Heat source and internal temperature estimation of an integrated modular motor drive in robotic application using inverse heat conduction problem

Electronic components inside integrated module is designed to endure harsh thermal condition. Information about interior temperature and heat sources is then crucial for the optimal design of the electronic components. However, because of the compact design and internal position within the housing, it is difficult to experimentally measure the heat sources and internal temperature. To handle this issue, this study presents a method for estimating the heat source and internal temperature distribution via an inverse heat conduction problem. A sequential time domain approach with Tikhonov regularization is employed to predict equivalent heat sources of motor and MOSFET from a few and noisy measured temperature data. Krylov subspace-based finite element model reduction is also utilized to increase computational efficiency of the proposed framework. As a result, the suggested IHCP framework can be synchronized with sensor systems, including thermocouples and can provide the essential information such as unmeasured heat sources and temperature contour. A 200 W BLDC motor drive module for a collaborative robot is taken into consideration to validate the suggested approach with a practical application. Well-designed experimental tests using the BLDC motor drive module are used to assess the accuracy and efficiency of the suggested approach. A heat dissipation design of the BLDC motor drive is also carried out to show off a good application of the suggested method.