Health monitoring method for intelligent non-pneumatic tire based on fusion autoregressive coefficient

Abstract

To address the issues of tire pressure and blowouts in pneumatic tires, the development of non-pneumatic tires (NPTs) has become a consensus among the world’s major tire manufacturers and research institutions. Implementing health monitoring for NPTs is significant for further ensuring vehicle safety. At present, there are only methods for monitoring tire pressure on inflatable tires, but there have been no reports on methods for monitoring the health of non pneumatic tires. This paper first proposes an intelligent health monitoring method for NPTs based on fusion autoregressive coefficient. Initially, a three-dimensional nonlinear finite element model of the NPT was established for simulating acceleration signals under various damage states. Subsequently, an intelligent health monitoring framework and process based on time-series models were constructed, while introducing a damage-sensitive index derived from the first three autoregressive coefficients of the auto-regressive and moving average (ARMA) model. Finally, the health status of NPTs was identified based on the simulated signals and the proposed health monitoring framework. The results indicate that the health monitoring method and damage-sensitive index proposed in this paper can effectively identify the health status of NPTs. The research findings provide a theoretical foundation and methodological support for the health monitoring and life prediction of NPTs.