Thermal Parameter and State Estimation for Digital Twins of E-Powertrain Components
Open accessAbstract
The performance of powertrain components in electric vehicles is tightly intertwined with their thermal behavior. In practical applications, their temperature must be monitored and kept below certain thresholds to avoid performance drops and failure. Sensors, however, cannot always be placed at critical locations. Instead, it is possible to use numerical models to estimate relevant magnitudes during system operation. Thermal effects in electric and electronic components can be represented in a compact way using lumped-parameter equivalent circuits. These can be combined with sensor readings from the device under study to develop digital twins and use them to monitor temperatures during test and operation. In this paper, we put forward a method to generate thermal digital twins of e-powertrain elements such as power inverters. The thermal equivalent circuit equations are obtained from a general-purpose simulation software tool and optimized to enable real-time execution. Kalman filters are then used to fuse the simulation results from this model and sensor measurements of component temperatures. The proposed method provides a way to estimate the inputs and parameters of the thermal circuit and can be used to avoid the drift of the simulation away from actual component behavior. The performance of this approach is demonstrated with a simple benchmark example and the thermal equivalent circuit of a three-phase inverter.
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Most components involved in electric vehicles are multi-physics systems incorporating interactions of mechanical, electronic, thermal and other phenomena.
“In the category of EVs, these present a challenge to design engineering due to the fact that most of the components involved are multi-physics systems incorporating interactions of mechanical, electronic, thermal and other phenomena [73].”
From Digital Twin Technology Challenges and Applications: A Comprehensive Review (2022) · cites this paper as [73]
Multi-physics modeling is an important part of digital twin implementation for electric vehicles.
“This makes multi-physics modeling an important part of DT implementation for EVs.”
From Digital Twin Technology Challenges and Applications: A Comprehensive Review (2022) · cites this paper as [73]
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- Authors
- Rodriguez, B., Sanjurjo, E., Tranchero, M., Romano, C., & Gonzalez, F.
- Affiliations
- Universidade da Coruña (ES)
- Venue
- IEEE Access
- Published
- 2021
- Volume
- 9
- Pages
- 97384-97400
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W3181692541
- Cited by
- 49
- References
- 32
- Citations by year
- 2026: 11 · 2025: 7 · 2024: 11 · 2023: 15 · 2022: 5
- FWCI
- 2.52
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- IEEE Access (publishedVersion, cc-by)
- RUC (Universidade Da Coruña) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Electronic Components and Systems for European Leadership (783174)
- Xunta de Galicia (ED431B2016/031)
- Secretara de Estado de Investigacin Desarrollo e Innovacin (RYC-2016-20222, TRA2017-86488-R)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Electric and Hybrid Vehicle Technologies
- Physical Sciences › Engineering › Control and Systems Engineering › Control Systems and Identification
- Physical Sciences › Engineering › Control and Systems Engineering › Real-time simulation and control systems
- Keywords
- digital twin, electric vehicle drivetrain, thermal parameter estimation, lumped parameter equivalent circuit, inverter, Kalman filter, sensor fusion, temperature monitoring, real-time simulation, three-phase inverter, electric vehicles
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