Radiation Modeling of COTS Power Converters in a Highly Shield Space Environment

Commercial off-the-shelf (COTS) electronics systems operated in highly-shielded enclosures (HSE) will all require power supplies or DC/DC converters to power the signal processing electronics. nbsp;Most power supplies are based on switching converters that require power transistors, diodes, gate drivers, and control ICs that regulate the power. These components in a COTS assembly will all be unhardened commercial components that are sensitive to single event effects (SEE).nbsp; Our objective is to develop the tools to predict which of these components are capable of tolerating the SEE and later validate the tools by experiments.Inside an HSE in space, the residual particle spectrum after filtering the space heavy-ion environment will consist of neutrons, protons, and alpha particles. These particles, when incident on a semiconductor device can produce secondary ion species through collisions, resulting in short-range energetic ions that can cause single-event effects. Consequently, the question addressed in the proposed work is whether commercial power converters can tolerate the secondary ion effects that will occur when operated in a highly-shielded environment.Busek and Vanderbilt University propose to use radiation transport modeling to determine the particle spectrum inside packaging enclosures and the result of the particles in the interior package environment impinging on semiconductor devices and producing secondary ions. We will calculate the spectrum of the secondary ions in Phase I. We will support the modeling with a low-energy ion test on representative components with a low-cost ion beam to find experimentally their sensitivities to the secondary ions.In Phase II, a high-energy accelerator heavy-ion test will be conducted with the calculated secondary ion spectrum as a proxy test. nbsp;We will also seek opportunities to demonstrate a COTS DC/DC converter in HSE such as the International Space Station as a validation of the modeling approach and prediction.