Modulation methods for electric traction drives

Project goal

Scientific analysis of modulation methods and development of a systematic parameterization strategy for optimal selection of the modulation strategy for electric traction drives.

Electric traction drives essentially consist of the components high-voltage battery, inverter and electric motor. The inverter supplies the rotating field motor with AC voltage so that the resulting current generates exactly the torque requested by the vehicle control unit in the motor and transmits it to the vehicle axle via the transmission. Conversely, when the vehicle decelerates, the inverter charges the high-voltage battery by recuperating the vehicle's kinetic energy. In addition to the control unit for monitoring and regulating the powertrain, the inverter includes a pulse inverter with DC link. By varying the duty cycles, it converts the fundamental voltage requested by the motor control into the pulsed output voltages. For this purpose, the time characteristic of the AC voltage is modulated in a time-discrete but amplitude-continuous manner into the duty cycle of the output voltage.

The pulse width modulation can be realized by different methods. The choice of the modulation method represents a degree of freedom on the software side in that it has a decisive influence on the shape of the pulse pattern. Thus, the shape of the pulse pattern directly or immediately influences, among other things, the AC current ripple, switching losses, motor losses, DC voltage ripple and energy efficiency. The latter, in addition to the capacity of the high-voltage battery, contributes significantly to the range and thus attractiveness of the electric traction drive. This research project aims to scientifically analyze and systematically optimize the "modulation" degree of freedom, taking into account typical requirements of the electromobility industry.

The Ostbayerische Technische Hochschule Amberg-Weiden is working on the research project as part of a cooperative doctorate with the Technische Universität Darmstadt.

Project duration

July 2022 to August 2026 (50 months)