Braking System Research Articles

Thermal Analysis of a Simplified Railway Brake Model with Numerical Simulation

The braking system is the most important safety device in all vehicles. When braking, the kinetic energy of the vehicle is converted into thermal energy. The use of friction brakes can cause problems in the long term, as the brake can heat up, reducing its coefficient of friction. Heating and cooling have a harmful effect on all frictional elements, causing material fatigue. As a result of the negative effects, the hot brake cannot reduce the velocity of the vehicle at the correct rate. In this paper, the propagation of frictional heat is analysed in a test specimen made of cast iron material using different numerical simulations. The computational results are validated with the results obtained during measurement. With proper validation, the brake discs are able to be modelled at different designs and materials without having to manufacture a test specimen for each case. In the study, it is important to point physical quantities to carry out the simulation.

Analysis of 3k Experiments Applied to Railway Braking: Influence of Contaminants and Train Speed

The presence of contaminants influences braking efficiency in the railway system because it alters the adhesion at the wheel–rail interface. It is essential to study this phenomenon, as contaminants reduce the friction between wheels and rails, which impacts braking and transport safety. In addition, these contaminants increase the risk of derailments. The objective of the research was to determine the impact of different contaminants and operating speeds on the critical braking system’s responses. Using the 3k full factorial experimental design methodology, with analysis of variance (ANOVA) and linear and quadratic regressions, visualized using surface graphs, the effects of three operating conditions were studied: clean rails, with sand and sawdust, and driving the train at three operating speeds. These conditions gave rise to variations in braking distances, maximum creep, wheel slip times, and maximum peaks of electric current when braking in each experiment. The tests were carried out on the straight section of a β-shaped track and a railway vehicle, designed at a scale of 1:20. The analysis reveals that the braking distance increases significantly with surface roughness (clean track < sawdust < sand). At 0.75 m/s, the sawdust track reduces braking distance by 21% compared with the clean track; at 1.00 m/s, the reduction is 19%; and at 1.30 m/s, it is 35%.

The effect of hardness on bending value in manufacturing brake pads from shell and palm fiber

Motorbikes are one of the primary needs for many people because they are more effectively used to carry out community activities than public transportation. Because motorbikes are used so frequently, the braking system is one of the parts that must be updated. Brake pads are motorbike equipment that function to slow and stop the vehicle comfortably. The research aims to determine the characteristics of brake linings and the optimal composition of brake linings that are good for use. Brake pads are a component of motorcycle vehicles that are useful for slowing down and stopping the speed of the vehicle comfortably. The purpose of this study is to find out how the characteristics of palm shells and fibers if used as material for making brake linings. The method used is direct experimentation with a qualitative approach. The results obtained are the characteristics of brake pads made from filler palm shell powder and palm fiber with polyurethane matrix have a hard texture, solid brown, if viewed from the surface of the brake lining is a little rough because the fiber is too long. The test results showed the best hardness value of 91 R and the best bending test with a value of 10.21 kgf/mm2

Methodology for determining the heat distribution in disc brakes of mine hoisting machines

Purpose. To study the course of heat phenomena in disc brakes using modern computing systems in order to determine and substantiate the operating parameters for the hoisting machine components. Methodology. The research uses software packages, with the help of which a computational-theoretical apparatus is developed for heat mode modeling processes. In particular, the mentioned function is used in the SolidWorks Simulation software with the ability to evaluate the errors of the calculation results. Findings. In the course of the research, the dependence of the hoisting machine disc brake performance on the operating parameters of its components was determined. The research has led to a better understanding of the heat transfer processes in disc braking devices, as well as the ability to study the friction response of various materials and determine optimal parameters that help improve the performance of braking systems. The effectiveness has been proven of the proposed method for analyzing the heat distribution processes of the mine hoisting machine drum components under the influence of operating and emergency braking modes. Originality. For the first time, a methodology for calculating the heating temperature distribution along the brake rim plane during a safety stop has been developed and substantiated. A method has also been developed for determining the temperature field arising under steady-state heating conditions, which occur after repeated operating braking and cooling of the device. In this case, when using the formula for determining the temperature on the brake rim surface, the sample length, the relative velocity between the friction components and the heat flow distribution coefficient are taken into account. The brake disc geometric model developed in the SolidWorks software package makes it possible to study the temperature change on the device rim in real time. Practical value. The proposed design improvement based on the research results of heating processes should improve vehicle safety. The cost of braking systems is expected to be reduced through the use of optimal materials and production technologies. The software methods for modeling and analyzing the temperature influence on brake discs of the Mine Hoisting Machine (MHM) have been improved. Based on the research results, recommendations have been developed for the optimum braking process of machines in various operating conditions.

Determination of Static Flow Characteristics of A Prototypical Differential Valve Using Computational Fluid Dynamics

Abstract The paper describes the numerical calculations of a conceptual air brake valve of a trailer equipped with a differential section, which is intended to shorten response time and braking distance. The static flow characteristics have been determined using computational fluid dynamics (CFD). Mixed (global and local) computational meshes were used in the paper to determine the static flow characteristics of the valve sections. The use of the local mesh was relevant for valve openings smaller than 0.5mm. Using CFD, it was possible to determine the static flow characteristics of the main, auxiliary feed and the differential sections, which were linear, degressive and progressive depending on the section. The analyzes, which have not yet been described in the literature, showed a significant difference in the MFR of the additional and main feed tracts, which reached 52.29%.The results are applicable to the configuration of the braking system. Further research will include performing dynamic simulations using dedicated software and building a test rig to validate the CFD calculation results.

Design of a tooth-shaped magnetorheological brake with multiple coils

This research presents an optimized design for a tooth-shaped magnetorheological brake (MRB) with multiple coils. The MRB configuration consists of a disk immersed in magnetorheological fluid (MRF), where four coils act as electromagnets when an electric current is applied. The energized coils induce the alignment of suspended particles in the MRF, forming a chain-like structure that increases the fluid's viscosity. This rapid, strong, and controllable phenomenon enables the MRB to find applications in haptic systems, tension control, and industrial braking systems. To analyze the electromagnetic behavior of the brake, Finite Element Method (FEM) simulations are conducted using ANSYS APDL, and the optimization process is performed utilizing ANSYS Workbench software. The software provides optimized geometries for the brake, resulting in significant improvements in desired performance aspects compared to prior designs, etc.

Numerical analysis of the subway tunnel thermal environment to predict the train-mounted condenser inlet temperature in the cold climate zone of China

Reasonable control of the subway tunnel thermal environment is the main objective of the ventilation system design, which is critical to the effectiveness of the train-mounted condenser. In this study, a numerical model utilizing the dynamic mesh technique is developed to investigate the subway tunnel thermal environmental characteristics in the cold climate zone of China. Full-scale field measurements are implemented to verify the model’s accuracy. According to the simulation results, the single Piston wind shaft (PWS) (outlet end) is the optimal ventilation system in the cold climate zone of China. The effects of tunnel wall temperature, passenger flow, and regeneration braking system (RBS) efficiency on the subway tunnel thermal environment are thoroughly analyzed, which shows that the tunnel wall temperature has the greatest effect on the air temperature rise of the subway interval tunnel, the passenger flow has the greatest effect on the air temperature rise of the subway station tunnel. In contrast, the RBS efficiency has the least effect on the maximum condenser inlet temperature. On this basis, the predictive model for the maximum and average condenser inlet temperature is proposed. The findings of this study provide a theoretical basis for temperature control in subway tunnels in the cold climate zone of China and contribute to the safe and energy-efficient operation of subway environmental control systems.

Autonomous Braking System for Automobile Powered by Artificial Intelligence and Reinforcement Learning

Autonomous Braking System for Automobile Powered by Artificial Intelligence and Reinforcement Learning

Research progress on transmission performance of special vehicles based on power loss characteristics analysis

The vehicle transmission system is a power transmission device between the engine and the wheel load. As the connecting hub of the power system, the travel system and the braking system, it ensures the mobility and safety of special equipment in combat missions. From the four aspects of the transmission system structure composition characteristics, power transmission characteristics, energy flow characteristics and vehicle power characteristics, it is demonstrated that the transmission efficiency is an important technical indicator for evaluating the performance of the transmission system; based on the analysis of the relationship between power loss and transmission efficiency, a global model framework of the power loss of the transmission system is established from the perspective of the generation mechanism and structural characteristics, providing a theoretical basis for the performance characterization of the transmission system; from the three aspects of theoretical numerical research, simulation research and experimental demonstration research of transmission efficiency, the difficulties and key points of the research on the power loss of the vehicle transmission system are discussed, and it is pointed out that the multi-media and multi-parameter coupling simulation analysis and experimental research of large-scale mechanical equipment under complex operating conditions can provide guidance for the performance optimization and health management of vehicle transmission components, and the performance evaluation and matching design of the transmission system; it is expected that the comprehensive transmission efficiency analysis under multiple factors, as well as the coupling research of power loss characteristics, efficiency characteristics and performance degradation characteristics based on intelligent algorithms have practical engineering significance for the performance monitoring and evaluation of large-scale mechanical equipment.

Integrated optimization control strategy for vehicle longitudinal and lateral assisted driving

In order to coordinate the control objectives of the longitudinal and lateral auxiliary driving system of the vehicle and the vehicle dynamics control requirements, this paper takes the four-wheel independent drive electric vehicle as the control object, and combines deep learning and model predictive control to establish the vehicle generalized control force prediction-dynamic optimization distribution control strategy. The upper-level algorithm calculates the generalized control force that meets the vehicle control requirements according to the reference objectives of the longitudinal and lateral auxiliary driving strategies; the middle-level module includes the vehicle expected generalized force neural network prediction model and the active set numerical solution algorithm; the lower level calculates the tire slip rate and sideslip angle according to the expected tire force, realizes the tire force control requirements by controlling the motor torque and the braking system, and adjusts the vehicle movement direction through the steering system. This paper uses simulation tests and hardware-in-the-loop tests to verify the algorithm. The results show that the established algorithm can simultaneously meet the longitudinal and lateral control requirements of the vehicle, with a lateral path following error of 0.0117 m and a vehicle speed error of 0.59 km/h.

Safety Trends in the Automobile Industry in India

The automobile industry in India has experienced significant advancements in recent years, driven by rapid technological innovations and evolving consumer expectations. Safety has emerged as a critical focus area, with stakeholders ranging from government bodies to manufacturers and consumers increasingly emphasizing the need for stringent safety measures. This paper explores the key safety trends shaping the Indian automotive sector, including the adoption of advanced driver-assistance systems (ADAS), the implementation of new crash test standards, and the increased integration of passive and active safety features in vehicles. Additionally, it highlights the regulatory changes brought forth by the Indian government, such as the Bharat New Vehicle Safety Assessment Program (BNVSAP) and mandatory safety norms like airbags and anti-lock braking systems (ABS). The study also examines the role of technological innovations, including connected vehicle technologies and the potential of autonomous driving in enhancing road safety. By analyzing these trends, the paper aims to provide insights into how safety measures in the Indian automobile industry are evolving to meet global standards and reduce the rising number of road accidents in the country.

FBrake, a Method to Simulate the Brake Efficiency of Laden Light Passenger Vehicles in PTIs While Measuring the Braking Forces of Their Unladen Configurations

This study introduces fBrake, a novel simulation method now designed for use in periodic technical inspections of M1 and N1 vehicle categories, addressing challenges posed by Directive 2014/45/EU. The directive mandates that braking efficiency must be measured relative to the vehicle’s maximum mass, which often results in underperformance during inspections due to vehicles typically being unladen. This discrepancy arises because the maximum braking forces are proportional to the vertical load on the wheels, causing empty vehicles to lock their wheels prematurely compared to laden ones. fBrake simulates the braking forces of unladen vehicles to reflect a laden state by employing an optimal brake-force distribution curve that aligns with the vehicle’s inherent braking behavior, whether through proportioning valves or through electronic brake distribution systems in anti-lock-braking-system-equipped vehicles. Our methodology, previously applied to heavy vehicles, involved extensive experimentation with a roller brake tester, comparing the actual braking performances of dozens of vehicles to those of their simulated counterparts using fBrake. The results demonstrate that fBrake reliably replicates the braking efficiency of laden vehicles, validating its use as an accurate and effective tool for braking system assessments in periodic inspections, irrespective of the vehicle’s load condition during the test. This approach ensures compliance with regulatory requirements while enhancing the reliability and safety of vehicle inspections.

Predicting noise and vibration in electric brake systems at mass production stage using q-axis current

This study explores the challenges of noise, vibration, and harshness (NVH) in electric brake systems within the context of the automotive industry's shift towards environmentally friendly technologies. The electrification of vehicles and their braking systems leads to weight reduction and enhanced braking efficiency. However, these advancements also yield new NVH challenges. The intricate motor-driven mechanisms of electric brake systems are prone to cogging torque, magnetic imbalance, and radial electromagnetic forces, which degrade the user experience and necessitate service interventions. Therefore, this study presents an approach to predicting noise and vibration levels using q-axis current measurements obtained during the initial actuation of electric brake systems in the mass production stage. This study aims to establish a predictive model that can identify potential NVH problems early, enhance the quality and reliability of electric brake systems, and improve user satisfaction. This method enhances sustainable vehicle technologies, improving the overall user experience. The study delves into the intricate relationship between electrical currents and NVH phenomena by integrating electromagnetic analysis with mechanical dynamics. Therefore, this paves the way for the development of advanced diagnostic tools in electric vehicle technology.

Thermal Fault-Tolerant Asymmetric Dual-Winding Motors in Integrated Electric Braking System for Autonomous Vehicles

A conventional dual-winding (DW) motor has two internal windings consisting of a master part and a slave part, each connected to a different electronic control unit (ECU) to realize a redundant system. However, existing DW motors have a problem related to heat generation in both the healthy mode and the faulty mode of the motor operation. In the healthy mode, unexpected overloads can cause both windings to burn out simultaneously due to equal heat distribution. If the current sensor fails to measure correctly, the motor may exceed the designed current density of 4.7 [Arms/mm2] under air-cooling conditions, further increasing burnout risk. External factors such as excessive load cycles or extreme heat conditions can further exacerbate this issue. In the faulty mode, the motor requires double the current to generate maximum torque, leading to rapid temperature increases and a high risk of overheating. To address these challenges, this paper proposes the design of a thermal fault-tolerant asymmetric dual-winding (ADW) motor, which improves heat management in both healthy and faulty modes for autonomous vehicles. A lumped-parameter thermal network (LPTN) with a piecewise stator-housing model (PSMs) was employed to evaluate the coil temperature during faulty operation. An optimal design approach, incorporating kriging modeling, Design of Experiments (DOE), and a genetic algorithm (GA), was also utilized. The results confirm that the proposed ADW motor design effectively reduces the risk of simultaneous burnout in the healthy mode and overheating in the faulty mode, offering a robust solution for autonomous vehicle applications.

The effect of annealing on the microstructure and wear performance of laser-clad high-entropy alloy composite coatings for monorail crane braking systems

Laser cladding was utilized to fabricate WC ceramic particle-reinforced CoCrFeMnNi high-entropy alloy (HEA) composite coatings, with an investigation into the influence of annealing heat treatment on the microstructure and wear behavior of the composite coatings. The HEA composite coatings with a WC particle content of 30 wt% primarily consist of a face-centered cubic (FCC) solid solution phase, various M6C carbides with blocky, fishbone, and dendritic morphologies, and incompletely melted WC ceramic particles. The microstructure of the composite coatings remains stable up to a temperature of 570°C. After annealing at 600°C, the microstructure transforms into a typical dendritic morphology with rod-like carbides precipitating from the solid solution and discontinuously distributed in the interdendritic regions. Due to the annealing softening effect, the microhardness of the coating decreases from 488.1 HV0.3 to 443.1 HV0.3. Following annealing at a high temperature of 800°C, recrystallization leads to a refined equiaxed grain microstructure, with precipitated carbides continuously distributed along the grain boundaries, forming a network. The combined effects of precipitation hardening and fine grain strengthening result in an increase in the microhardness of the coating to 568.6 HV0.3 after annealing at 800°C. As the annealing temperature increases, the wear rate of the WC particle-reinforced CoCrFeMnNi HEA composite coatings also increase. The wear mechanism for the unannealed coating is oxidative wear, and the reduction in hardness leads to adhesive phenomena in the coating after annealing at 600°C. The network of carbides reduces the ductility of the HEA and also the toughness of the oxide film, resulting in the highest wear rate for the coating annealed at 800°C, reaching 38.636×10−6 mm3/(N·m). This study provides valuable insights for the fabrication of advanced wear-resistant coatings.

Road target recognition based on radar range-Doppler spectrum with GS – ResNet

ABSTRACT Road target recognition ability of automotive millimetre-wave (mmWave) radar is crucial in areas such as autonomous driving, advanced driver assistance systems (ADAS), and automated emergency braking systems (AEBS). Current mmWave radar systems are primarily utilized for speed, distance, and angle measurements, with limited capability or unsatisfactory performance in target classification. In response to this limitation, this paper proposes a novel method for road target recognition, using radar range-Doppler spectrum as input data and introducing a global attention mechanism and SCConv module. First, the range-Doppler spectrum is processed by the clutter removal algorithm block to remove background clutter and vibration interference. Second, considering the small features and susceptibility to noise interference in the range-Doppler spectrum, we have devised a deep residual network based on a global attention mechanism, significantly enhancing the model’s accuracy in range-Doppler spectrum classification. Finally, we introduce the SCConv module and improve the downsampling module in ResNet to enhance the model’s classification accuracy. Experimental results demonstrate that the model achieves an average accuracy of 99.79% in classifying six types of road targets, significantly outperforming other methods. This research is of significant importance in advancing the understanding of road traffic conditions by autonomous driving systems and enhancing system safety.

Ego-Vehicle Speed Correction for Automotive Radar Systems Using Convolutional Neural Networks.

The development of autonomous driving vehicles has increased the global demand for robust and efficient automotive radar systems. This study proposes an automotive radar-based ego-vehicle speed detection network (AVSD Net) model using convolutional neural networks for estimating the speed of the ego vehicle. The preprocessing and postprocessing methods used for vehicle speed correction are presented in detail. The AVSD Net model exhibits characteristics that are independent of the angular performance of the radar system and its mounting angle on the vehicle, thereby reducing the loss of the maximum detection range without requiring a downward or wide beam for the elevation angle. The ego-vehicle speed is effectively estimated when the range-velocity spectrum data are input into the model. Moreover, preprocessing and postprocessing facilitate an accurate correction of the ego-vehicle speed while reducing the complexity of the model, enabling its application to embedded systems. The proposed ego-vehicle speed correction method can improve safety in various applications, such as autonomous emergency braking systems, forward collision avoidance assist, adaptive cruise control, rear cross-traffic alert, and blind spot detection systems.

Finite-Time Adaptive Control for Electro-Hydraulic Braking Gear Transmission Mechanism with Unilateral Dead Zone Nonlinearity

Autonomous vehicles require more precise and reliable braking control, and electro-hydraulic braking (EHB) systems are better adapted to the development of autonomous driving. However, EHB systems inevitably suffer from unilateral dead zone nonlinearity, which adversely affects the position tracking control. Therefore, a finite-time adaptive control strategy was designed for unilateral dead zone nonlinearity. Initially, the unilateral dead zone nonlinearity was reformulated into a matched disturbance term and an unmatched disturbance term to reduce the adverse effects of disturbances, thereby enhancing system controllability. Then, the “complexity explosion” in the design of the control strategy was avoided by command filtering, and the design process of the controller was simplified. Furthermore, the finite-time control theory was employed to boost the system’s convergence speed, thereby enhancing control performance. In order to ensure the stability of the system under the dead zone disturbance, the unknown disturbance terms were estimated. The stability of the control strategy was validated through the finite-time stability theorem and the Lyapunov function. Eventually, simulations and hardware-in-the-loop (HIL) experiments validated the feasibility and availability of the finite-time adaptive control strategy.

Pressing Mechanism Design and Performance Analysis for Brake Pedal System at Low-Speed Driving

This article focuses on the modelling and analysis of an automatic braking mechanism for low-speed driving scenarios. The study aims to replicate the force exerted by a driver on the brake and accelerator pedals by strategically placing the suitable actuator within the pedal subsystem assembly. The primary objective is to model the pedal pressing mechanism for the braking subsystem and gain insights into driver ‘s behaviour during traffic congestion, thereby ensuring the effective operation of the automatic braking system. The actuator was modelled using 3D virtual environment, while the car body or dynamics was modelled using SimScape in MATLAB environment, and the simulation performance analysis was employed to evaluate the performance outcomes. It has shown that the mechanism designed mimics the actual manual pedal pressing mechanism of driver’s leg where the results show that the actuator managed to produce 150 N to reach speed at 8.5 km/h at 48 mm linear actuator stroke. Therefore, the research findings are anticipated to contribute significantly to the advancement of automatic braking systems, particularly during low speed in road traffic delay, which may help in reducing the fatigue among drivers, enhancing vehicle safety, and providing valuable insights for the development of more reliable and efficient systems within the automotive industry.

Research on the characteristics of a pneumatic proportional valve

Abstract The execution of autonomous driving in heavy-duty trucks necessitates stringent regulation of their braking torque output. Hydraulic retarder serves as a widely auxiliary braking system in heavy-duty vehicles, with the pneumatic proportional valve functioning as the core component of its control system, regulating the output response and control precision of the braking torque of the hydraulic retarder. To improve the accuracy of brake torque control for hydraulic retarders, it is critical to conduct thorough research on the control system, especially the pneumatic proportional valve. Therefore, A detailed analysis of the working mechanism of pneumatic proportional valves was conducted, encompassing the construction of mathematical and simulation models. The efficacy of the simulation model was confirmed via experimental validation. When the control pressure increases, the simulation results are close to the experimental results, with a maximum discrepancy of 18%; when the control pressure decreases, the simulation results show a similar trend to the experimental results. The research can aid in formulating control methodologies for pneumatic proportional valves and offer theoretical guidelines for future exploration into boosting the precision of hydraulic retarder braking torque control.