Project

Selection, design and control of electromagnetic torque ripple reduction for drivetrains (Torque-Ripple_Reduction)

Code
180N1218
Duration
01 March 2019 → 30 November 2021
Funding
Regional and community funding: various
Research disciplines
  • Engineering and technology
    • Computer aided engineering, simulation and design
    • Mechanical drive systems
Keywords
drivetrains
 
Project description

This project aims to help the industry to achieve higher performing yet cost-efficient drive systems by evaluating new innovative concepts and new controller designs for torque ripple suppression. The models developed on the basis of these concepts and the new controller models will form the basis of a model-based design tool for drive systems with torque ripple suppression mechanisms. This project will build on the results and knowledge obtained in previous Flanders Make projects such as EMVeMFP7, EMtechno and Profensto.

Concrete objectives and criteria

The aim of this project is to develop better drive systems, with a 20% reduction in torque ripple, without an increase in energy consumption and with a minimal increase in cost. The drive train must be able to cope with varying loads and varying system behaviour. These drive systems must be designed in a systematic manner and with a minimum time to market. This will be realized through

  • new innovative (electro) magnetic components,
  • New designs for the drive system controller
  • new tools for drive system design, with optimized drive parameters and an optimized controller.

To achieve this ultimate goal, the following objectives have been set:

Goals in the field of generic technology

  • Mathematical models and design tools for an (adaptive) magnetic compensator will be developed and experimentally validated.
  • New controller designs for drive systems with and without magnetic compensator will be developed and experimentally validated.
  • A model-based drive system design tool will be developed that selects the various drive system components, determines their dimensions, while optimizing controller design. The tool will also be experimentally validated.