Vehicle Braking Research Articles

Research on intelligent optimal allocation control strategy for stability and braking of heavy tyre blowout vehicle

The traditional control strategy mainly compensates and corrects the driving state of heavy vehicles with a tyre blowout, and rarely considers the need for emergency braking. It is also difficult to effectively coordinate the problems of lateral yaw, slip and tailspin, and longitudinal braking performance degradation. For this, an intelligent optimization allocation control strategy combining stability control and braking control is innovatively designed in this article. The joint simulation model for heavy tyre blowout vehicles is built based on the Dugoff tyre blowout model and the TruckSim vehicle model. A linear quadratic form regulator stable control based on the particle swarm optimization algorithm optimization is used to dynamic equilibrium of the additional yaw moment generated by the vehicle tyre blowout. A logic threshold braking control based on adaptive adjustment is adopted to achieve an ideal braking effect for the vehicle. In order to simultaneously consider the stability and braking performance of vehicles with blowout tyre, a braking force distribution strategy and a fuzzy optimization allocation algorithm are proposed to achieve coordination of lateral and longitudinal control strategies. The results indicate that intelligent optimized allocation control can effectively correct the deviation trajectory of a heavy tyre blowout vehicle, enabling it to achieve rapid braking while maintaining stability.

Assessing braking performance on wet-road through water-depth estimation and vehicle-pavement dynamic simulation

ABSTRACT The presence of water on wet roads due to rainfall has emerged as a critical factor influencing driving safety. During severe weather, the non-uniform water distribution on the road can significantly diminish pavement friction, elevating the risk of traffic accident. Furthermore, the tire-pavement friction coefficient varies with vehicle velocity, rendering wet braking analysis complex. Conventional braking risk analysis often assumes a fixed friction coefficient, neglecting the impact of uneven pavement-induced water depth irregularities. This paper introduces a novel braking performance assessment method based on water-depth estimation and vehicle-pavement simulation. The uneven water-depth distribution is first estimated using LiDAR-measured pavement geometry. A co-simulation framework is then proposed to analyze the tire-pavement friction and study the dynamic braking performance. The 85th percentile stopping distance is adopted as the evaluation index for quantifying braking risk. Results from case studies highlight the substantial influence of rainfall intensity and vehicle velocity on braking risk. Additionally, pavement rutting accumulates deeper water depth, thereby elevating braking safety risks. The proposed model offers a novel perspective on vehicle braking risk analysis and can serve as a valuable safety indicator for highway transportation management and decision-making in driving strategies during wet weather conditions.

Dynamic wheel-rail interaction of a train crossing a turnout under traction/braking behaviour and research on rail wear of the turnout

In order to study the dynamic behaviour of a vehicle passing through turnouts under traction and braking conditions, as well as its influence on the wear of turnout rails, a high-speed vehicle-turnout rigid-flexible coupling dynamic model is established based on the coupling dynamic theory of vehicle and turnout, using China’s No. 18 high-speed turnout and CRH380 high-speed EMU as prototypes. The model is used to analyse wheel-rail creep characteristics, wheel-rail contact mechanics, and wheel-rail wear under traction and braking conditions. The results indicate that when a high-speed train passes through a turnout under traction or braking conditions, the longitudinal creepage of the wheel-rail will change due to the rotative speed difference generated by traction or braking. Furthermore, due to the existence of the lead curve, the longitudinal creep rate of the wheel-rail becomes even more complex when passing through the turnout in the diverging route. The calculations reveal that the traction behaviour of the train leads to a significant increase in wear at the front of the switch rail and nose rail, while the wear number of the switch rail in the heel of the frog after 6m increases significantly under braking conditions. The different impact characteristics of vehicle traction and braking conditions on turnout rail wear obtained in this study can provide guidance for optimizing and grinding the profiles of turnout rails at the throat of railway stations.

Intelligent Robust Controllers Applied to an Auxiliary Energy System for Electric Vehicles

This paper presents two intelligent robust control strategies applied to manage the dynamics of a DC-DC bidirectional buck–boost converter, which is used in conjunction with a supercapacitor as an auxiliary energy system (AES) for regenerative braking in electric vehicles. The Neural Inverse Optimal Controller (NIOC) and the Neural Sliding Mode Controller (NSMC) utilize identifiers based on Recurrent High-Order Neural Networks (RHONNs) trained with the Extended Kalman Filter (EKF) to track voltage and current references from the converter circuit. Additionally, a driving cycle test tailored specifically for typical urban driving in electric vehicles (EVs) is implemented to validate the efficacy of the proposed controller and energy improvement strategy. The proposed NSMC and NIOC are compared with a PI controller; furthermore, an induction motor and its corresponding three-phase inverter are incorporated into the EV control scheme which is implemented in Matlab/Simulink using the “Simscape Electrical” toolbox. The Mean Squared Error (MSE) is computed to validate the performance of the neural controllers. Additionally, the improvement in the State of Charge (SOC) for an electric vehicle battery through the control of buck–boost converter dynamics is addressed. Finally, several robustness tests against parameter changes in the converter are conducted, along with their corresponding performance indices.

Bionic Optimization Design and Fatigue Life Prediction of a Honeycomb-Structured Wheel Hub.

The wheel hub is an important component of the wheel, and a good hub design can significantly improve vehicle handling, stability, and braking performance, ensuring safe driving. This article optimized the hub structure through morphological aspects, where reducing the hub weight contributed to enhanced fuel efficiency and overall vehicle performance. By referencing honeycombed structures, a bionic hub design is numerically simulated using finite element analysis and response surface optimization. The results showed that under the optimization of the response surface analytical model, the maximum stress of the optimized bionic hub was 109.34 MPa, compared to 119.77 MPa for the standard hub, representing an 8.7% reduction in maximum stress. The standard hub weighs 34.02 kg, while the optimized hub weight was reduced to 29.89 kg, a decrease of 12.13%. A fatigue analysis on the optimized hub indicated that at a stress of 109.34 MPa, the minimum load cycles were 4.217 × 105 at the connection point with the half-shaft, meeting the fatigue life requirements for commercial vehicle hubs outlined in the national standard GB/T 5334-2021.

Incorporating date palm fibers for sustainable friction composites in vehicle brakes

The demand for eco-friendly materials in automotive components has spurred research into natural fibers as sustainable alternatives for brake pads. This study examines the potential of date palm fibers, particularly the palm frond midrib (PFM), in brake pad composites. The effects of epoxy, PFM, and calcium carbonate on the composites’ mechanical and tribological properties were analyzed. The optimal formulation (25% epoxy, 30% PFM, 35% calcium carbonate) exhibited superior properties, including a hardness of 87 HRB, wear rate of 1.5E-03 mg/mm, and COF of 0.73, surpassing commercial pads. Additionally, an inverse relationship between PFM/calcium carbonate content and compressibility was observed, with increased calcium carbonate enhancing wear resistance. This research underscores the potential of utilizing date palm resources in eco-friendly brake manufacturing, reducing the environmental and health impacts of traditional materials.

Soft collision avoidance based car following algorithm for autonomous driving with reinforcement learning

By safety supervision on dangerous driving behaviors, emergent braking in autonomous vehicles can effectively prevent collisions when using the car following algorithm based on deep reinforcement learning. However, the significant deceleration associated with emergent braking often results in an uncomfortable driving experience and high energy consumption. To address this issue, a soft collision avoidance based car following algorithm is proposed. Different from emergent braking, our approach introduces a deceleration adjustment value to the current acceleration output. This adjustment value is calculated by considering safe distance with attenuation coefficient in terms of multi-step prediction, while the attenuation coefficient and the predicted time step are discussed in detail. Comparative analysis, including statistical results and representative cases, demonstrates that the proposed algorithm significantly enhances driving comfort (improve 37.341 %) and reduces energy consumption (improve 11.244 %) without increasing collision risks.

Wheel Slip Equilibrium Point Model Reference Adaptive Control Based PID Controller for Antilock Braking System: A New Approach

This paper presents a new approach to wheel slip control in Antilock Braking System (ABS) using an Approximated First Order Wheel Slip (AFOWS) Model Reference Adaptive Control (MRAC) based PID (AFOWS-MRAC-PID) controller. An ABS was modeled in a MATLAB/Simulink environment using a quarter car model with the proposed controller. Simulations were conducted with a wide range of adaptation gains (50, 100, 150, 200, and 250) to study the effectiveness of the proposed control system. The results revealed that the proposed system could track and maintain 10% wheel slip and eliminate oscillation (instability) in terms of overshoot associated with conventional PID controllers, particularly on wet and snowy road surfaces, using adaptation gains of 150, 200, and 250. Overall, the proposed system provided the best performance in terms of stopping distance, vehicle braking velocity, and braking torque on all road surfaces with an adaptation gain of 250, although braking on dry road surfaces was the most effective.

A comprehensive wheel–rail contact model incorporating sand fragments and its application in vehicle braking simulation

Increasing the wheel–rail adhesion coefficient by spreading sand grains to the wheel–rail interface is a common approach to improve the traction and braking efficiency of trains. To simulate this process accurately, two highlights are presented in this paper. Firstly, this paper proposes a wheel–rail contact model considering sand fragments, a third body, based on the non-Hertzian theory, which includes a random sand-grain generator and a sand crushing model. The proposed wheel–rail model is used to analyze the wheel–rail adhesion state after sand grains enter the wheel–rail contact interface. How sand particles change the distribution of normal force and tangential force to affect the wheel–rail adhesion is clarified and, in addition, the influence of the parameters of sand fragments on the wheel–rail adhesion coefficient is given. Secondly, a vehicle system dynamics model considering sanding and wheel slip protection (WSP) control is developed to analyze the effect of sanding on braking distance and wheel slip during braking processes. The wheel–rail contact model and the vehicle system dynamics model presented in this paper can support the study of more effective sanding and adhesion enhancement devices.

Collision Avoidance Path Planning and Tracking Control for Autonomous Vehicles Based on Model Predictive Control.

In response to the fact that autonomous vehicles cannot avoid obstacles by emergency braking alone, this paper proposes an active collision avoidance method for autonomous vehicles based on model predictive control (MPC). The method includes trajectory tracking, adaptive cruise control (ACC), and active obstacle avoidance under high vehicle speed. Firstly, an MPC-based trajectory tracking controller is designed based on the vehicle dynamics model. Then, the MPC was combined with ACC to design the control strategies for vehicle braking to avoid collisions. Additionally, active steering for collision avoidance was developed based on the safety distance model. Finally, considering the distance between the vehicle and the obstacle and the relative speed, an obstacle avoidance function is constructed. A path planning controller based on nonlinear model predictive control (NMPC) is designed. In addition, the alternating direction multiplier method (ADMM) is used to accelerate the solution process and further ensure the safety of the obstacle avoidance process. The proposed algorithm is tested on the Simulink and CarSim co-simulation platform in both static and dynamic obstacle scenarios. Results show that the method effectively achieves collision avoidance through braking. It also demonstrates good stability and robustness in steering to avoid collisions at high speeds. The experiments confirm that the vehicle can return to the desired path after avoiding obstacles, verifying the effectiveness of the algorithm.

Regarding the issue of the influence of factors on the braking parameters of M1 category vehicles with electric or hybrid power unit

Problem. The relevance of this work is explained by the fact that there are no works at all in the reference and normative literature on the theory and practice of forensic auto technical examination, and even more so, methodical recommendations regarding the values ​​of the braking parameters of vehicles of the M1 category with an electric power plant. Goal. The purpose of the work is to establish the factors that affect the braking parameters of M1 category vehicles with an electric or hybrid power unit. Methodology. The approaches adopted in the work to solve the set goals are based on the theory of conducting the experiment, the theory of the interaction of the pneumatic tire with the road surface, the theory of the car and the laws of theoretical mechanics. Results. On the basis of the obtained experimental data regarding the value of permanent deceleration and the time value of the increasing deceleration during emergency braking of the M1 category vehicles with an electric or hybrid power unit, the tasks will be solved necessary for conducting forensic engineering and transport examinations for specific road traffic events with the participation of M1 category vehicles with an electric or hybrid power unit. Originality. The results of the study provided an opportunity to get an idea of the influence of factors on the braking parameters of M1 category vehicles with an electric or hybrid power unit. Practical value. The obtained results can be recommended to forensic experts when writing expert opinions or expert studies.

Real-time testing of AI enabled automatic emergency braking system for ADAS vehicle using 3D point cloud and precise depth information

At the forefront of automobile safety technology, Automatic Emergency Braking (AEB) represents a major advancement in collision avoidance systems. The cutting-edge technology provides an additional layer of security at pivotal times, making it a vital part of the changing landscape of vehicle safety. This research introduces an effective system for automatic emergency braking in ADAS-equipped or Autonomous vehicles using a combination of 3d lidar and stereo vision camera for a swift and robust system in the vehicle that is faster than human drivers in cases of unexpected emergencies. Utilizing the power of clustering algorithms on 3d point clouds and state-of-the-art computer vision algorithms on an RGB image mapped to a depth frame from the stereo vision camera, the system as a whole provides a comprehensive system adding to the safety of the vehicle and the passengers. Further, the efficiency of the system is studied based on various parameters. The data from an external inertial measurement unit is also utilized to derive results that support the claims of the study. The system has been developed and implemented on a passenger car that has been modified into an electric vehicle and further tested in real-world traffic conditions in autonomous driving mode. The findings of the study were having exceptionally good precision in split-second decision-making in emergency maneuvers.

A rotary self-sensing magnetorheological damper based on triboelectric nanogenerator

A rotary self-sensing magnetorheological (MR) damper(RSMRD) based on a triboelectric nanogenerator is proposed in this study, which can provide variable torque and state self-sensing without a power supply. Compared with traditional self-sensing devices, the sensing part of RSMRD has the advantages of small size, no external power supply, and good low-frequency response. The feasibility of the angular velocity self-sensing (AVS) function is verified through theoretical derivation and experimental verification. The experimental results demonstrate a linear relationship between the output voltage generated by the AVS component and the rotational speed of the rotating shaft. Additionally, the torque characteristics of the rotary self-sensing MR damper are tested, revealing a torque generation of approximately 9.26 N ⋅ m at a current of 1.6 A. Furthermore, a fuzzy control algorithm for vehicle braking is proposed, based on the model parameters of RSMRD. The simulink software is used to establish a dynamic model of 1/4 car braking, with an initial braking speed of 15 m s−1. The results indicate that the vehicle comes to a complete stop after 1.64 s, with a braking distance of 10.93 m. Throughout the braking process, the vehicle slip rate remains close to the optimal slip rate of 0.2.

Application of dynamic desired headway based adaptive backstepping sliding mode control design to mixed traffic system

To optimize the mixed car-following behavior of connected autonomous vehicles (CAVs) and human-driven vehicles (HDVs), an adaptive backstepping sliding mode control (ABSMC) strategy for longitudinal velocity and distance control model (namely, MCF-ABSMCM) is put forth. First, the variable desired headway model (VDHM) is designed based on the vehicle-to-vehicle and vehicle-to-infrastructure information. Also, an asymmetric stochastic car-following model (ASCM) is designed to realistically describe the stochastic factor as well as vehicle acceleration and braking behaviors in mixed car-following. Second, an adaptive cruise sliding mode control law with a backstepping approach is devised to precisely track the desired following distance based on the VDHM. After creating the basic diagram of the two-model traffic flow, the intelligent driver model (IDM) is used as a baseline to compare and analyze the traffic capacity. Lastly, the effectiveness of the MCF-ABSMCM approach is confirmed in terms of both the mixed traffic flow density wave evolution and the vehicle control strategy, and the MCF-ABSMCM is validated under various adversary inputs. The simulation results demonstrate that the mixed-flow queue can finish headway tracking and keep a safe distance when using the MCF-ABSMCM described. This control strategy has been validated in VISSIM to significantly improve the efficiency of traffic operations compared to IDM and ASCM.

Energy recovery and storage systems in vehicle braking systems

The paper focuses on the most frequently used systems for storing energy recovered during vehicle braking are presented in this paper. Various solutions relying mainly on electrochemical batteries were analysed. The attention is also concentrated on systems that enable storing large amounts of energy using supercapacitors, and kinetic energy accumulators as the alternative approach.

Research capabilities of the Competence Centre for Autonomous and Connected Vehicles in the area of testing autonomous vehicles in Poland

The paper focuses on the most frequently used systems for storing energy recovered during vehicle braking are presented in this paper. Various solutions relying mainly on electrochemical batteries were analysed. The attention is also concentrated on systems that enable storing large amounts of energy using supercapacitors, and kinetic energy accumulators as the alternative approach.

Thermodynamics-Based Energy Management Strategy for Electric Vehicle Braking

Thermodynamics-Based Energy Management Strategy for Electric Vehicle Braking

Laboratory Tests on the Possibility of Using Flax Fibers as a Plant-Origin Reinforcement Component in Composite Friction Materials for Vehicle Braking Systems.

Braking systems are extremely important in any vehicle. They convert the kinetic energy of motion into thermal energy that is dissipated into the atmosphere. Different vehicle groups have different nominal and maximum speeds and masses, so the amount of thermal energy that needs to be absorbed by the friction pads and then dissipated can vary significantly. Conventional friction materials are composite materials capable of withstanding high temperatures (in the order of 500-600 °C) and high mechanical loads resulting from braking intensity and vehicle weight. In small vehicles traveling at low speeds, where both the amount of thermal energy and its density are limited, the use of slightly weaker friction materials with better ecological properties can be considered. This work proposes a prototype composite friction material using flax fibers as reinforcement instead of the commonly used aramid. A number of samples were prepared and subjected to laboratory tests. The samples were prepared using components of plant origin, specifically flax fibers. This component acted as reinforcement in the composite friction material, replacing aramid commonly used for this purpose. The main tribological characteristics were determined, such as the values of the coefficients of friction and the coefficients of abrasive wear rate. For this purpose, an authorial method using ball-cratering contact was used. The results were analyzed using statistical methods. It was found that the composite material using flax fibers does not differ significantly in its tribological properties from conventional solutions; so, it can be assumed that it can be used in the vehicle's braking system.

Pedestrian-ground contact injury protection method under the constraint of the vehicle-front end shape and its robust analysis

This research paper introduces a novel approach for protecting pedestrians from ground contact injuries through incorporating vehicle front-end shape constraints in the braking control method. The feasibility of the proposed method is evaluated through simulations, and its resilience to different disturbances is studied. Results indicate that the proposed method effectively manages vehicle movement by monitoring the first head-vehicle contact time (t1 ) between the pedestrian’s head and the vehicle. The simulations show that the proposed method reduces ground-related Weighted Injury Cost (WIC) by up to 84%, and the proportion of ‘safe’ mechanisms increases to 74%. The robustness of the braking control method is also evidenced by its high performance during disturbances such as changes in friction coefficient, lag time, and t1 . Furthermore, the anti-disturbance abilities of each vehicle shape are comparable except for t1 disturbance. There are no significant variations in the braking control protection effect between different friction coefficients and each t1 , but noticeable differences exist between lag times. Further analysis reveals that parameter disturbances affect the deceleration of the vehicle and the impact speed of the pedestrian and vehicle, leading to changes in the Vz (Vertical head-to-ground impact velocity), thorax acceleration, pelvic lateral impact force, and knee lateral bending angle, which subsequently increases the risk of pedestrian ground contact injuries. The proposed method offers an efficient solution for protecting pedestrians from ground contact injuries by controlling vehicle braking, highlighting its practical utility.

Analyzing Tribological and Mechanical Properties of Polymer Nanocomposite for Brake Pad Applications - A Critical Review

A brake pad is an integral component of a vehicle's braking system, designed to impart controlled friction and, ultimately, assist in slowing or stopping a vehicle. Their constituents include binder, filler, abrasive, lubricant, and reinforcing fiber. Materials for brake pads must have excellent wear resistance, increased heat dissipation, a consistent coefficient of friction, low noise and vibration, durability, compatibility, minimal environmental impact, and cost-effectiveness. This paper aims to examine the various materials used in brake pad applications. They are composed of matrix, ceramic, and polymer composites, and are manufactured using various processes. In addition to mechanical and tribological testing, there are various methods for testing the mechanical and tribological properties of brake pads. Various instruments, such as SEM, TEM, AFM, and XRD, were surveyed in order to analyse the morphology and crystal structure of nanoscale brake pads. Various applications such as automobiles, railroads, and aerospace utilise brake pads. The study reveals that integrating nano-fillers into polymer composites significantly enhances the mechanical and tribological properties of automotive brake pads, offering a promising route toward more durable, efficient, and safer braking systems. Through this analysis, researchers will gain a deeper understanding of the materials used in brake pads and their adaptability for various applications.