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Dual-resonance converse magnetoelectric and voltage step-up effects in laminated composite of long-type 0.71Pb(Mg1/3Nb2/3)O3-0.29PbTiO3 piezoelectric single-crystal transformer and Tb0.3Dy0.7Fe1.92 magnetostrictive alloy bars

The contact between the tire and the road is the key enabler of vehicle acceleration, deceleration and steering. However, due to changes to the road conditions, the driver's ability to maintain a stable vehicle may be at risk. In many cases, this requires intervention from the chassis control systems onboard the vehicle. Although these systems perform well in a variety of situations, their performance can be improved if a real-time estimate of the tire-road friction coefficient is available. Existing tire-road friction estimation approaches often require certain levels of vehicle longitudinal and/or lateral motion to satisfy the persistence of excitation condition for reliable estimations. Such excitations may undesirably interfere with vehicle motion controls. This paper presents a novel development and implementation of a real-time tire-road contact parameter estimation methodology using acceleration signals from an intelligent tire. The proposed method characterizes the terrain using the measured frequency response of the tire vibrations and provides the capability to estimate the tire road friction coefficient under extremely lower levels of force utilization. Under higher levels of force excitation (high slip conditions), the increased vibration levels due to the stick/slip phenomenon linked to the tread block vibration modes make the proposed tire vibrations based method unsuitable. Therefore for high slip conditions, a brush model-based nonlinear least squares (NLLS) parameter estimation approach is proposed. Hence an integrated approach using the intelligent tire based friction estimator and the model based estimator gives us the capability to reliably estimate friction for a wider range of excitations. Considering the strong interdependence between the operating road surface condition and the instantaneous forces and moments generated; this real time estimate of the tire-road friction coefficient is expected to play a pivotal role in improving the performance of a number of vehicle control systems. In particular, this paper focuses on the possibility of enhancing the performance of the ABS control systems. In order to achieve the aforementioned objectives, the design and implementation of a fuzzy/sliding mode/proportional integral (fuzzy-SMC-PI (FSP)) control methodology is proposed. The results show significant improvements in the stopping distance of a vehicle equipped with an intelligent tire based FSP controller as compared to a vehicle equipped with a standard ABS.

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