Monitoring of the Cooling System via Thermal Parameters

Zheng, Shuai; Du, Xiong; Zhang, Jun; Yu, Yaoyi

doi:10.1109/access.2019.2942326

Cited by 8 publications

(2 citation statements)

References 22 publications

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“…Because with the degradation of the thermal grease caused by the pump-out and dry-out phenomenon, the heat transfer path will be affected, so it is necessary to monitor the change of the thermal grease impedance. As proposed in [25]- [27], by utilizing the time constants of cooling curves, the degradation of thermal impedance can be monitored. It should be noted that this method is based on the Cauer thermal network model.…”

Section: ) Parameter Extraction Of Thermal Grease Impedancementioning

confidence: 99%

Improved Temperature Monitoring and Protection Method of Three-Level NPC Application Based on Half-Bridge IGBT Modules

et al. 2022

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The overheating stress of power devices is the main cause of converter system failures, so real-time temperature acquisition, as well as timely over-temperature protection, under various operating conditions are key to achieving a more reliable energy conversion. In this paper, an improved threedimensional (3-D) coupled thermal model for insulated gate bipolar transistors (IGBTs) and related heatsink is constructed by considering the thermal coupling effects at both the device-and the module level. Furthermore, the coupled thermal impedance parameters are thereby extracted based on the finiteelement method (FEM), so that the dynamic loss and transient temperature distribution under actual working conditions can be obtained based on this electro-thermal coupling model. Meanwhile, to avoid the overheating damage of power devices due to untimely action of the negative temperature coefficient (NTC) thermistor over-temperature protection, this article aims at the idle IGBT device in the three-level neutral-point clamped (NPC) application using IGBT half-bridge modules, combined with the emitter terminal temperature, and finally realizes the multiple over-temperature protection settings. The improved temperature monitoring methods proposed in this paper are realized by the drive and control circuits and verified through simulation and experimental results.INDEX TERMS Reliability, half-bridge IGBT module, three-level NPC topology, temperature monitoring, over-temperature protection.

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Section: ) Parameter Extraction Of Thermal Grease Impedancementioning

confidence: 99%

Improved Temperature Monitoring and Protection Method of Three-Level NPC Application Based on Half-Bridge IGBT Modules

et al. 2022

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“…So how to apply it to practical engineering remains to be studied. [16] studied the operation state prediction of the forced air cooling system, but the scheme is an offline monitoring scheme, workable only during the downtime of equipment.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Prediction Method for Heat Dissipation State of Converter Heatsink

Jia

Chen

et al. 2023

IEEE Access

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S Currently, the offline manual periodic detection method is a well-established practice in detecting the thermal state of the converter heatsink. This method, however, is huge in maintenance costs. To lower maintenance costs and improve maintenance efficiency in detecting the thermal dissipation state, this paper proposes an intelligent online prediction scheme based on Gauss-Newton iteration method. Firstly, the power loss model of the power module is established according to the characteristics of IGBT and FWD. The power loss of the power device is then calculated in real time with the voltage and current parameters of the converter. Next, the transient thermal model of the heatsink is established based on thermodynamics theory. And the calculation method of steady thermal resistance of heatsink based on Gauss-Newton iteration method is proposed according to the model. The transient thermal impedance data allow for timely prediction of thermal resistance of the heatsink and characterize the thermal state of the heatsink. Finally, with the help of DSP28377D, an experimental platform is built to verify the scheme. Results show that this method can realize intelligent prediction of thermal state online.

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