Experimental Analysis of Powertrain Test Bed Dynamometers for Black Box-Based Digital Twin Generation
Research output: Contribution to book/conference proceedings/anthology/report › Conference contribution › Contributed › peer-review
Contributors
Abstract
The recent developments in the automotive industry denote a significant increase in embedded control units, algorithms and connectivity inside the vehicle and with its environment. All trends require a substantial increase in the virtualization of present development activities. Here, the deployed methods must be proven valid and optimized strategies for building and identifying real-time simulation models have to be developed. The context of the present work is the validation of low-frequency powertrain oscillations based on drivability-relevant properties at a full-vehicle level. An early powertrain validation at the subsystem level demands real-time modelling of the specimen, the test bed and the residual vehicle. The simulation models must be proven valid in the drivability-relevant frequency range of up to 30 Hz. Therefore, the reference test bed setup is presented together with the selected design of experiments. Then, a system identification process in the time and frequency domain is conducted to allow fast and reliable identification of the first torsional natural mode of the powertrain and the time characteristic of the dynos stated in dead time and group delay. In conclusion, the authors present a method for efficient drivability-related dynamometer characterization for blackbox-based modeling up to 1 kHz.
Details
Original language | English |
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Title of host publication | 2023 IEEE Transportation Electrification Conference & Expo (ITEC) |
Publisher | IEEE Xplore |
Pages | 1-6 |
Number of pages | 6 |
ISBN (electronic) | 979-8-3503-9742-0 |
ISBN (print) | 979-8-3503-9743-7 |
Publication status | Published - 25 Jul 2023 |
Peer-reviewed | Yes |
External IDs
Scopus | 85168249156 |
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Mendeley | 4dd45d85-827d-301f-87ef-fddc6384be93 |
ORCID | /0000-0002-0679-0766/work/141545031 |
Keywords
ASJC Scopus subject areas
Keywords
- Powertrain test bed, digital twin, group delay, system identification, transfer function estimation