Multi-Objective Optimization Design for DC-Link Capacitor of Motor Driver
The capacitor is a common weak point in motor drive system design, necessitating targeted selection, design, and optimization of capacitor banks within these systems. Traditional capacitor design often relies on engineering experience, usually meeting specific capacitance and voltage requirements through simple parallel or series connections of capacitors. This approach often fails to fully optimize volume, cost, and reliability. This paper uses comprehensive theoretical modeling to optimize capacitor module design, effectively balancing capacitor lifespan, cost, and volume. For the design and selection of DC-link capacitors in a 1kW permanent magnet synchronous motor drive system, a multi-objective optimization design method for capacitor banks is proposed. The study treats the individual capacitance values of parallel capacitors as variables, significantly enhancing the overall performance of the capacitor module through precise optimization and the introduction of necessary constraints in the selection design. The proposed method is validated with a 1kW permanent magnet synchronous motor drive system. The optimization results show that under the guidance of a multi-objective optimization framework, the designed DC-link capacitor module meets physical size requirements while achieving overall optimization in terms of volume, cost, and lifespan, significantly improving system reliability.
Authors
- Xueliang Wei (ORCID: https://orcid.org/0000-0003-3571-1702)
- Yu Zheng (ORCID: https://orcid.org/0000-0001-8242-850X)
- Xiang Hao (ORCID: https://orcid.org/0000-0002-3782-1211)
- K. David Huang (ORCID: https://orcid.org/0000-0002-1746-3170)
- Qian Liu (ORCID: https://orcid.org/0000-0001-5341-1290)
Institutions
- Wuhan University of Technology (CN)
- Hong Kong University of Science and Technology (HK)
- China University of Petroleum, Beijing (CN)
- University of Hong Kong (HK)
Publication Details
- Published
- 2024-11-08
- DOI
- https://doi.org/10.1109/isesc63657.2024.10785435
- Primary Topic
- Electric and Hybrid Vehicle Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00