Submitted:
20 January 2018
Posted:
23 January 2018
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Abstract
This paper proposes a novel method for optimizing the Cauer-type thermal network model considering both the temperature influence on the extraction of parameters and the errors caused by the physical structure. In terms of prediction of the transient junction temperature and the steady-state junction temperature, the parameters of conventional Cauer-type are modified, and the general method for estimating junction temperature is studied by using the adaptive thermal network model. The results show that junction temperature estimated by adaptive Cauer-type thermal network model is more accurate than that of the conventional model.
Keywords:
insulated gate bipolar transistor (IGBT)
; thermal network
; parameter identification
; junction temperature
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