Passive wireless strain monitoring of actual tire using capacitance–resistance change and multiple spectral features

To improve reliability of automobile tires and anti-lock braking system (ABS), intelligent tires that measure strain of tires are increasingly demanded. The high stiffness of an embedded sensor like a strain gage, however, causes debonding of a sensor from tire rubber. In a previous study, the authors proposed a wireless strain monitoring method that adopts a rectangular tire specimen as a sensor with a tuning circuit. Compared to the tire specimen, an actual tire has a large hysteresis between the measured strain of the inner tire surface and the capacitance in a tire belt. The large hysteresis in the actual tire makes it difficult to measure a tire strain precisely. In the present study, to measure the strain precisely, multiple power spectrum features of the sensor output are used to estimate the strain with a statistical method. As the spectral features, a peak power spectrum and a sharpness of the resonance in addition to a tuning frequency are used for the estimating. As a result the experiments demonstrate that the method is effective for the passive wireless strain monitoring of actual radial tires.