Schamberger Stephanie, Brandl Lukas, Reuss Hans-Christian, Wagner Alfons
Research Institute for Automotive Engineering and Powertrain Systems Stuttgart (FKFS), 70569 Stuttgart, Germany.
Department of Automotive Mechatronics, Institute of Automotive Engineering (IFS), Faculty 7: Engineering Design, Production Engineering and Automotive Engineering (F07), University of Stuttgart, 70569 Stuttgart, Germany.
Sensors (Basel). 2025 Mar 29;25(7):2170. doi: 10.3390/s25072170.
Electric machines (EMs) of electrified vehicle drivetrains can be tested on drivetrain test benches at an early stage of development. In order to protect the EMs from premature damage or failure during testing, monitoring their thermal condition is important. Due to the package requirements of compact and powerful EMs with high-speed requirements and high-power densities, the heat build-up inside the motor during operation is particularly high. For this reason, fluid cooling with heat exchangers is increasingly being used in EMs. The EMs analysed in this work are water-cooled by a cooling jacket. This influences the heat flow inside the machine through heat transfer mechanisms, making it difficult to detect damage to the EMs. This paper presents a novel method for non-destructive and non-contact thermal condition monitoring of water-cooled EMs on drivetrain test benches using thermography. In an experimental setup, infrared images of an intact water-cooled EM are taken. A bearing of the EM's rotor is then damaged synthetically, and the experiment is repeated. The infrared images are then processed and analysed using appropriate software. The analysis of the infrared images shows that the heat propagation of the motor with bearing damage differs significantly from the heat propagation of the motor without bearing damage. This means that thermography opens up another method of condition monitoring for water-cooled EMs. The results of the investigation serve as a basis for future condition monitoring of water-cooled EMs on powertrain test benches using artificial intelligence (AI).
电动汽车传动系统的电机（EMs）在开发的早期阶段就可以在传动系统试验台上进行测试。为了保护电机在测试期间不发生过早损坏或故障，监测其热状态非常重要。由于紧凑且强大的电机的封装要求、高速要求以及高功率密度，电机在运行过程中的内热积聚特别高。因此，带有热交换器的液体冷却越来越多地应用于电机中。在这项工作中分析的电机由冷却套进行水冷。这通过热传递机制影响了电机内部的热流，使得难以检测到电机的损坏。本文提出了一种在传动系统试验台上使用热成像技术对水冷电机进行无损和非接触式热状态监测的新方法。在一个实验装置中，拍摄了一个完好的水冷电机的红外图像。然后对电机转子的一个轴承进行人为损坏，并重复该实验。接着使用适当的软件对红外图像进行处理和分析。对红外图像的分析表明，有轴承损坏的电机的热传播与无轴承损坏的电机的热传播有显著差异。这意味着热成像为水冷电机的状态监测开辟了另一种方法。该研究结果为未来在动力总成试验台上使用人工智能（AI）对水冷电机进行状态监测奠定了基础。
