Optimization of Induction Machine Design for Electric Vehicle Powertrain
(2023) 2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023 In 2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023- Abstract
This paper proposes a methodology to include induction machine (IM) in an optimization scheme for EV powertrains using Particle Swarm Optimization (PSO) as the optimization algorithm. The IM model is developed based on finite element analysis (FEA) and all the losses are estimated. The main objective is to generate a large database of base designs in a computationally efficient but accurate way. To perform the optimization, scaling methods are used. Detailed transmission and inverter models are also considered based on previous work to estimate the overall powertrain efficiency. The optimization case study shows how the optimizer evaluates a large number of alternatives and picks the optimal IM design and associated transmission and... (More)
This paper proposes a methodology to include induction machine (IM) in an optimization scheme for EV powertrains using Particle Swarm Optimization (PSO) as the optimization algorithm. The IM model is developed based on finite element analysis (FEA) and all the losses are estimated. The main objective is to generate a large database of base designs in a computationally efficient but accurate way. To perform the optimization, scaling methods are used. Detailed transmission and inverter models are also considered based on previous work to estimate the overall powertrain efficiency. The optimization case study shows how the optimizer evaluates a large number of alternatives and picks the optimal IM design and associated transmission and inverter. The proposed methodology can serve as a basis for future research on powertrain optimization for dual-motor driven vehicles.
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- author
- Lu, Meng LU ; Domingues-Olavarria, Gabriel ; Marquez-Fernandez, Francisco J. LU ; Byden, Hannes LU and Alakula, Mats LU
- organization
- publishing date
- 2023
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Induction machine, loss estimation, Powertrain optimization, PSO
- host publication
- 2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023
- series title
- 2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023
- conference location
- San Francisco, United States
- conference dates
- 2023-05-15 - 2023-05-18
- external identifiers
-
- scopus:85172729906
- ISBN
- 9798350398991
- DOI
- 10.1109/IEMDC55163.2023.10238871
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 2023 IEEE.
- id
- bddd7877-bb55-4cf3-89f8-02ab40081b96
- date added to LUP
- 2024-01-08 14:45:52
- date last changed
- 2024-02-09 10:44:29
@inproceedings{bddd7877-bb55-4cf3-89f8-02ab40081b96, abstract = {{<p>This paper proposes a methodology to include induction machine (IM) in an optimization scheme for EV powertrains using Particle Swarm Optimization (PSO) as the optimization algorithm. The IM model is developed based on finite element analysis (FEA) and all the losses are estimated. The main objective is to generate a large database of base designs in a computationally efficient but accurate way. To perform the optimization, scaling methods are used. Detailed transmission and inverter models are also considered based on previous work to estimate the overall powertrain efficiency. The optimization case study shows how the optimizer evaluates a large number of alternatives and picks the optimal IM design and associated transmission and inverter. The proposed methodology can serve as a basis for future research on powertrain optimization for dual-motor driven vehicles.</p>}}, author = {{Lu, Meng and Domingues-Olavarria, Gabriel and Marquez-Fernandez, Francisco J. and Byden, Hannes and Alakula, Mats}}, booktitle = {{2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023}}, isbn = {{9798350398991}}, keywords = {{Induction machine; loss estimation; Powertrain optimization; PSO}}, language = {{eng}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, series = {{2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023}}, title = {{Optimization of Induction Machine Design for Electric Vehicle Powertrain}}, url = {{http://dx.doi.org/10.1109/IEMDC55163.2023.10238871}}, doi = {{10.1109/IEMDC55163.2023.10238871}}, year = {{2023}}, }