Three Three-Axis IEPE Accelerometers on the Inner Liner of a Tire for Finding the Tire-Road Friction Potential Indicators

Abstract

Direct tire-road contact friction estimation is essential for future autonomous cars and active safety systems. Friction estimation methods have been proposed earlier for driving conditions in the presence of a slip angle or slip ratio. However, the estimation of the friction from a freely-rolling tire is still an unsolved topic. Knowing the existing friction potential would be beneficial since vehicle control systems could be adjusted before any remarkable tire force has been produced. Since accelerometers are well-known and robust, and thus a promising sensor type for intelligent tires, this study uses three three-axis IEPE accelerometers on the inner liner of a tire to detect friction potential indicators on two equally smooth surfaces with different friction levels. The equal roughness was chosen for both surfaces in order to study the friction phenomena by neglecting the effect of surface texture on vibrations. The acceleration data before the contact is used to differentiate the two friction levels between the tire and the road. In addition, the contact lengths from the three accelerometers are used to validate the acceleration data. A method to differentiate the friction levels on the basis of the acceleration signal is also introduced.

Identification of Road-Surface Type Using Deep Neural Networks for Friction Coefficient Estimation

“…The main advantage of such a system is that a road surface can be measured in the front of the moving vehicle before the front wheel contact with an obstacle. Niskanen and Tuononen [13] proposed the friction identification by estimating a three-axis accelerometer mounted inside the tyre. While such a method can be applied to detect friction potential indicators, different levels of pavement roughness still cause undesirable vibration and a negative influence on results.…”

A Road Condition Classification Algorithm for a Tire Acceleration Sensor using an Artificial Neural Network

“…However, that study used simulation data rather than data obtained in a real vehicle environment, so further studies are required for validation. Niskanen et al conducted a study to distinguish between two road surfaces with different friction conditions by attaching an acceleration sensor to the inside of a tire [18]. Their road condition classification method can be used to measure acceleration within the leading edge section of the tire, i.e., the section before the sensor contacts the ground, in the frequency domain.…”

A Multisensing Setup for the Intelligent Tire Monitoring

“…In the last twenty years, research has moved towards a different approach [1,2,3,4,5,6,7,8,9,10,11,12], which is based on using newly conceived sensors [9,10] to pursue the measurement of some key variables involving the tire-road contact interface [13,14,15,16], such as pressure, temperature, contact-patch dimensions, or even better wheel load [17], acceleration, friction factor [18,19,20] or deformation [21,22]. These new hardware and related algorithms are capable of measuring new quantities and extract additional information with potential use for the enhancement of the performance of the vehicle control systems, also putting the basis for breakthrough in new control devices.…”

“…Among the solutions that obtained a good visibility in the context of intelligent tires, two macro-categories are worth mentioning, the former related to a direct acceleration measurement [6,8,13], the latter related to strain measurements [21,25,26,27], both of inner tire points. Works of Audisio [30], Morinaga [31] and Hannah [14] are more focused on a widespread industrial application of smart tire and employ commercial sensors, while others [8,13,15,25,32] use prototypal devices to study the nature of the phenomena involving the tire rolling.…”

“…Works of Audisio [30], Morinaga [31] and Hannah [14] are more focused on a widespread industrial application of smart tire and employ commercial sensors, while others [8,13,15,25,32] use prototypal devices to study the nature of the phenomena involving the tire rolling.…”