Date of Award

Spring 4-1-2017

Document Type


Degree Name

Doctor of Philosophy (PhD)


Electrical, Computer & Energy Engineering

First Advisor

Robert Erickson

Second Advisor

Dragan Maksimovic

Third Advisor

Khurram Afridi

Fourth Advisor

David Jones

Fifth Advisor

Daniel Seltzer


With the stringent regulations on greenhouse gas emissions and constraints of energy sources, electrified vehicles have attracted attentions by automotive manufacturers and customers. Power conversion unit consisting of boost converter and traction inverter employed in conventional EV powertrain system exhibits low efficiency on EPA standard driving cycles such as US06, UDDS, or HWFET. To maintain high efficiency over a wide range of power and voltage, composite boost converter architecture has been introduced. This dissertation addresses the design optimization of power conversion unit with composite boost converter architecture. Comprehensive loss model including switching loss, conduction loss, and magnetic loss are developed, and the calibration process is proposed to reduce the loss model error over a wide range of power and voltage. Also, weighted loss method is proposed for a design optimization of boost converter on given driving cycles. The weighted loss method reduces computational efforts by a magnitude of three without the loss of optimization result accuracy, relative to the brute-force exhaustive search method. The Si-MOSFET composite boost converter is designed, and experimental results exhibit high efficiency over a wide range of power and voltage. Also, high volumetric and gravimetric power density are demonstrated with a SiC-MOSFET composite boost converter. For the traction inverter, the conventional Si-IGBT system is analyzed, and SiC-MOSFET traction inverter is designed. The SiC-MOSFET traction inverter shows superior loss reductions in urban driving cycle and semiconductor die area. The complete power conversion unit composed of the composite boost converter and the SiC-MOSFET traction inverter exhibits 98% of CAFE (Corporate Average Fuel Economy) average efficiency.