TY - JOUR
T1 - Power optimization of the aircraft electrothermal de-icing heaters
AU - Wang, Tianxin
AU - Zhang, Wenqiang
AU - Chen, Jun
AU - Li, Si
AU - Yu, Lei
AU - Zhu, Dongyu
AU - Mao, Xuerui
N1 - Publisher Copyright:
© 2025 Elsevier Ltd
PY - 2025/12/1
Y1 - 2025/12/1
N2 - Icing accumulated at the leading edge of a wing significantly impacts the aerodynamic performance of aircraft and incurs serious safety hazards. This work advances the well-adopted electrothermal de-icing strategy, aiming to minimize the time for ice to melt and shed from the airfoil by optimizing the power distribution. An optimization scheme combining the genetic algorithm and the apparent heat capacity method to simulate the phase change from ice to water is developed and validated. A Radial Basis Function surrogate model is established to further reduce the computational costs. The protection area is divided into seven parts with constraints on the total power of all heaters and power limits for each heater, and the total de-icing time is divided into 2-, 4-, and 6-segment to take into account spatial and temporal variations of the heater power. The optimization results reveal that the power allocation for heaters presents a targeted adjustment trend corresponding to the ice thickness distribution, where regions with thicker ice cover are allocated higher power input to achieve efficient de-icing. With more time segments, the power tends to concentrate in ice-covered areas, with heaters in ice-free areas turned off, thus reducing the de-icing time and overall energy consumption. Specifically, the introduction of time variation leads to a 13% reduction in de-icing time and a 17% decrease in energy consumption. These results demonstrate the advantage of applying a complex control law that allows both spatial and temporal adjustments of the power distribution. Overall, this study provides numerical algorithms and strategies to improve the performance of electrothermal de-icing systems, offering clear benefits in reducing de-icing time and energy consumption.
AB - Icing accumulated at the leading edge of a wing significantly impacts the aerodynamic performance of aircraft and incurs serious safety hazards. This work advances the well-adopted electrothermal de-icing strategy, aiming to minimize the time for ice to melt and shed from the airfoil by optimizing the power distribution. An optimization scheme combining the genetic algorithm and the apparent heat capacity method to simulate the phase change from ice to water is developed and validated. A Radial Basis Function surrogate model is established to further reduce the computational costs. The protection area is divided into seven parts with constraints on the total power of all heaters and power limits for each heater, and the total de-icing time is divided into 2-, 4-, and 6-segment to take into account spatial and temporal variations of the heater power. The optimization results reveal that the power allocation for heaters presents a targeted adjustment trend corresponding to the ice thickness distribution, where regions with thicker ice cover are allocated higher power input to achieve efficient de-icing. With more time segments, the power tends to concentrate in ice-covered areas, with heaters in ice-free areas turned off, thus reducing the de-icing time and overall energy consumption. Specifically, the introduction of time variation leads to a 13% reduction in de-icing time and a 17% decrease in energy consumption. These results demonstrate the advantage of applying a complex control law that allows both spatial and temporal adjustments of the power distribution. Overall, this study provides numerical algorithms and strategies to improve the performance of electrothermal de-icing systems, offering clear benefits in reducing de-icing time and energy consumption.
KW - Apparent heat capacity method
KW - Electrothermal de-icing systems
KW - Radial Basis Function surrogate model
UR - http://www.scopus.com/pages/publications/105015503488
U2 - 10.1016/j.applthermaleng.2025.128236
DO - 10.1016/j.applthermaleng.2025.128236
M3 - Article
AN - SCOPUS:105015503488
SN - 1359-4311
VL - 280
JO - Applied Thermal Engineering
JF - Applied Thermal Engineering
M1 - 128236
ER -