚驰电气有限公司检测试验中心采集的试验数据，全面覆盖了减速轮毂电机和直驱轮毂电机的性能参数。仿真平台通过电-磁-热相互耦合的迭代计算方式，准确预测电机的电阻、电感、反电动势、转矩、效率及温升等性能。实验数据依照国标及行业标准获取，涵盖电机电阻、电感、空载反电动势、额定转矩及其脉动、损耗、效率与温升等关键指标。本数据集在时间上精确到测试年月，空间上覆盖典型测试实验室场地，计算方式通过多物理场仿真平台与商业软件两种模式进行对比分析，结果采用实验测得数据为基准，提供仿真数据的误差与精度计算，并量化多物理场平台相较商业软件的性能精度提升比例。数据采集过程中严格使用符合精度要求的专业测量仪器，确保数据质量的准确性和可靠性。本数据集为轮毂电机的优化设计、性能验证及产业化提供了基础数据支持，具有显著的科研与工程价值，同时为多物理场耦合仿真平台的开发及应用提供了重要的参考依据。Dataset for the Multi-physics Coupling Analysis and Collaborative Design Simulation Platform of Hub Motors This dataset is generated from multi-physics platform simulations and commercial finite element software Maxwell simulations conducted at Southeast University between 2022 and 2024, as well as experimental data collected in September 2024 by the testing centers of Hunan Vehicle Testing Technology Co., Ltd. and Zhejiang Shangchi Electric Co., Ltd. It comprehensively covers the performance parameters of both geared hub motors and direct-drive hub motors. The simulation platform adopts an iterative calculation method with electro-magnetic-thermal mutual coupling to accurately predict key motor performance indicators including resistance, inductance, back electromotive force (EMF), torque, efficiency and temperature rise. The experimental data is acquired in accordance with national and industry standards, covering critical metrics such as motor resistance, inductance, no-load back EMF, rated torque and its ripple, loss, efficiency and temperature rise. This dataset features temporal precision down to the year and month of testing, and spatially covers typical test laboratory sites. For the calculation methods, comparative analysis is performed between the multi-physics simulation platform and commercial software. Taking the experimentally measured data as the benchmark, the error and accuracy calculations of the simulation data are provided, and the performance accuracy improvement ratio of the multi-physics platform relative to commercial software is quantified. Professional measuring instruments meeting precision requirements were strictly utilized during the data collection process to guarantee the accuracy and reliability of data quality. This dataset provides fundamental data support for the optimal design, performance verification and industrialization of hub motors, holds remarkable scientific research and engineering value, and also offers an important reference for the development and application of multi-physics coupling simulation platforms.

搜集汇总

背景与挑战

背景概述

该数据集基于2022-2024年东南大学的仿真数据和2024年的试验数据，全面覆盖减速和直驱轮毂电机的性能参数，通过多物理场耦合仿真与实验对比，量化了仿真精度提升。它为轮毂电机的优化设计、性能验证及多物理场仿真平台开发提供了基础数据支持。