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| Content Provider | The American Society of Mechanical Engineers (ASME) Digital Collection |
|---|---|
| Author | Ahmed, M. Ali Söffker, Dirk |
| Copyright Year | 2018 |
| Abstract | Optimal power management in real-time is a core technology of hybrid electric vehicles (HEVs). The online application of optimized power split ratios based on driver demand is a promising approach allowing near optimal power handling decisions in real-time. However, the fulfillment of exact power delivery (driveability) is an open challenge of this approach due to interpolation of driver’s demand to the optimized discrete solutions. Finding balanced power management that handles unscheduled loads and sustains required power conversion efficiency may significantly improve the experimental application of this approach. This work proposes an observer-based control method integrated to the power management system that ensures better driveability with minimal effect on power handling optimality. Modeling of traction system for observer design is based on a simplified brushless DC motor model. Identification of system parameters is achieved by a newly introduced error minimization algorithm using NSGA-II to obtain the same dynamic response as the original system. Results analysis shows 7% reduction of power consumption and 98% improvement of driveability at minimal mitigation of power conversion efficiency. |
| Sponsorship | Design Engineering Division Computers and Information in Engineering Division |
| File Format | |
| ISBN | 9780791851784 |
| DOI | 10.1115/DETC2018-85220 |
| Volume Number | Volume 3: 20th International Conference on Advanced Vehicle Technologies; 15th International Conference on Design Education |
| Conference Proceedings | ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference |
| Language | English |
| Publisher Date | 2018-08-26 |
| Publisher Place | Quebec City, Quebec, Canada |
| Access Restriction | Subscribed |
| Subject Keyword | Dynamic response Energy consumption Motors Hybrid electric vehicles Traction Modeling Engines Stress Design Errors Interpolation Algorithms Energy conversion Electric vehicles |
| Content Type | Text |
| Resource Type | Article |
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