A Combined Design Procedure of High-Speed/High-Power PMSMs for an Adiabatic Compressed Air Energy Storage System

• Published in: IEEE transactions on industry applications Vol. 60; no. 1; pp. 1 - 13
• Main Authors: Floris, Andrea, Damiano, Alfonso, Serpi, Alessandro
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-01-2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adiabatic compressed air energy storage system; Adiabatic flow; Combined design procedure; Compressed air; Compressors; Configuration management; Cost function; Costs; Design specifications; Electromagnetics; Energy storage; Finite element analysis; Finite element method; Gears; Genetic algorithms; High speed; Low speed; Mathematical analysis; Modular design; Modular structures; Modular systems; Optimization; Permanent magnets; Preliminary designs; Synchronous machines; Synchronous motors; Torque; Turbines
• ISSN: 0093-9994; 1939-9367
• DOI: 10.1109/TIA.2023.3336312

This paper presents a Combined Design Procedure (CDP) applied to modular high-speed/high-power Permanent Magnet Synchronous Machines (PMSMs) for an Adiabatic Compressed Air Energy Storage system (ACAES). Particularly, the modular structure enables higher maximum speed and flexibility compared to a monolithic PMSM as a suitable number of identical mechanically series-connected modules can be employed. These share the same speed and contribute together to the high overall power required by ACAES, thus avoiding excessive volume requirements and low-speed operation. The modular PMSM design has been accomplished by the proposed CDP, which exhibits multi-physic and optimization features thanks to both analytical and Finite Element Analysis (FEA) approaches. The former enables a rapid preliminary design that satisfies a given objective function, by complying with all electromagnetic and mechanical constraints. Such a preliminary design is then refined by the FEA approach, which accounts also for thermal constraints, and guarantees a better cost function optimization through a genetic algorithm. In this regard, different objective functions have been considered, leading to different PMSM configurations. The corresponding performance analysis reveals that all PMSM configurations comply with electromagnetic, mechanical, and thermal constraints, by guaranteeing design specifications as well