Quispe Parillo, Alexander Leandro (2025) Dynamic Characterization and Optimization of High-Power IGBT Modules: Advanced Gate Driving Strategies. PhD thesis, University of Sheffield.
Abstract
In contemporary power electronic systems, the primary workhorse for high-power applications is the Insulated Gate Bipolar Transistor (IGBT) power modules, playing an increasingly crucial role. These modules find applications in various domains such as renewable energy systems, transportation traction, high-voltage electric power transmission systems, and industrial motor drives. This thesis focuses on exploring the dynamic characteristics of IGBT modules and the latest techniques in gate driving.
To enhance the switching characteristics of high-power IGBT modules, this research
scrutinises and compares potential driving parameters for advanced active driving strategies.
Additionally, an innovative active gate driver based on a voltage-controlled current source is designed and experimentally validated. The characterization of high-power IGBT modules and the validation of the active gate driver's efficacy are conducted using a double pulse test platform, guided by a design procedure. The application of designed computer-aided software for control and data post-processing serves to enhance both the efficiency and accuracy of the test platform. Furthermore, the controllability of transient current and voltage slopes during the turn-off transition of high-power IGBT modules is investigated. An effective and efficient evaluation method is put forward and validated for assessing the controllability of the modules. Finally, an optimization method using the proposed gate driver is implemented. This optimization method employs a genetic algorithm to determine the optimal gate driving pattern, ensuring low switching losses and overshoot in the IGBT.
In conclusion, this work is concentrated on the dynamic characterization of the IGBT, the design of a voltage-controlled current source gate driver, and optimization using a genetic
algorithm.
Metadata
| Supervisors: | Foster, Martin and Stone, David |
|---|---|
| Keywords: | IGBT, Power Semiconductors, Dynamic Characterisation, Gate Driver, Dynamic behaviour analysis, Energy Losses, , Switching Optimization, Gate Pattern, FPGA, Optimisation Algorithm, NSGA-II, Genetic Algorithm, |
| Awarding institution: | University of Sheffield |
| Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Electronic and Electrical Engineering (Sheffield) |
| Date Deposited: | 08 Dec 2025 09:36 |
| Last Modified: | 08 Dec 2025 09:36 |
| Open Archives Initiative ID (OAI ID): | oai:etheses.whiterose.ac.uk:37874 |
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