Bayesian Optimization of PCB-Embedded Electric-Field Grading Geometries for a 10 kV SiC MOSFET Power Module
| dc.contributor.author | Cairnie, Mark A. Jr. | en |
| dc.contributor.committeechair | DiMarino, Christina M. | en |
| dc.contributor.committeemember | Ngo, Khai D. T. | en |
| dc.contributor.committeemember | Boroyevich, Dushan | en |
| dc.contributor.department | Electrical and Computer Engineering | en |
| dc.date.accessioned | 2021-06-02T16:45:06Z | en |
| dc.date.available | 2021-06-02T16:45:06Z | en |
| dc.date.issued | 2021-04-28 | en |
| dc.description.abstract | A finite element analysis (FEA) driven, automated numerical optimization technique is used to design electric field grading structures in a PCB-integrated bus bar for a 10 kV bondwire-less silicon-carbide (SiC) MOSFET power module. Due to the ultra-high-density of the power module, careful design of field-grading structures inside the bus bar is required to mitigate the high electric field strength in the air. Using Bayesian optimization and a new weighted point-of-interest (POI) cost function, the highly non-uniform electric field is efficiently optimized without the use of field integration, or finite-difference derivatives. The proposed optimization technique is used to efficiently characterize the performance of the embedded field grading structure, providing insights into the fundamental limitations of the system. The characterization results are used to streamline the design and optimization of the bus bar and high-density module interface. The high-density interface experimentally demonstrated a partial discharge inception voltage (PDIV) of 11.6 kV rms. When compared to a state-of-the-art descent-based optimization technique, the proposed algorithm converges 3x faster and with 7x smaller error, making both the field grading structure and the design technique widely applicable to other high-density high-voltage design problems. | en |
| dc.description.abstractgeneral | Innovation trends in electrical engineering such as the electrification of consumer and commercial vehicles, renewable energy, and widespread adoption of personal electronics have spurred the development of new semiconductor materials to replace conventional silicon technology. To fully take advantage of the better efficiency and faster speeds of these new materials, innovation is required at the system-level, to reduce the size of power conversion systems, and develop converters with higher levels of integration. As the size of these systems decreases, and operating voltages rise, the design of the insulation systems that protect them becomes more critical. Historically, the design of high-density insulation system requires time-consuming design iteration, where the designer simulates a case, assesses its performance, modifies the design, and repeats, until adequate performance is achieved. The process is computationally expensive, time-consuming, and the results are not easily applied to other insulation design problems. This work proposes an automated design process that allows for the streamlined optimization of high-density insulation systems. The process is applied to a 10 kV power module and experimentally demonstrates a 38\% performance improvement over manual design techniques, while providing an 8 times reduction in design cycle time. | en |
| dc.description.degree | M.S. | en |
| dc.format.medium | ETD | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.uri | http://hdl.handle.net/10919/103566 | en |
| dc.language.iso | en_US | en |
| dc.publisher | Virginia Tech | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject | Bayesian Optimization | en |
| dc.subject | Packaging | en |
| dc.subject | Silicon-Carbide | en |
| dc.subject | Power Electronics | en |
| dc.subject | Partial Discharge | en |
| dc.subject | Finite element method | en |
| dc.title | Bayesian Optimization of PCB-Embedded Electric-Field Grading Geometries for a 10 kV SiC MOSFET Power Module | en |
| dc.type | Thesis | en |
| thesis.degree.discipline | Electrical Engineering | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | masters | en |
| thesis.degree.name | M.S. | en |