Effect of Fiber Shape on the Tribological, Mechanical, and Morphological Behaviors of Sisal Fiber-Reinforced Resin-Based Friction Materials: Helical, Undulated, and Straight Shapes

In this paper, we aim to evaluate the tribological, mechanical, and morphological performance of resin-based friction composites reinforced by sisal fibers with different shapes, namely helical, undulated, and straight shapes. The experimental results show that the shape of the sisal fibers exerts a significant effect on the impact property of the composite materials but no obvious influence on the density and hardness. The friction composite containing the helical-shaped sisal fibers exhibits the best overall tribological behaviors, with a relatively low fade (9.26%), high recovery (98.65%), and good wear resistance (2.061 × 10−7 cm3∙N−1∙m−1) compared with the other two composites containing undulated-shaped fibers and straight-shaped fibers. The impact fracture surfaces and worn surfaces of the composite materials were inspected by scanning electron microscopy, and we demonstrate that adding helical-shaped sisal fibers into the polymer composites provides an enhanced fiber–matrix interface adhesion condition and reduces the extent of fiber debonding and pullout, effectively facilitating the presence of more secondary plateaus on the friction surface, which are responsible for the enhanced tribological and mechanical properties. The outcome of this study reveals that sisal fibers with a helical shape could be a promising candidate as a reinforcement material for resin-based brake friction composite applications.

Research on a Rice Counting Algorithm Based on an Improved MCNN and a Density Map

The thousand grain weight is an index of size, fullness and quality in crop seed detection and is an important basis for field yield prediction. To detect the thousand grain weight of rice requires the accurate counting of rice. We collected a total of 5670 images of three different types of rice seeds with different qualities to construct a model. Considering the different shapes of different types of rice, this study used an adaptive Gaussian kernel to convolve with the rice coordinate function to obtain a more accurate density map, which was used as an important basis for determining the results of subsequent experiments. A Multi-Column Convolutional Neural Network was used to extract the features of different sizes of rice, and the features were fused by the fusion network to learn the mapping relationship from the original map features to the density map features. An advanced prior step was added to the original algorithm to estimate the density level of the image, which weakened the effect of the rice adhesion condition on the counting results. Extensive comparison experiments show that the proposed method is more accurate than the original MCNN algorithm.

Chassis Coordinated Control for Full X-by-Wire Vehicles-A Review

An X-by-wire chassis can improve the kinematic characteristics of human-vehicle closed-loop system and thus active safety especially under emergency scenarios via enabling chassis coordinated control. This paper aims to provide a complete and systematic survey on chassis coordinated control methods for full X-by-wire vehicles, with the primary goal of summarizing recent reserch advancements and stimulating innovative thoughts. Driving condition identification including driver's operation intention, critical vehicle states and road adhesion condition and integrated control of X-by-wire chassis subsystems constitute the main framework of a chassis coordinated control scheme. Under steering and braking maneuvers, different driving condition identification methods are described in this paper. These are the trigger conditions and the basis for the implementation of chassis coordinated control. For the vehicles equipped with steering-by-wire, braking-by-wire and/or wire-controlled-suspension systems, state-of-the-art chassis coordinated control methods are reviewed including the coordination of any two or three chassis subsystems. Finally, the development trends are discussed.

Experimental prototyping of the adhesion braking control system design concept for a mechatronic bogie

The dynamic parameters of a roller rig vary as the adhesion level changes. The change in dynamics parameters needs to be analysed to estimate the adhesion level. One of these parameters is noise emanating from wheel–rail interaction. Most previous wheel–rail noise analysis has been conducted to mitigate those noises. However, in this paper, the noise is analysed to estimate the adhesion condition at the wheel–rail contact interface in combination with the other methodologies applied for this purpose. The adhesion level changes with changes in operational and environmental factors. To accurately estimate the adhesion level, the influence of those factors is included in this study. The testing and verification of the methodology required an accurate test prototype of the roller rig. In general, such testing and verification involve complex experimental works required by the intricate nature of the adhesion process and the integration of the different subsystems (i.e. controller, traction, braking). To this end, a new reduced-scale roller rig is developed to study the adhesion between wheel and rail roller contact. The various stages involved in the development of such a complex mechatronics system are described in this paper. Furthermore, the proposed brake control system was validated using the test rig under various adhesion conditions. The results indicate that the proposed brake controller has achieved a shorter stopping distance as compared to the conventional brake controller, and the brake control algorithm was able to maintain the operational condition even at the abrupt changes in adhesion condition.

Importance of Interfacial Adhesion Condition on Characterization of Plant-Fiber-Reinforced Polymer Composites: A Review

Plant fibers have become a highly sought-after material in the recent days as a result of raising environmental awareness and the realization of harmful effects imposed by synthetic fibers. Natural plant fibers have been widely used as fillers in fabricating plant-fibers-reinforced polymer composites. However, owing to the completely opposite nature of the plant fibers and polymer matrix, treatment is often required to enhance the compatibility between these two materials. Interfacial adhesion mechanisms are among the most influential yet seldom discussed factors that affect the physical, mechanical, and thermal properties of the plant-fibers-reinforced polymer composites. Therefore, this review paper expounds the importance of interfacial adhesion condition on the properties of plant-fiber-reinforced polymer composites. The advantages and disadvantages of natural plant fibers are discussed. Four important interface mechanism, namely interdiffusion, electrostatic adhesion, chemical adhesion, and mechanical interlocking are highlighted. In addition, quantifying and analysis techniques of interfacial adhesion condition is demonstrated. Lastly, the importance of interfacial adhesion condition on the performances of the plant fiber polymer composites performances is discussed. It can be seen that the physical and thermal properties as well as flexural strength of the composites are highly dependent on the interfacial adhesion condition.

An improved degraded adhesion model for wheel–rail under braking conditions

Purpose The purpose of this paper is to develop an improved adhesion model to better reproduce the low adhesion condition of the anti-skid control for rail vehicles under braking condition. Design/methodology/approach In view of the low adhesion characteristics for rail vehicles under braking conditions, the Polach adhesion model was improved based on the sliding power and sliding energy. The wheel–rail low adhesion model suitable for braking condition was given. The analysis of braking anti-skid control under emergency braking condition was carried out through the co-simulation, and compared with the test data; the effectiveness and practicability of the improved low adhesion model were verified. Findings The results showed that the improved adhesion model is simple and efficient and the parameters involved are less, and it can be directly applied to the real-time simulation of anti-skid control in the process of train braking. Originality/value This paper can provide a theoretical reference for the reasons of change and improvement of adhesion between wheel and rail caused by the adjustment of braking force under anti-skid control, which can fulfill a need to the study of sliding energy on the contact surface, the removal effect of pollutants on the wheel–rail surface and the improvement and recovery of adhesion caused. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2020-0244/

A novel anti-slip control approach for railway vehicles with traction based on adhesion estimation with swarm intelligence

Anti-slip control systems are essential for railway vehicle systems with traction. In order to propose an effective anti-slip control system, adhesion information between wheel and rail can be useful. However, direct measurement or observation of adhesion condition for a railway vehicle in operation is quite demanding. Therefore, a proportional–integral controller, which operates simultaneously with a recently proposed swarm intelligence-based adhesion estimation algorithm, is proposed in this study. This approach provides determination of the adhesion optimum on the adhesion-slip curve so that a reference slip value for the controller can be determined according to the adhesion conditions between wheel and rail. To validate the methodology, a tram wheel test stand with an independently rotating wheel, which is a model of some low floor trams produced in Czechia, is considered. Results reveal that this new approach is more effective than a conventional controller without adhesion condition estimation.

Variable Control Setting to Enhance Rail Vehicle Braking Safety

Train braking technology needs to be advanced corresponding to the vehicle advancement to fully utilize the benefits of the potential capacity, efficiency and to ensure safety. The effectiveness of the braking changes as the friction condition at the wheel-rail interface and speed of rail vehicle change. The conventional brake control systems do not differentiate these changes in conditions and consider a constant slip reference. To overcome this issue, a new control algorithm for a wheel slide protection device incorporated in the electronically controlled pneumatic brake system has been proposed. Unlike conventional controllers, the proposed controller is responsive to the change of operational and environmental parameters between wheel and rail. It is designed based on multiple modes shifting during operations as the friction conditions change which allows to utilize the maximum adhesion available and to prevent the occurrence of sliding. The control algorithm is developed in a modular approach, where the first module identifies the adhesion condition at the wheel-rail interface. The result from the first module is further implemented in the second module to search for the optimum slip range for that adhesion condition and vehicle speed. For numerical simulation, a wagon model considering in-train forces is developed. The adhesion force is modeled by a proper definition of an adhesion-creep characteristics curve achieved from measured data. The comparison between the proposed control algorithm and the conventional algorithm suggests that the proposed control algorithm can optimally utilize available adhesion between wheel and rail to ensure shorter braking distance while maintaining vehicle stability.

Multi-Objective Optimization Study of Regenerative Braking Control Strategy for Range-Extended Electric Vehicle

Currently, the researches on the regenerative braking system (RBS) of the range-extended electric vehicle (R-EEV) are inadequate, especially on the comparison and analysis of the multi-objective optimization (MOO) problem. Actually, the results of the MOO problem should be mutually independent and balanced. With the aim of guaranteeing comprehensive regenerative braking performance (CRBP), a revised regenerative braking control strategy (RRBCS) is introduced, and a method of the MOO algorithm for RRBCS is proposed to balance the braking performance (BP), regenerative braking loss efficiency (RBLE), and battery capacity loss rate (BCLR). Firstly, the models of the main components related to the RBS of the R-EEV for the calculation of optimization objectives are built in MATLAB/Simulink and AVL/Cruise. The BP, RBLE, and BCLR are selected as the optimization objectives. The non-dominated sorting genetic algorithm (NSGA-II) is applied in RRBCS to solve the MOO problem, and a group of the non-inferior Pareto solution sets are obtained. The simulation results show a clear conflict that three optimization objectives cannot be optimal at the same time. Then, we evaluate the performance of the proposed method by taking the individual with the optimal CRBP as the final optimal solution. The comparation among BP, RBLE, BCLR, and CRBP before and after optimization are analyzed and discussed. The results illustrate that characteristic parameters of RRBCS is crucial to optimization objectives. After parameters optimization, regenerative braking torque works early to increase braking energy recovery on low tire-road adhesion condition, and to reduce the battery capacity loss rate at the expense of small braking energy recovery on the medium tire-road adhesion condition. In addition, the results of the sensitivity analysis show that after parameter optimization, RRBCS is proved to perform better road adaptability regarding the distribution of solutions. These results thoroughly validate the proposed approach for multi-objective optimization of RRBCS and have a strong directive to optimize the control strategy parameters of RBS.

Surface buckling delamination patterns of film on soft spherical substrates

The morphological transition of film buckling-delamination in an elastomeric bilayer spherical shell system was studied experimentally and numerically. It was changed by the film thickness, Young's modulus, and interfacial adhesion condition, etc.