This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
Virtual Prototyping of Electric Drive Systems for System-Level Parameter Studies and Optimization
Technical Paper
2014-01-1876
ISSN: 0148-7191, e-ISSN: 2688-3627
Annotation ability available
Sector:
Language:
English
Abstract
As the demand for electric motors and drives grows, designers and manufacturers are faced with the challenge of understanding the effects of often non-deterministic duty cycles on their products. Too often, flaws in the design that can lead to failure only come to light when a prototype is built, or worse, after the product has been launched, leading to delays in product releases or costly recalls.
To help mitigate these risks, designers are increasingly turning to simulation technologies that not only allow the engineer to implement the electric drives and motors but also all the various engineering factors, such as mechanical loads, vibrations and thermal effects, together in a single “virtual prototype” to get a clearer idea of how the whole system will behave over multiple duty cycles. Furthermore, if the resulting model can be fully parameterized it is then possible to perform sensitivity studies to determine which parameters will have the greatest influence on the overall behavior and therefore focus on them to understand effect of parameter variation through the lifetime of the product.
This paper will illustrate the use of modeling tools that allow engineers to develop high-fidelity multi-domain models of complex engineering systems and then generate fully parameterized code for high-speed execution for either parameter optimization or real-time implementation for Hardware-in-the-Loop testing. We illustrate these concepts through the use of a hybrid-electric vehicle (HEV) example.
Authors
Citation
Slough, S., Goossens, P., Schwarz, C., and Dao, T., "Virtual Prototyping of Electric Drive Systems for System-Level Parameter Studies and Optimization," SAE Technical Paper 2014-01-1876, 2014, https://doi.org/10.4271/2014-01-1876.Also In
References
- Friebe , J. , Schwartz , C. , Dao , T. Model-based Design of Hybrid Electrical Vehicle Devices using Automated Optimization Strategies ISKO technical paper
- Bauman , J. Advances in Fuel Cell Vehicle Design PhD thesis University of Waterloo 2008
- Maplesoft 2013 www.maplesoft.com/contact/webforms/whitepapers/enginemodels.aspx
- Heywood , J.B. Internal Combustion Engine Fundamentals McGraw hill 1988
- Moskwa , J.J. Automotive Engine Modeling for Real-Time Control PhD dissertation Massachusetts Institute of Technology 1988