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Optimize electric motors design and controls considering torsional vibrations and acoustic noise
Frontload qualitative NVH risk assessment
Electric machines are key elements to guarantee optimal vehicle performance, but they also have a strong impact on the system level NVH performance. The machine torque waveform may contain harmonics that may have implications on the control, power output, noise, vibration, and durability.
Being able to address those issues requires the implementation of a comprehensive process including the optimization of design trade-offs for torque and torque ripple by the machine designer, the machine’s vehicle level integration at various fidelity levels, and collaborations with the NVH teams to assess the influence of different design topologies and control strategies.
In this webinar, our experts will explain how to use simulation to improve the electromagnetic and vibro-acoustic design of e-machines, and to increase performance, reliability and durability levels.
Fine-tuning electric motors design for increased efficiency and optimal torsional vibration
During this 45-minutes session, we’ll introduce possible solutions to:
- Optimize machine design efficiency while limiting torque ripple
- Create and export machine models of various fidelities for system-level and NVH analyses
- Check the impact of the integration of the selected e-machine in the driveline on torsional vibration
- Optimize machine controls to limit torsional vibrations
- Assess e-motor noise and identify system sensitivities during the conceptual design phase
About the speakers
Business Development Manager, Siemens Digital Industries Software
Lionel is the Business Development Manager for System simulation activities, focusing on the electrification of ground transportation. He has a master's degree in mechanical engineering and is involved in multi-domain system simulation since 1999.
Product Manager, Electric Machines, Siemens Digital Industries Software
Tanvir has worked extensively on the design and development of electric motors for the last 12 years as a product manager, researcher, software developer, and application engineer. Between 2013 and 2016, Tanvir worked as a research engineer at McGill University’s Computer and Electrical Engineering Department in the Automotive Partnership Canada (APC) project. He worked with industrial partners to deliver R&D results for commercial development. Tanvir obtained his Ph. D. in computational physics from McGill University in 2006.
Technical Expert, Siemens Digital Industries Software
Stefano Orlando has been with Siemens Digital Industries Software for 12 years, working in various roles in the Engineering and Consulting services division. He is currently a technical expert responsible for developing and deploying new technologies related to car body concept design and NVH for e-powertrains, including early stage BiW concept design and NVH characterization of e-motors, advanced CAE modeling of laminated structures, model order reduction techniques for improving simulation process efficiency, etc.
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