Impact of lifetime model selections on the reliability prediction of IGBT modules in modular multilevel converters

Abstract

Abstract-Power cycling in semiconductor modules contributes to repetitive thermal-mechanical stresses, which in return accumulate as fatigue on the devices, and challenge the lifetime. Typically, lifetime models are expressed in number-of-cycles, within which the device can operate without failures under predefined conditions. In these lifetime models, thermal stresses (e.g., junction temperature variations) are commonly considered. However, the lifetime of power devices involves in crossdisciplinary knowledge. As a result, the lifetime prediction is affected by the selected lifetime model. In this regard, this paper benchmarks the most commonly-employed lifetime models of power semiconductor devices for offshore Modular Multilevel Converters (MMC) based wind farms. The benchmarking reveals that the lifetime model selection has a significant impact on the lifetime estimation. The use of analytical lifetime models should be justified in terms of applicability, limitations, and underlying statistical properties.

A Viable Mission Profile Emulator for Power Modules in Modular Multilevel Converters

“…As for the capacitor voltage, it operates in order to get a similar switching loss behavior as in real operation. It is determined by the current, blocking voltage and the junction temperature as [17] An evenly distributed switching action is assumed throughout the fundamental period in order to exclude the complex calculation of the exact switching time [20]. All three kinds of energy losses (E sw on , E sw off and E sw rec ) occur simultaneously with the total energy loss of E sw x (i arm , v sm , T j ) per switching action.…”

“…The arm current considering the current ripple is i arm = I 0 + I 1 sin(ωt + ϕ 1 ) + I r max sin(ω c t + ϕ r ), (17) where the triangle current ripple is overlapped by a sinusoidal waveform, and ω c and ϕ r are the angular frequency and the initial phase angle of the carrier in the current source.…”

Submodule Level Power Loss Balancing Control for Modular Multilevel Converters

“…where a 2 , a 1 and a 0 are the curve-fitting coefficients, i arm is the arm current, and V ref , T ref are the references of the blocking voltage and the junction temperature in the data-sheet respectively. The switching energy considering the impact of blocking voltage and junction temperature is [18]…”

Impact of Long-Term Mission Profile Sampling Rate on the Reliability Evaluation of Power Electronics in Photovoltaic Applications

“…10, the reliability estimation of the power stage can be carried out. By means of Reliability Block Diagram (RBD) analysis the individual reliability information of the components of interest are merged according to (7), and the unreliability curves of the power stage are obtained and shown in Fig. 11.…”

“…Unfortunately, the accuracy of the resulting reliability metrics is subject to many factors, such as: environmental / operating mission profiles [6], loss and thermal modeling, cycle counting method, damage accumulation method or the lifetime model itself [7]. All of these factors will introduce a certain degree of uncertainty.…”