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In transmission line anti-icing applications, self-heating ferromagnetic sleeves can achieve passive heating through hysteresis and eddy current losses induced by alternating current magnetic fields. However, full-length installation significantly increases the conductor mechanical load, requiring a coordinated design between antiicing thermal performance and structural safety. In this study, an LGJ-400/35 conductor is selected as the research object, and a coupled thermal-fluid numerical model of the conductor-ferromagnetic sleeve system is established. The effectiveness of the ferromagnetic sleeve is first verified by comparing the temperature distributions of sleeved and bare conductors under identical conditions, demonstrating that the sleeve can significantly increase the conductor surface temperature and form a local effective anti-icing length. Under the constraint that the total sleeve mass per unit length does not exceed the equivalent design icing load, the minimum installation spacing ensuring mechanical safety in the light icing zone, moderate icing zone, and heavy icing zone is determined to be 0.43 m, 0.26 m, and 0.18 m, respectively. Furthermore, under a fixed operating current of 500 A, using the conductor midpoint temperature criterion (T mid > 0.5 ℃), the anti-icing performance boundary is evaluated for different spacing configurations. The results show that the maximum tolerable wind speeds are 4 m/s, 6 m/s, and 8 m/s for the three icing zones, respectively, indicating that reducing the spacing enhances anti-icing capability through thermal superposition. To address the limitation of fixed sleeve power under higher wind speed conditions, the required massspecific heating power of the sleeve is further inversely determined for different icing zones under their design wind speeds, yielding values within the range of 42-53 W/kg.The results indicate that the anti-icing performance of ferromagnetic sleeves is jointly governed by mechanical load constraints, installation spacing, and convective heat transfer conditions. By integrating load constraint, performance boundary evaluation, and power requirement determination,
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Su et al. (2026) studied this question.
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