An Axial Parallel Memory Machine with DC-Bias Flux-Adjustment Capability.
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| Title: | An Axial Parallel Memory Machine with DC-Bias Flux-Adjustment Capability. |
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| Authors: | Zheng, Yanwen1,2 (AUTHOR), Shan, Yuanyuan2,3 (AUTHOR), Qin, Ling1,2,3 (AUTHOR) 24310119@tongji.edu.cn |
| Source: | Energies (19961073). May2026, Vol. 19 Issue 10, p2368. 21p. |
| Subject Terms: | *Permanent magnets, *Finite element method, *Magnetic coupling, *Genetic algorithms |
| Abstract: | Conventional memory machines often suffer from magnetic interference between high-coercive-force (HCF) and low-coercive-force (LCF) permanent magnets, which unintentionally alters the magnetization state and limits overload capability. To address this challenge, this paper proposes a novel axial parallel memory machine (DCB-AXMM) featuring a DC-bias-controlled variable-flux capability. Instead of a conventional structure, the proposed machine employs an axially segmented topology to spatially isolate the excitation sources, effectively shielding the LCF PMs from HCF PM interference and armature reaction. Furthermore, integrated windings are utilized to perform both armature excitation and pulse magnetization, thereby enhancing the overall space utilization. The flux-regulating mechanism is theoretically elucidated using a piecewise linear hysteresis model. To maximize electromagnetic performance, a two-step optimization framework based on a genetic algorithm (GA) is implemented. Comprehensive non-linear finite element analysis (FEA) is conducted to validate the proposed design. Quantitative results demonstrate that the DCB-AXMM achieves a wide flux regulation range, characterized by a 21.8% average torque reduction from 2.2 Nm at full magnetization to 1.72 Nm at zero magnetization, while maintaining a robust 1.5-times overload capability. These measurable outcomes confirm the topology's effectiveness and reliability for high-performance variable-flux applications. [ABSTRACT FROM AUTHOR] |
| Database: | Energy & Power Source |
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| Abstract: | Conventional memory machines often suffer from magnetic interference between high-coercive-force (HCF) and low-coercive-force (LCF) permanent magnets, which unintentionally alters the magnetization state and limits overload capability. To address this challenge, this paper proposes a novel axial parallel memory machine (DCB-AXMM) featuring a DC-bias-controlled variable-flux capability. Instead of a conventional structure, the proposed machine employs an axially segmented topology to spatially isolate the excitation sources, effectively shielding the LCF PMs from HCF PM interference and armature reaction. Furthermore, integrated windings are utilized to perform both armature excitation and pulse magnetization, thereby enhancing the overall space utilization. The flux-regulating mechanism is theoretically elucidated using a piecewise linear hysteresis model. To maximize electromagnetic performance, a two-step optimization framework based on a genetic algorithm (GA) is implemented. Comprehensive non-linear finite element analysis (FEA) is conducted to validate the proposed design. Quantitative results demonstrate that the DCB-AXMM achieves a wide flux regulation range, characterized by a 21.8% average torque reduction from 2.2 Nm at full magnetization to 1.72 Nm at zero magnetization, while maintaining a robust 1.5-times overload capability. These measurable outcomes confirm the topology's effectiveness and reliability for high-performance variable-flux applications. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 19961073 |
| DOI: | 10.3390/en19102368 |
