Ensure Greater Efficiency in Electric Motors
As industrial equipment becomes more complex, leading industrial OEMs are finding ways to build more effective and trustworthy simulations. This can be especially helpful when modeling electric motors, which can be laborious and cumbersome.
In this webinar you will learn about the latest simulation techniques to predict electric motor performance by Leveraging 3D/2D finite element approaches to predict electric motor performance and get immediate feedback on a design’s performance. Leverage those models into system-level simulation so that proper motor sizing, overall energy efficiencies, control strategies, and control precision can be tested. Also, you can drive the models with intelligent design exploration methods and find better designs, faster.
Finite Element Simulation & System Simulation for Electric Motor Design
In this webinar, we will also discuss the benefits of using finite element simulation for electric motor design. In addition, we will present system simulation approaches that allow fast and accurate transient analysis for system-level performance. We will demonstrate the integration of an electric motor in the design of a delta robot, perform sizing studies, evaluate robot motion precision and related controls validation.
Electric Motor Analysis and Prediction
Key webinar learnings:
- How to drive design decisions with simulation and optimize motor design
- How to assess electric motor performance and its impact on the system performance
- How to detect system integration issues early
Electric Motor Design Capabilities in Simcenter Software
- Optimal sizing of electrical motors to reach target performances
- Explore trade-offs; performance, cost, and energy consumption
- Multi-physics simulation of the complete system to assess interactions
- Evaluate the impact of PLC code upgrades on performance and electric consumption
Meet our Subject Matter Expert on Electric Motor Design
Paul Weal. Portfolio Development Executive Siemens Simcenter
Paul has over 30 years of engineering experience focusing on the application of computer modeling and simulation towards the product development of Industrial Machines. He is skilled in PLM Performance Engineering, Model-Based Systems Engineering, and Finite Element Analysis. He holds a Bachelor of Science degree in Electrical Engineering from Southern Illinois University.