A Lifetime Estimation Technique for Voltage Source Inverters

On-Line Junction Temperature Monitoring of Switching Devices with Dynamic Compact Thermal Models Extracted with Model Order Reduction

“…The control algorithm is designed so as to provide a 50 Hz pure sine current computed by extracting a DCTM, which is then simulated [21], or with standard transient FEM simulations by activating one HS at a time, e.g., [32][33][34]. Figure 3 on a desktop PC equipped with an octa-core Intel i7-5960X and 64 GB RAM, leading to a total of 5 × 8 = 40 h for computing the whole ZTH(t) as required by fitting-based DCTMs, e.g., [18,20]. The proposed MOR procedure implemented in MATLAB lasts, instead, only 1.5 h for extracting Equations (4)- (6) with subsequent negligible time (1 s) for performing the ZTH(t) simulations, thus providing a fast model extraction.…”

“…Since DCTMs are usually assumed to be time-invariant, this approach requires only the measurement of the dissipated power, which is quite easy to carry out with respect to TSPs-based methods. This is a widely employed procedure with a broad range of adopted DCTMs and their extraction procedures [16][17][18][19][20]. In [20], the DCTM is obtained in a two-step process: at first, a set of preliminary transient simulations with the Finite Elements Method (FEM) is performed to model the thermal behavior of the system under test; subsequently, an equivalent circuit is synthesized in the form of a Foster network, characterizing the active devices' average temperature.…”

“…Most DCTMs are normally built in the Matlab/Simulink environment [18], and they can be unsuitable for on-line applications. Hence, there is an emphasis on the need for a real-time implementation of the DCTMs in [17] and the more recent [19].…”

Improved reliability of single-phase PV inverters by limiting the maximum feed-in power

“…There are many cycle counting algorithms reported, e.g. level crossing counting, rain-flow counting, and simple range counting methods [13]- [15], [26], which can be used to appropriately interpret the thermal loading profile according to a dedicated lifetime model. Then, the lifetime can be calculated with the extracted information.…”

“…Hence, the varying operation conditions due to the intermittent nature of solar energy has been one of the challenges to perform reliability analysis in PV systems. Currently, most of the existing reliability prediction methods for the lifetime estimation of power devices in PV inverters only consider either shortterm mission profiles [13], [14] or long-term mission profiles with a low data-sampling frequency, where the effects of small temperature cycles are not considered [19]. Moreover, the widely used lifetime models unfortunately consider only a few failure modes, e.g.…”