Hierarchical Parameter Calibration of Digital Twins at Ford Motor Company
We propose a hierarchical calibration framework for digital twins that accounts for parameter structures. Applied to real-world electric vehicle digital twin from Ford Motor Company, the method improves calibration accuracy and enables prediction of trip-specific parameters for future driving conditions.
Authors
- Jaeshin Park (ORCID: https://orcid.org/0009-0002-4347-5914)
- Yashodeep Lonari
- Eunshin Byon (ORCID: https://orcid.org/0000-0002-2506-1606)
- Chenfei Li (ORCID: https://orcid.org/0000-0001-5607-4015)
- Quazi Hussain
- William Bailey
Institutions
- Ford Motor Company (United States) (US)
- University of Michigan (US)
- Ford Motor Company (Czechia) (CZ)
Publication Details
- Journal
- INFORMS Journal on Applied Analytics
- Published
- 2026-05-22
- DOI
- https://doi.org/10.1287/inte.2025.0259
- Primary Topic
- Digital Transformation in Industry
- Type
- article
- Field-Weighted Citation Impact
- 0.00