From a traffic safety point of view, there is an urgent need for intelligent tires which can optimize braking control by estimating the slip ratio and friction coefficient between road surface and tire. In previous studies, we have proposed an application of strain data for estimating a friction coefficient. However, it only investigated the condition when the vertical or frictional loads changed but the other load remained constant. Since both of the frictional and vertical loads alter the measured strain data, an independent applied load estimation method is needed. This study develops a concurrent method for estimating the frictional and vertical loads applied to the tires from the measured strain data when both loads change. The method decomposes the measured circumferential strain to the frictional and vertical strain components using their symmetrical and anti-symmetrical characteristics. FEM analysis is used for simulating tire deformation under various wheel loads and braking torques and the relationship between the strain distribution at the sensing point and the applied loads are calculated. When the estimated and true applied loads were compared, it was confirmed that the vertical and frictional loads can be estimated independently from the circumferential strain with sufficient accuracy. Using this method, one can represent the slip slope curve during driving, which enables the optimization of vehicle control and implementation of a road condition warning system. 1497in capacitance (10)(11)(12) . The sensor uses a very soft material so that it does not interfere with tire deformation and avoids debonding (11,12) . Another sensor proposed is a self-sensing method that uses the tire structure itself as the sensor (13) . This has the advantage that an attached sensor is not needed and debonding problems are eliminated. An optical method was developed for the concurrent monitoring of in-plane strain and out-of-plane displacement (rolling radius) (14,15) . The optical method enables noncontact measurement of strain distribution. The in-plane strain and out-of-plane displacement are calculated using image processing with an image of the interior surface of a tire that is taken with a single CCD camera fixed on the wheel rim. We have also developed a battery-less wireless communication system (10,16,17) . However, a practical model of strain used for improved tire safety has not yet been presented and is urgently needed.Our previous study (18) investigated the application of strain data for an optimized braking control and road condition warning system. The relationships between strain sensor outputs and tire mechanical parameters, including braking torque, effective radius and contact patch length, are calculated using finite element analysis and an estimating method for the slip ratio and frictional coefficient between road and tire surface were proposed. Here the friction coefficient µ is a key parameter indicating the braking/accelerating efficiency and defined by the normal force (wheel load), F N , div...
Intelligent tires, also known as smart tires, are equipped with sensors to monitor the strain of the interior surface and the rolling radius of tire, and are expected to improve the reliability of tires and tire control systems such as anti-lock braking systems (ABS). However, the high stiffness of an attached sensor like a strain gauge causes sensors to debond from the tire rubber. In the present study, a novel optical method is used for the concurrent monitoring of in-plane strain and out-of-plane displacement (rolling radius) utilizing the non-planar surface of the monitoring object. The optical method enables noncontact measurement of strain distribution. The in-plane strain and out-of-plane displacement are calculated by using image processing with an image of the interior surface of a tire that is taken with a single CCD camera fixed on the wheel rim. This new monitoring system is applied to an aluminum beam and a commercially available radial tire. As a result, the monitoring system provides concurrent measurement of in-plane strain, out-of-plane displacement and tire pressure, and is shown to be an effective monitoring system for intelligent tires.
The estimation and management of motor temperature are important for the continuous movements of robots. In this study, we propose an online learning method of thermal model parameters of motors for an accurate estimation of motor core temperature. Also, we propose a management method of motor core temperature using the updated model and anomaly detection method of motors. Finally, we apply this method to the muscles of the musculoskeletal humanoid and verify the ability of continuous movements.
From a traffic safety point of view, there is an urgent need for intelligent tires which can optimize braking control by estimating the slip ratio and friction coefficient between a road surface and an automobile tire. The present study develops concurrent monitoring of frictional and vertical loads applied to the tires from the inner tire strain data for estimating the road/tire friction coefficient, which enables optimization of vehicle control and implementation of a road condition warning system. The tire strain is obtained using a three-dimensional digital image correlation method with a single wireless CCD camera attached to the wheel rim inside the tire. The procedures of the applied load estimation decompose the measured strain into the frictional and vertical strain components using their symmetrical and anti-symmetrical characteristics. Static tire rotation tests were carried out, and the applied loads were estimated from the inner tire surface strain distribution. Compared with the actual applied loads measured from strain gages attached to the experimental apparatus, it was confirmed that the vertical and frictional loads can be estimated independently with adequate accuracy.
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