Braking Operation Research Articles

Study on the Origin of Rail Corrugation at a Long Downhill Braking Section Based on Friction-Excited Oscillation

This article studies a special rail corrugation phenomenon occurring at a braking section of Shenzhen Metro Line 3 based on friction-excited oscillation. The rail corrugation is strongly related to the braking operation: when the braking operation was canceled, the corrugation did not appear again after being ground. In this article, a new viewpoint that the corrugation originates from the unstable vibration of the wheel–rail–brake shoe braking system is put forward. To test this point of view, a finite element model composed of two wheelsets with a brake shoe braking system and two rails for complex modal analysis was established. Parameter sensitivity analysis was carried out to develop some measures to suppress rail corrugation. The results show that rail corrugation at the long downhill braking section originates from the unstable vibration at about 430 Hz of the wheel–rail–brake shoe braking system. The corrugation wavelength predicted by the finite model is about 55 mm, which shows good agreement with the on-site data. The results of parameter sensitivity analysis show that the influence of the coverage angle of the brake shoe on the rail corrugation is significant. The possibility of the rail corrugation and its progression speed increase significantly with a decrease in the coverage angle of the brake shoe. To suppress the rail corrugation, the coverage angle should not be less than 48° when designing the brake shoe structure. The influence of the installation position of the brake shoe on the rail corrugation is also obvious. The position of the brake shoe with a pressure angle of 8° can restrain rail corrugation to the greatest extent. The contact state between the brake shoe and wheel tread has little influence on rail corrugation. In practice, the brake shoe should be in full contact with the tread.

Braking Torque Control Strategy for Brushless DC Motor With a Noninductive Hybrid Energy Storage Topology

This article first presents a simple hybrid energy storage system (ESS) that consists of a battery, a supercapacitor and two mosfet s, without additional inductors and other power devices. Then, according to the operation characteristics of the brushless DC motor, the energy transmission of this storage system is discussed when the motor operates in constant speed mode, acceleration mode, and braking deceleration mode, respectively. In the braking operation mode, four types of switching vectors are further designed based on the ESS. By analyzing the influence of different switching vectors on the two objectives of braking torque control and braking energy regeneration, the priority grade of each vector is determined from these two perspectives. On this base, the switching vector selection mechanism based on average grade ranking is constructed. The proposed strategy gives consideration to both smooth braking torque control and effective braking energy regeneration by adopting unified switching vectors during the whole braking process, without needing to switch control strategies according to the speed range. The feasibility of the presented method is validated by the experimental results.

Examination of Experimental Method to Extract Characteristics of Lower Limb Movement in Emergency Braking Operation

The purpose of this study is to clarify the driving behavior and reaction pattern peculiar to the elderly. In this paper, we conducted a brake operation experiment with five young people, and aimed to create an evaluation index and an experimental method that can extract the characteristics of emergency brake operation from pedaling force and lower limb movement. The results showed that in order to operate the brakes strongly and quickly, the knee was firmly flection, and then the pedaling force was increased when the knee was extended. Furthermore, it was shown that if the brakes were operated without moving the ankle joint, the operation would be quicker.

Seat-driver vibration parameters effect on horizontal driver acceleration and its relationship to driver mass

This paper studies the direct effects of acceleration transmissibility between the head and seat of the driver, such as driver mass. The six DOF, seat-driver vibration model, is considered. A refuse truck with a specific driving cycle for 20 minutes is selected to evaluate the horizontal driver vibrations. The horizontal acceleration used on the driver is due to acceleration and braking operations, and the amount is considered based on the root mean square of the vibration transfer function for 20 minutes. Besides, suitable values of the vibration parameters are obtained according to the driver mass to minimise the horizontal acceleration. A survey conducted shows that the damping coefficient between the lower part of the driver's body and seat the most effect on the horizontal acceleration acting on the driver. A linear relation between driver mass and backrest parameters and seat pan derived. Also, polynomial equations between driver mass, seat pan, and backrest derived.

Blockchain-Based Federated Learning for Intelligent Control in Heavy Haul Railway

Due to the long train marshaling and complex line conditions, the operating modes in heavy haul rail systems frequently change when trains travel. Improper traction or braking operation made by drivers will increase the longitudinal impact force to trains and causes the train decoupling, severely affecting the safe operations of trains. It is quite desirable to replace the manual control with intelligent control in heavy haul rail systems. Traditional machine learning-based intelligent control methods suffer from insufficient data. Due to lacking effective incentives and trust, data from different rail lines or operators cannot be shared directly. In this paper, we propose an approach on blockchain-based federated learning to implement asynchronous collaborative machine learning between distributed agents that own data. This method performs distributed machine learning without a trusted central server. The blockchain smart contract is used to realize the management of the entire federated learning. Using the historical driving data collected from real heavy haul rail systems, the learning agent in the federated learning method adopts a support vector machine (SVM) based intelligent control model. To deal with the imbalanced traction and braking data, we optimize the classic SVM model via assigning different penalty factors to the majority and minority classes. The data set are mapped to a high dimension using kernel functions to make it linearly separable. We construct a mixing kernel function composed of polynomial and radial basis function (RBF) kernel functions, which uses a dynamic weight factor changing with train speeds to improve the model accuracy. The simulation results demonstrate the efficiency and accuracy of our proposed intelligent control method.

Microcontroller Based Bi-Directional DC-DC Converter for Automobile Application

This paper presents different topology for non isolating bi-directional dc–dc converter for automotive application. To increase and decrease the voltage level Buck-boost bidirectional converter type is used. This type of converter reduces the switching losses by using less number of switches. Also regenerative concept was introduced. During braking operation the energy stored in the motor was reduced by buck operation of the bidirectional converter and stored into the battery. This Battery will also act as the supply voltage when required. An auxiliary energy storage battery stores the regenerated energy which is obtained during the process of braking and it fed back to the electric machine in the electric vehicle applications. Auxiliary battery provides the power to the bidirectional dc-dc converter to boost the high-voltage bus during vehicle starting. To achieve power transfer between two dc power sources in either direction, the bidirectional dc-dc converters are used since it has the ability to reverse the direction of the current flow and power. This can also be used in multi port systems. In Multi-Port HEVs, two or more voltage source purposes of better performances of the vehicle are used.

DC Feeder Voltage Control Strategy of Bidirectional DC to DC converter for Railway Traction

The regenerative energy which is generated during the period of braking of railway traction increases voltage of DC feeder line which makes it crucial and important to consider. Regenerative energy storage system is one of the key solutions to use regenerative energy more effectively and efficiently. Super capacitor has advanced version of the conventional capacitor because of its instant charging and discharging, making it suitable to use as energy storage device for traction system. In this paper, operation of half bridge type bidirectional DC-DC converter for both running and braking operation of traction motor is modeled & simulated and performance analysis is carried out. During charging mode of supercapacitor this converter works as buck converter and during discharge works as boost converter to control the DC feeder voltage at appropriate levels.

An intelligent braking system composed single-pedal and multi-objective optimization neural network braking control strategies for electric vehicle

The braking system is significant to improve the total energy efficiency and ensure driving security of electric vehicles. An intelligent braking system (IBS) composed single-pedal and multi-objective optimization neural network braking control strategies is proposed in this paper to improve the energy economy, braking stability and driving intelligence for electric vehicles. The braking operations of drivers are divided into two parts: (1) releasing the accelerator pedal and (2) stepping on brake pedal. In the first braking operation, a single-pedal regenerative braking control strategy (RBCS) of accelerator pedal based on adaptive fuzzy control algorithm is proposed to improve energy recovery and driving intelligence. Simulation results illustrate that the simulation velocities under the control of adaptive single-pedal RBCS can follow several standard test cycles (including US06, UDDS, LA92 and ECE) very well. The braking energy can be recovered effectively with a less usage of brake pedal. In the second braking operation, a neural network (NN) controller for the composite braking system (CBS) is proposed to optimize the energy economy and braking stability at the same time. The control effect is verified by simulation results under NEDC cycles. The hardware-in-loop (HIL) experiments of the IBS are also conducted in this paper. Compared with a parallel braking strategy used in EU260 electric vehicles, the energy economy of IBS is improved by 3.67% than EU260 in 3 NEDC cycles. IBS performs more closely to the I curve in a specific braking condition with a decreasing braking severity. The time ratio of hydraulic braking in IBS is 2.27% less than EU260 with an increasing driving intelligence.

E-bikers’ braking behavior: Results from a naturalistic cycling study

Objective: The number of e-bike users has increased significantly over the past few years and with it the associated safety concerns. Because e-bikes are faster than conventional bicycles and more prone to be in conflict with road users, e-bikers may need to perform avoidance maneuvers more frequently. Braking is the most common avoidance maneuver but is also a complex and critical task in emergency situations, because cyclists must reduce speed quickly without losing balance. The aim of this study is to understand the braking strategies of e-bikers in real-world traffic environments and to assess their road safety implications. This article investigates (1) how cyclists on e-bikes use front and rear brakes during routine cycling and (2) whether this behavior changes during unexpected conflicts with other road users.Methods: Naturalistic data were collected from 6 regular bicycle riders who each rode e-bikes during a period of 2 weeks, for a total of 32.5 h of data. Braking events were identified and characterized through a combined analysis of brake pressure at each wheel, velocity, and longitudinal acceleration. Furthermore, the braking patterns obtained during unexpected events were compared with braking patterns during routine cycling.Results: In the majority of braking events during routine cycling, cyclists used only one brake at a time, favoring one of the 2 brakes according to a personal pre-established pattern. However, the favored brake varied among cyclists: 66% favored the rear brake and 16% the front brake. Only 16% of the cyclists showed no clear preference, variously using rear brake, front brake, or combined braking (both brakes at the same time), suggesting that the selection of which brake to use depended on the characteristics of the specific scenario experienced by the cyclist rather than on a personal preference. In unexpected conflicts, generally requiring a larger deceleration, combined braking became more prevalent for most of the cyclists; still, when combined braking was not applied, cyclists continued to use the favored brake of routine cycling. Kinematic analysis revealed that, when larger decelerations were required, cyclists more frequently used combined braking instead of single braking.Conclusions: The results provide new insights into the behavior of cyclists on e-bikes and may provide support in the development of safety measures including guidelines and best practices for optimal brake use. The results may also inform the design of braking systems intended to reduce the complexity of the braking operation.

Using Approximate Dynamic Programming to Maximize Regenerative Energy Utilization for Metro

With the rapid development of Metro, it has aroused more attention to its energy efficiency. The regenerative energy is a kind of energy generated by a braking train, which can be used by other trains nearby. Due to the application of regenerative braking and automatic train operation function, more and more studies focus on using regenerative energy by optimal train control. To maximize the utilization of regenerative energy for a couple of trains, we formulate a model and design an algorithm for maximizing the utilization of regenerative energy (MURE) by using the proposed approximate dynamic programming (ADP) approach to adjust the speed curve of the accelerating train. Then, we discuss three approximation methods for the proposed ADP-based approach such as rollout method, interpolation method, and neural network. The rollout algorithm could improve the basic policy for train control with carefully designing. The function approximation method using interpolation could further decrease the energy consumption with assuring punctuality. The neural network approximation usually cannot realize the effect superior to the interpolation strategy due to its complex structure, and it needs more computation time. Finally, the analysis of regenerative energy utilization is given by implementing the numerical experiments with field data from the Yizhuang line, Beijing subway. The numerical results show its effectiveness and stability.

Study of wheel-rail adhesion during braking maneuvers

The present work aims to better understand the phenomenon of adhesion under degraded conditions during railway braking maneuvers with the aim of optimizing the anti-slip algorithms in order to reduce damage to the profiles of wheels and rails and to minimize the braking distance. The proposed approach is based on the analysis of experimental data acquired during braking tests carried out on track, considering different types of vehicles and different types of contaminants, able to reproduce the typical degraded adhesion conditions occurring during normal operation. The work describes a numerical model that allows to evaluate the dynamics of the vehicle during the braking operation and to correlate the pressures to the brake cylinder, which are related to the braking forces, and the angular velocities measured on the axles of the vehicle, with the adhesion coefficient.

Variable Switch Regenerative Braking Technique for PM BLDC Motor Driven Electric Two-wheeler

In this paper PM BLDC motor driven electric two-wheeler is proposed. The operation of PMBLDC motor in all four quadrants along with various regenerative braking control strategies are simulated MATLAB/ SIMULINK. Three braking methods are proposed for electric vehicle application. Factors like recovered energy, braking time, maximum braking current are compared. Depending on the simulation results switching between different braking methods is proposed for efficient and reliable braking operation. Moreover, by using variable switch braking technique one can extract more braking energy.

Study on driver’s braking intention identification based on functional near-infrared spectroscopy

Purpose Cooperative driving refers to a notion that intelligent system sharing controlling with human driver and completing driving task together. One of the key technologies is that the intelligent system can identify the driver’s driving intention in real time to implement consistent driving decisions. The purpose of this study is to establish a driver intention prediction model. Design/methodology/approach The authors used the NIRx device to measure the cerebral cortex activities for identifying the driver’s braking intention. The experiment was carried out in a virtual reality environment. During the experiment, the driving simulator recorded the driving data and the functional near-infrared spectroscopy (fNIRS) device recorded the changes in hemoglobin concentration in the cerebral cortex. After the experiment, the driver’s braking intention identification model was established through the principal component analysis and back propagation neural network. Findings The research results showed that the accuracy of the model established in this paper was 80.39 per cent. And, the model could identify the driver’s braking intent prior to his braking operation. Research limitations/implications The limitation of this study was that the experimental environment was ideal and did not consider the surrounding traffic. At the same time, other actions of the driver were not taken into account when establishing the braking intention recognition model. Besides, the verification results obtained in this paper could only reflect the results of a few drivers’ identification of braking intention. Practical implications This study can be used as a reference for future research on driving intention through fNIRS, and it also has a positive effect on the research of brain-controlled driving. At the same time, it has developed new frontiers for intention recognition of cooperative driving. Social implications This study explores new directions for future brain-controlled driving and wheelchairs. Originality/value The driver’s driving intention was predicted through the fNIRS device for the first time.

Towards a two-part train traffic emissions factor model for airborne wear particles

In 2017 a new railway tunnel containing two stations opened in Stockholm, Sweden. A series of field measurements were carried out on the platforms in this tunnel before and after it was opened for normal traffic. These measurements were used to investigate the contribution of airborne particle emissions from wear processes to total train emissions. This field data was used to develop a two-part train traffic emission factor model for PM10. The two parts are the accumulative effect term (relating to operating distance such as wheel-rail contact and overhead electric line sliding contact) and a brake effect term (relating to the number of braking operations such as brake disc and brake pad contact). The results show that operating a single trial train at a higher than normal frequency on an otherwise empty platform increases the platform particulate concentration until the concentration reaches a steady value. The model suggests that brake emissions account for about 50% of the total emissions measured in the tunnels.

A Smooth Torque Control Strategy for Brushless DC Motor in Braking Operation

In braking operation, when the unipolar modulation pattern is adopted by brushless DC motor (BLDCM), there exists not only the commutation torque ripple, but also a problem concerning controllability of braking torque. This paper conducts a research into eight unipolar modulation patterns and proposes a smooth braking torque control strategy for BLDCM. First, the controllability principle of braking torque is theoretically analyzed under different modulation patterns. Then, this paper derives and compares the speed ranges of each pattern where the braking torque is controllable and the commutation torque ripple can be reduced. On this basis, according to the torque control performance of each modulation pattern in different speed ranges, an optimized combination modulation method is developed in full-speed range. During the whole braking process, the proposed control strategy ensures that the braking torque is controllable, and meanwhile the commutation torque ripple can be reduced, thus obtaining good braking torque control performance. The effectiveness of the proposed strategy is verified by experimental results.

Assessing wagon pack sizes in longitudinal train dynamics simulations

ABSTRACT Wagon packs replace some couplers with draw-bars to reduce slacks in the train. Prior to the decision of wagon pack sizes, the implications of wagon pack sizes for train dynamics and connection system fatigue life have to be assessed. This paper uses longitudinal train dynamics (LTD) simulations to assess three different wagon pack sizes (1-pack, 2-pack and 4-pack) for a real-world heavy haul train configuration on a real-world railway. Simulations are conducted to assess the implications of wagon pack sizes during train starting, speed correction braking, emergency braking and whole-trip train operations. In-train forces and train speed differences are compared and analysed for all simulations. Wagon connection fatigue life is compared for the whole-trip train simulations. The results show that both 2-pack and 4-pack plans can decrease the in-train force magnitudes during train operations. However, the improvements from the 1-pack plan to 2-pack plan are evidently larger than those when moving from the 2-pack plan to 4-pack plan. The results also show that force magnitudes are not the major conflict for the studied cases. Fatigue life calculations show that the 2-pack plan and 4-pack plan can increase the wagon connection system fatigue life by 69% and 176%, respectively Table 2.

Development of Braking Force Distribution Strategy for Dual-Motor-Drive Electric Vehicle

In the development of the optimal braking force distribution strategy for a dual-motor-drive electric vehicle (DMDEV) with a series cooperative braking system, three key factors were taken into consideration, i.e. the regenerative force distribution coefficient between the front and the rear motor ( β ), the energy recovery coefficient at the wheels ( α 3 ), and the front-and-rear-axle braking force distribution coefficient ( λ ). First, the overall power loss model of the two surface-mounted permanent magnetic synchronous motors (SMPMSMs) was created based on the d-q axis equivalent circuit model. The optimal relationship of β and the overall efficiency of the dual-motor system were confirmed, where the latter was quite different from that obtained from the traditional look-up table method for the motors’ efficiency. Then, four dimensionless evaluation coefficients were used to evaluate braking stability, regenerative energy transfer efficiency, and energy recovery at the wheels. Finally, based on several typical braking operations, the comprehensive effects of the four coefficients on braking stability and energy recovery were revealed. An optimal braking force distribution strategy balancing braking stability and energy recovery is suggested for a DMDEV with a series cooperative braking system.

Towards a real-time pneumatic tire performance prediction using an advanced tire-ice interface model

Icy road conditions and tire operational parameters play a vital role in determining the overall performance of a vehicle. This study builds on prior work in the researchers’ group. The Advanced Tire-Ice Interface Model (ATIIM) simulates the temperature rise in the contact patch based on the measured pressure distribution and the thermal properties of the tread compound and of the ice surface. It has the capability to simulate the height of the thin water film created from the melted ice, to predict the tractive performance, and to estimate the viscous friction due to the water layer and the influence of braking operations, including the locked wheel condition. The experimental investigation included measuring the bulk temperature distribution in the contact patch to validate the temperature rise simulations of the ATIIM. As shown by the simulations and the test data, a rise in temperature was observed from the leading edge to the trailing edge of the contact patch. As the wheel load increases, the difference in temperature rise increases, as also reflected in the experimental study. When the temperature difference was significant, a thin water film was observed that resulted in a reduction of friction, which was simulated using the ATIIM.

Thermal Analysis of Solid Disc Brake Rotor

The work deals with the analysis of heat generation and dissipation in a solid disc brake of a motorcycle during continuous braking by using computer -aided engineering software with two disc profile and three different materials of the rotor disc. The objective of this work is to investigate and analyze the temperature distribution and heat dissipation (steady- state thermal analysis) of the rotor disc during braking operation. The work uses the finite element analysis technique to predict the temperature distribution on the disc rotor and to identify the critical temperature of the brake rotor disc. All three modes of heat transfer (conduction, convection, radiation) have been analyzed. The three different materials studied are Grey Cast Iron, Aluminum Alloy 6262 T-9 and Carbon-Ceramics with two different profiles of disc rotor. The results obtained from the analysis shows that different material on similar load conditions during continuous braking shows different temperature distribution. Thus, a comparison is made between the three materials used to know the best material for making disc brake rotor based on the rate of heat dissipation and critical temperature. Hence, it is found that Aluminum Alloy is the most appropriate material among all three material selected for solid disc rotor.

An Open-Circuit Fault Diagnosis Approach for Single-Phase Three-Level Neutral-Point-Clamped Converters

This paper presents a model-based open-circuit fault diagnosis approach for single-phase three-level neutral-point-clamped (3LNPC) converters in electric railway application. The diagnosis algorithm, which only requires the signals existing in the control system, not only detects open-circuit faults but also identifies the faulty device among the transistors and clamping diodes. The mixed logical dynamic (MLD) model of the converter is built to estimate the grid current. The residual generated from the measured current subtracting the estimated one is analyzed under different open-circuit faults. According to the characteristics of the residual changing rate, the proposed approach allows fault localization. The proposed method is effective both in traction and regenerative braking operation and has fast diagnosis speed. Hardware-in-the-loop (HIL) experiments are carried out to verify the effectiveness of the proposed fault diagnosis algorithm.