A novel reliability estimation methodology towards the design and implementation of symmetric multilevel inverter for long run applications

Abstract

Multilevel inverters (MLIs) are gaining attention in numerous applications due to their better performance attributes. Still, their utility in long-run applications remains a critical concern due to the reliability issues. This work proposes a novel reliability estimation methodology tailored specifically for MLIs. The proposed reliability method employs advanced simulation techniques and statistical models to estimate the failure probabilities of critical components within the MLI. The proposed methodology provides a more optimal assessment of the MLI's expected reliability over time. This enables designers and engineers to make informed decisions regarding component selection, system configuration, and maintenance schedules to enhance the long-term reliability of the MLI. Considering the drawbacks of the existing MLIs, this work has proposed a new symmetrical 7-level inverter with promising functional and reliability traits. The proposed topology appears to surpass existing topologies in several key metrics, including switching losses, reliability, THD, and component count. The performance of the proposed MLI has been validated through hardware results. These results show that the reliability methodology implemented can accurately estimate the MLI's reliability across various scenarios, enabling the identification of potential failure points and the formulation of strategies to mitigate reliability risks.