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The purpose of this paper is to find the variations of brake lining's frictional performance with braking conditions, and their influence on the braking safety and reliability of automobiles.

As the semimetal brake lining is widely used currently in automobiles, it was selected as the experimental material. By simulating the braking conditions and environment of automobiles, some tribological experiments of the brake lining were investigated on the X‐DM friction tester, when it is paired with the friction disc made of gray cast iron. The influence of braking pressure, sliding velocity and surface temperature on the friction coefficient and its stability coefficient were studied in depth through experiments.

The friction coefficient decreases gradually with the increasing of braking pressure and sliding velocity when the surface temperature is naturally rising. It rises first then falls with the surface temperature rising and the maximal value appears at nearly 200°C. The stability of friction coefficient decreases obviously when the sliding velocity exceeds 30 m/s, the braking pressure exceeds 1.8 MPa and the surface temperature is over 200°C. Based on the experimental results, the authors consider that it is not reliable to execute an emergency braking only by rising the braking pressure when the automobile is driving with a high velocity. In order to reduce the bad influence of high temperature on frictional performance, some effective actions should be taken for cooling the friction disc. What is more, special attention should be paid to the decreasing of frictional stability during the braking with high velocity, pressure and temperature.

This paper studies the influence of braking conditions on friction coefficient and its stability of the semimetal brake lining for automobiles. It is believed that this research may have some actual guidance for enhancing the braking safety and reliability of automobiles.

In order to improving the braking reliability and assuring the driving safety of automobiles, this paper aims at the wear performance and its online monitoring of its brake lining.

The wear performance of the semimetal brake lining for automobiles was investigated on a self-made braking tester for disc brakes. Based on the experimental data, an intelligent forecasting model for the wear rate was established by the artificial neural network (ANN) technology. And by taking it as a core, an online braking wear monitoring system for automobiles was designed.

It is shown that the wear rate rises obviously with the increasing of both initial braking velocity and braking pressure. By the contrast, the initial braking velocity affects the wear rate more seriously. The ANN model trained by the experimental data shows favorable capability for predicting of the wear rate. The big forecasting errors at high velocity and heavy load should be attributed to the jumping of the wear rate at this period. Based on the existed sensors and electronic control unit system of automobiles, the online braking wear monitoring system can be established easily by the ANN technology.

A self-made braking tester for disc brakes was used to test the wear performance, which can simulate better the actual disc braking conditions than the standard pin-on-disc friction tester. An online braking wear monitoring system was designed to help improving the braking reliability and safety of automobiles.

This paper aims to thrash out friction and wear properties of automobile brake lining reinforced by lignin fiber and glass fiber in braking process.

ABAQUS finite element software was used to analyze thermo-mechanical coupled field of friction materials. XD-MSM constant speed friction testing machine was used to test friction and wear properties of friction material. Worn surface morphology and mechanism of friction materials were observed by using scanning electron microscope.

The results show that when the temperature was below 350°C, worn mechanism of MFBL was mainly fatigue wear and abrasive wear, and worn mechanism of GFBL was mainly fatigue wear because MFBL contained lignin fiber. Therefore, it exhibits better mechanical properties and friction and wear properties than those of GFBL.

Lignin fiber can improve mechanical properties and friction and wear properties of the automobile brake lining.

To avoid braking accidents caused by excessive wear of brake pad, this study aims to achieve online prediction of brake pad wear life (BPWL).

A simulated braking test bench for automobile disc brake was used. The correlation and mechanism between the three braking condition parameters of initial braking speed, braking pressure and initial braking temperature and the tribological performance were analyzed. The different artificial neural network (ANN) models of wear loss were discussed. Genetic algorithm was used to optimize the ANN model. The structure scheme of the online prediction system of BPWL was discussed and completed.

The results showed that the braking conditions were positively correlated with the wear loss, but negatively correlated with the friction coefficient. The prediction accuracy of back propagation (BP) ANN model was higher. The model was optimized by genetic algorithm, and the average deviation of prediction results was 4.67%. By constructing the online monitoring system of automobile braking conditions, the online prediction of BPWL based on the ANN model could be realized.

The research results not only have important theoretical significance for the study of BPWL but also have practical value for guiding the maintenance and replacement of automobile brake pads and avoiding the occurrence of braking accidents.

The friction between brake pair causes an intense temperature rise on interface during braking, which affects the braking performance seriously. Therefore, building an accurate testing method for frictional temperature rise (FTR) is a prerequisite.

Facing braking conditions of automobiles, an experimental system for testing of FTR based on preset thermometry method (PTM) was established. The FTR was collected by the PTM and the variation laws as well as the cause of errors were analyzed by experiments. The deviations between tested and real temperature were corrected based on tribology and heat theories. Finally, an online prediction method for FTR was pointed out.

After correction, the temperature curve accords well with the laws of tribology and thermal theories. The corrected FTR at braking end point is approximately equal to the authentic temperature test by hand thermometer.

This study eliminated the hysteresis phenomenon of temperature rise sequence and lays a foundation for online accurate monitoring and warning of brake friction temperature rise. It has important theoretical and practical value for expanding the monitoring and improvement of brake performance.

The purpose of this work is to investigate the effect of oxide-coated steel in comparison with mild steel fibers on the tribological and corrosion performances of friction composites.

In this study, the friction composites were developed in the form of standard brake pads by using oxide-coated steel and compared with mild steel fibers-based one without varying the other ingredients. The brake pads were developed as per the industrial procedure. The physical, mechanical, thermal properties of the developed brake pads were analyzed as per the industrial standards. The tribological properties were analyzed using the Chase test. The worn surface analysis was done using scanning electron microscope. Corrosion behavior was also analyzed in both salt and normal water conditions.

The experimental results indicate that the oxide-coated steel-based friction composites brake pads possess good physical, chemical, thermal, corrosion resistance and mechanical properties with stable fade and recovery characteristics because of its oxide coating and flake morphology.

This paper explains the influence of oxide-coated steel in friction composites for enhancing the tribological performance and corrosion resistance by its oxide coating and flake morphology which could potentially replace mild steel fibers-based problems in friction composites.

In this study, artificial neural networks (ANNs) are constructed and validated by using the bearing data generated numerically from a thermohydrodynamic (THD) lubrication model. In many tribological simulations, a surrogate model (meta-model) for obtaining a fast solution with sufficient accuracy is highly desired.

The THD model is represented by two coupled partial differential equations, a simplified generalized Reynolds equation, considering the viscosity variation across the film thickness direction and a transient energy equation for the 3-D film temperature distribution. The ANNs tested are having a single- or dual-hidden-layer with two inputs and one output. The root-mean-square error and maximum/minimum absolute errors of validation points, when comparing with the THD solutions, were used to evaluate the prediction accuracy of the ANNs.

It is demonstrated that a properly constructed ANN surrogate model can predict the THD lubrication performance almost instantly with accuracy adequately retained.

This study extends the use of ANNs to the applications other than the analyses dealing with experimental data. A similar procedure can be used to build a surrogate model for computationally intensive tribological models to have fast results. One of such applications is conducting extensive optimum design of tribological components or systems.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2020-0109/