Abstract
Polymer-based self-sensing composite intelligent materials have become an innovative application in the field of road monitoring. Aiming at the shortcomings of existing models that mostly focus on single-filler systems and rarely consider the dual evolution of tunneling gap and conductive network, this study establishes a strain-resistance response model for micro–nano-structured polymer composite smart materials by analyzing four conductive models and taking the tunneling effect as the core conduction mechanism. Taking CNTs-CB/epoxy composites as the object, it constructs a 3D resistive network model, optimizes the Simmons tunneling current model, and deduces the functional relationships of effective conductive pathways and tunnel gap with tensile strain, thus establishing the strain-resistance change rate model. Validated by experimental data and data from the literature on diverse composite systems, the model shows high fitting accuracy (R2 > 0.98). It reveals that the resistance change rate is linear with small strain and grows exponentially with increased strain, failing when the conductive network is damaged. The model is verified for monotonic tensile loading, with a concise analytical form and clear physical meaning of parameters, providing theoretical support for design and optimization of composite strain sensors for road monitoring.