Mustafa Ali Arat

High magnetic field sensitivity in Pb(Zr,Ti)O3–Pb(Mg1/3Nb2/3)O3 single crystal/Terfenol-D/Metglas magnetoelectric laminate composites

We report the magnetic field sensitivity results on five layer structure given as Metglas/Terfenol-D/PMN–PZT/Terfenol-D/Metglas, where PMN and PZT correspond to Pb(Mg1/3Nb2/3)O3 and Pb(Zr,Ti)O3, respectively. The piezoelectric constant (d33) of poled PMN–PZT was found to be 1600 pC/N with dielectric constant of 5380 at 1 kHz. The sensitivity measurements were conducted after attaching individual layers in the laminate clearly delineating the effect occurring in the response. The magnetoelectric response for this five layer structure at 1 kHz was found to be 5 V/cm Oe at dc bias field of 1000 Oe under an ac drive of 1 Oe. At 1 kHz frequency, the sensor was able to deterministically measure step changes of 500 nT while at 10 Hz we can clearly identify the sensitivity of 1 μT. These results are very promising for the cheap room-temperature magnetic field sensing technology.

Enhancement of Collision Mitigation Braking System Performance Through Real-Time Estimation of Tire-road Friction Coefficient by Means of Smart Tires

In the case of modern day vehicle control systems employing a feedback control structure, a real-time estimate of the tire-road contact parameters is invaluable for enhancing the performance of the chassis control systems such as anti-lock braking systems (ABS) and electronic stability control (ESC) systems. However, at present, the commercially available tire monitoring systems are not equipped to sense and transmit high speed dynamic variables used for real-time active safety control systems. Consequently, under the circumstances of sudden changes to the road conditions, the drivers ability to maintain control of the vehicle maybe 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 a smart/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 tire-road friction model-based parameter estimation approach is proposed. Hence an integrated approach using the smart/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 collision mitigation braking systems. Language: en

An intelligent tyre based adaptive vehicle stability controller

Active safety systems have become an essential part of today’s vehicles. Although they have advanced in many aspects, there are still many areas where that they can be improved. Being able to obtain information about tyre-road conditions (e.g., slip ratio, tyre-slip angle, tyre forces, tyre-road friction) would be especially significant due to the key role tyres play in providing directional stability and control. Current systems are capable of obtaining such information by means of indirect methods (i.e., vehicle kinematic relations); however, they tend to fail in severe manoeuvres mainly because of the highly nonlinear characteristics of tyres. As a result, other methods are sought to directly obtain information about tyre–road interaction. This paper examines such a method where a tyre-attached sensor unit (intelligent tyre system) provides tyre slip information and the potential performance improvements offered by integrating this system with an adaptive vehicle stability controller.

Adaptive Vehicle Stability Control With Optimal Tire Force Allocation

Vehicle stability control systems have been receiving increasing attention, especially over the past decade, owing to the advances in on-board electronics that enables successful implementation of complex algorithms. Another major reason for their increasing popularity lies in their effectiveness. Considering the studies that expose supporting results for reducing crash risk or fatality, organizations such as E.U. and NHTSA are taking steps to mandate the use of such safety systems on vehicles. The current technology has advanced in many aspects, and undoubtedly has improved vehicle stability as mentioned above; however there are still many areas of potential improvements. Especially being able to utilize information about tire-vehicle states (tire forces, tire-slip angle, and tire-road friction) would be significant due to the key role tires play in providing directional stability and control. This paper presents an adaptive vehicle stability controller that makes use of tire force and slip-angle information from an online tire monitoring system. Solving the optimality problem for the tire force allocation ensures that the control system does not push the tires into the saturation region where neither the driver nor the controller commands are implemented properly. The proposed control algorithm is implemented using MATLAB/CarSim® software packages. The performance of the system is evaluated under an evasive double lane change maneuver on high and low friction surfaces. The results indicate that the system can successfully stabilize the vehicle as well as adapting to the changes in surface conditions.© 2012 ASME