Enhancing temperature uniformity in multi-coil CFRP induction heating via WOA-optimized fuzzy PID

Abstract

Induction heating is a promising technology for the rapid and energy-efficient curing of carbon fiber-reinforced polymer (CFRP) composites. However, in multi-coil systems, electromagnetic coupling and nonlinear thermal dynamics readily produce non-uniform temperature fields that compromise curing quality. To address this issue, an integrated framework combining mesoscopic mechanism analysis, coupled dynamic modeling, and curing-oriented intelligent control was developed. A mesoscopic finite element model was first established to clarify the origin of non-uniform heat generation in CFRP under multi-coil excitation. Based on this physical insight, a control-oriented dual-coil dynamic model was derived through system identification, and a fuzzy PID controller was then globally tuned offline using the whale optimization algorithm (WOA) for temperature regulation. Simulation results show that the optimized controller reduces overshoot by approximately 84% in the primary zone, shortens the settling time to 100 s, and improves inter-zone synchronization and disturbance rejection under multiple disturbance conditions. These results demonstrate that linking mechanism-level understanding with control-oriented optimization provides an effective route to improving temperature uniformity and process reliability in multi-coil CFRP induction curing.