The evolution characteristics of electrical resistance response of filled conductive polymer composites under cyclic loading by modelling strain sensing behavior

Filled conductive polymer composites (CPCs) under cyclic loading often exhibit resistance attenuation, shoulder peaks, baseline drift, and hysteresis, which are beyond the explanatory capability of classical piezoresistive theory, particularly regarding nonmonotonic responses and cyclic evolution. In this work, a strain sensing model is established for cyclic loading by considering the reversible and irreversible deformation behaviors, conductive network rearrangement, and interfacial effects. Gent type hyperelasticity strain energy function combined with a quasi-linear viscoelastic formulation is employed to describe reversible mechanical response, and residual strain is introduced to represent irreversible deformation accumulated. The effective deformation and coupling effect of the conductive network are introduced to analyze the influence on the resistance response, with experimental verification performed. Theoretical analysis indicates that conductive pathway coupling governs the shoulder peak features, including an initial decrease then increase during loading and a sudden rise near unloading completion. Stress relaxation and interfacial degradation reduce resistance amplitude cycle-by-cycle, residual strain primarily causes baseline drift, and interfacial viscoelasticity induces hysteresis. Experimental results demonstrate that the proposed model reasonably reproduces and accurately predicts the non-monotony change and cyclic evolution of resistance. External validation of the resistance response further shows good applicability and effectiveness across different CPCs and strain amplitudes. Additionally, an optimization framework shows that interface modification and structure design improve long-term sensing stability and suppress shoulder peaks; a CUF-based intelligent beam model and equivalent constitutive database further validate structural scale applicability.