Braking Model Research Articles

Regenerative Braking Logic That Maximizes Energy Recovery Ensuring the Vehicle Stability

This paper presents a regenerative braking logic that aims to maximize the recovery of energy during braking without compromising the stability of the vehicle. This model of regenerative braking ensures that the regenerative torque of the electric motor (for front- and rear-wheel drive vehicles) or electric motors (for all-wheel drive vehicles equipped with one motor for each axle) is exploited to the maximum, avoiding the locking of the driving wheels and, subsequently, if necessary, integrating the braking with the traditional braking system. The priority of the logic is that of maximizing energy recovery under braking, followed by the pursuit of optimal braking distribution. This last aspect in particular occurs when there is an integration of braking and, for vehicles with all-wheel drive, also when choosing the distribution of regenerative torque between the two electric motors. The logic was tested via simulation on a front-, rear-, and all-wheel drive compact car, and from the simulations, it emerged that, on the WLTC driving cycle, the logic saved between 29.5 and 30.3% in consumption compared to the same vehicle without regenerative recovery, and 22.6–23.5% compared to a logic commonly adopted on the market. On cycle US06, it saves 23.9–24.4% and 19.0–19.5%, respectively.

Transmission speed and ratio optimization for heavy-duty electric truck

Nowadays, the Heavy-Duty Truck industry is facing one of the most critical questions in the universe. How would it be possible to decrease the CO2 emissions? Performing all possible technological steps in conventional engines is only a “part” of the solution. Electrification is a must for both keeping the environment clean and fulfilling the stringent emission regulations successfully. In this paper, the electrification part of the solution is examined. The main goal is to develop a transmission speed and ratio selection methodology that can be used at the early stages of battery electric truck development, especially for conceptual decisions or hardware selection. The authors are focused on the effect of electric axle (e-axle) transmission speed and ratio selection in 27 Tons Battery Electric (BE) Road Truck application. First of all, a one-dimensional vehicle model is created in GT-Suite software. Then, e-axle, electric motor (e-motor) & battery, regenerative braking model block, electric driveline transmission & differential submodels, and the integrated control algorithm are also implemented. In order to complete a thorough analysis, five different transmission designs (2-speed single, 2 + 1 speed split, 2 + 2 speed split, 3-speed single, 4-speed single) with thousands of gear ratio sets are studied. Satisfying the performance requirements with minimum energy consumption in defined Vecto routes is the vital target of these studies. Dual e-motor studies show that the most effective way of decreasing energy consumption is using e-motors at the same speed (up to 5% benefit) and turning off one (up to 0.6% benefit) below specific torque values if the same e-motors are used. Instead of using complex split transmissions, increasing the number of gears in the single transmission is a prominent configuration because it operates the e-motors at a higher efficient point. In the light of these studies, 3-speed single transmission is capable of providing gradeability requirements with the lowest energy consumption and less system complexity.

Evaluation on Braking Stability of Autonomous Vehicles Running along Curved Sections Based on Asphalt Pavement Adhesion Properties

As the main objective influencing factor on the brake safety of autonomous vehicles, pavement texture information is directly related to road surface antiskid performance. However, in the brake system of autonomous vehicles, the influence of road surface adhesion characteristics on braking stability is seldomly considered. To study the braking stability of autonomous vehicles on curved sections under different road conditions, the advanced close-range photogrammetry system was utilized to extract the road surface texture information. Thereafter, the power spectral density (PSD) of the road surface was calculated by MATLAB to obtain the pavement adhesion coefficient curves based on the Persson friction theory model under different road conditions. Considering the pavement adhesion characteristics, the braking model of autonomous vehicles was built in Simulink, and then, the braking performance on curved sections was analyzed with CarSim/Simulink cosimulation. The results indicate that, according to the adhesion coefficient of different asphalt pavement types under different road conditions, the ranking order is open-grade friction course (OGFC) > stone matrix asphalt (SMA) > dense-graded asphalt concrete (AC). In addition, both the maximum lateral offset distances and the maximum lateral forces of the tires decrease as the curve radius gradually increases under different road conditions. It can also be found that there is a relatively uniform vertical forces distribution of the tire when the curve radius is no less than 100 m, and the limit speed of the vehicle varies parabolically with increasing in curve radius. Compared with dry road, the reduction of vehicle braking deceleration is more significant and the yaw rate is greater on wet road. Last but not least, the braking comfort with a radius of 200 m is the best according to the comfort index (CI) in International Standard ISO, in which the comfort level can be sorted into six levels.

Following Consistency of Energy‐Saving Operation for Urban Rail Trains Based on Event Triggering Mechanism

To reduce the traction energy consumption of urban rail trains by regenerating energy, a train traction and braking model was designed based on algebraic graph theory and train dynamics theory and the following consistency model of energy‐saving operation of urban rail trains was constructed based on the conditions of the coordination coefficient and the operating condition conversion of trains. Not only to constantly update the consistency controller and save communication resources but also to optimize the energy‐saving effect, the consistency algorithm of event triggering was used to search for the optimal operating conditions of trains and the energy‐saving operation scheme for multiple trains was established. Taking the train diagram of a subway line in Jinan as an example, the energy‐saving control scheme of four trains was solved by MATLAB simulation. The simulation results show that the model can not only ensure parking accuracy and punctuality but also energy savings effectively; that is, the proportion of the total regenerative energy used by the follower train in the actual energy consumption is increased from 3.32% to 10.76%, and the actual total energy consumption of the train is reduced by 9.23%.

Research on Dynamic Control Method of Loom Spindle Braking System Based on Fuzzy Neural Network

Aiming at the problems of slow response speed of loom electromagnetic braking system and low accuracy of parking angle after braking, resulting in driving marks and thin and dense roads of fabrics, a braking control system based on fuzzy theory and BP neural network is proposed to improve the response speed and control accuracy of the braking system. Firstly, the transmission torque in the braking process of the loom is dynamically analyzed by establishing the mathematical model of electromagnetic braking and the Ansoft electromagnetic finite element model. The causes of braking angle slip are explored, and the driving mechanism of the electromagnetic clutch control circuit based on PWM pulse is analyzed. Based on the control strategy of excitation current, by introducing the fuzzy theory and BP neural network, a fuzzy electromagnetic braking control system based on a neural network is proposed to improve the adaptive ability of the system. At the same time, the IBA-BP algorithm is used to train the neural network to avoid the generation of local optimization and improve the control accuracy of the system. The simulation and experimental results show that compared with PID control and fuzzy PID control, the neural network method based on fuzzy theory has a smaller braking slip angle, and the accuracy of parking angle after braking action is less than 10 °, which improves the control accuracy of loom electromagnetic braking system and weaving quality.

Magnetic and Rotational Evolution of ρ CrB from Asteroseismology with TESS

Abstract During the first half of main-sequence lifetimes, the evolution of rotation and magnetic activity in solar-type stars appears to be strongly coupled. Recent observations suggest that rotation rates evolve much more slowly beyond middle age, while stellar activity continues to decline. We aim to characterize this midlife transition by combining archival stellar activity data from the Mount Wilson Observatory with asteroseismology from the Transiting Exoplanet Survey Satellite (TESS). For two stars on opposite sides of the transition (88 Leo and ρ CrB), we independently assess the mean activity levels and rotation periods previously reported in the literature. For the less active star (ρ CrB), we detect solar-like oscillations from TESS photometry, and we obtain precise stellar properties from asteroseismic modeling. We derive updated X-ray luminosities for both stars to estimate their mass-loss rates, and we use previously published constraints on magnetic morphology to model the evolutionary change in magnetic braking torque. We then attempt to match the observations with rotational evolution models, assuming either standard spin-down or weakened magnetic braking. We conclude that the asteroseismic age of ρ CrB is consistent with the expected evolution of its mean activity level and that weakened braking models can more readily explain its relatively fast rotation rate. Future spectropolarimetric observations across a range of spectral types promise to further characterize the shift in magnetic morphology that apparently drives this midlife transition in solar-type stars.

Computational modeling of driver pre-crash brake response, with and without off-road glances: Parameterization using real-world crashes and near-crashes

When faced with an imminent collision threat, human vehicle drivers respond with braking in a manner which is stereotypical, yet modulated in complex ways by many factors, including the specific traffic situation and past driver eye movements. A computational model capturing these phenomena would have high applied value, for example in virtual vehicle safety testing methods, but existing models are either simplistic or not sufficiently validated. This paper extends an existing quantitative driver model for initiation and modulation of pre-crash brake response, to handle off-road glance behavior. The resulting models are fitted to time-series data from real-world naturalistic rear-end crashes and near-crashes. A stringent parameterization and model selection procedure is presented, based on particle swarm optimization and maximum likelihood estimation. A major contribution of this paper is the resulting first-ever fit of a computational model of human braking to real near-crash and crash behavior data. The model selection results also permit novel conclusions regarding behavior and accident causation: Firstly, the results indicate that drivers have partial visual looming perception during off-road glances; that is, evidence for braking is collected, albeit at a slower pace, while the driver is looking away from the forward roadway. Secondly, the results suggest that an important causation factor in crashes without off-road glances may be a reduced responsiveness to visual looming, possibly associated with cognitive driver state (e.g., drowsiness or erroneous driver expectations). It is also demonstrated that a model parameterized on less-critical data, such as near-crashes, may also accurately reproduce driver behavior in highly critical situations, such as crashes.

Adaptive distributed finite‐time fault‐tolerant controller for cooperative braking of the vehicle platoon

Vehicle platooning can significantly reduce traffic accidents and enhance transportation safety. Among many subsystems and functionalities equipped in a vehicle platoon, cooperative braking is a safety-critical one. Besides, as actuator faults would deteriorate vehicle safety and stability, they pose a great challenge to the platoon, particularly during cooperative braking. To address the aforementioned problems, this study designed an adaptive distributed finite-time fault-tolerant controller for vehicle platoons under cooperative braking condition. First, based on the graph theory and vehicle longitudinal dynamics, the cooperative braking model of a platoon is constructed. Then, the models of hydraulic braking system and regenerative braking system are developed with malfunction analysis. Based on the vehicle's fault model and the representation of the platoon consensus errors, an adaptive finite-time sliding-mode fault tolerant controller is proposed to maintain consensus between vehicle's states during fault occurring. Further, a distributed adaptive law is presented considering the parameter estimation error and sliding-mode surface. The finite-time convergence property and the stability of the proposed controller are demonstrated. Numerical simulations are conducted under different conditions. The simulation results reflected by the control performance and actuators' responses validate the feasibility and effectiveness of the designed control method.

Observer-Based Coordinated Control for Blended Braking System with Actuator Delay

The coordinated control of a blended braking system is always a difficult task. In particular, blended braking control becomes more challenging when the braking actuator has an input time-delay and some states of the braking system cannot be measured. In order to improve the tracking performance, a coordinated control system was designed based on the input time-delay and state observation for a blended braking system comprising a motor braking system and friction braking system. The coordinated control consists of three parts: Sliding mode control, a multi-input single-output observer, and time-delay estimation-based Smith Predictor control. The sliding mode control is used to calculate the total command braking torque according to the desired braking performance and vehicle states. The multi-input single-output observer is used to simultaneously estimate the input time-delay and output braking torque of the friction braking system. With time-delay estimation-based Smith Predictor control, the friction braking system is able to effectively track the command braking torque of the friction braking system. The tracking of command braking torque is realized through the coordinated control of the motor braking system and friction braking system. In order to validate the effectiveness of the proposed approach, numerical simulations on a quarter-vehicle braking model were performed.

INFLUENCE OF VEHICLE SUSPENSION PARAMETERS ON ITS BRAKING PROPERTIES

The paper focuses on the study of the performance of elastic and damping parameters of the car suspension. The problem of arising vibrations of the sprung and unsprung vehicle masses on the braking process is considered. The article presents theoretical models of vehicle braking taking into account the oscillations of the vehicle's sprung masses. The research results will make it possible to establish the relationship between the suspension parameters and the estimated parameters of braking properties, to supplement the "driver - car - road" system, and also to more accurately assess the active safety of vehicles associated with braking dynamics.

Braking of the tractor-semi-trailer set in a rectilinear motion

Because of the increasing share of cargo movement using road transport, the issue of safety hazards related to the movement of trucks and road sets remains an essential element of the overall road safety system. Braking is the primary defensive maneuver in accident situations. The main purpose of this work is to present a simulation method for assessing potential hazards occurring during the braking of an articulated vehicle (tractor-semitrailer combination). A relatively simple, quasistatic mathematical model of road vehicle set braking was presented. Several qualitative and quantitative criteria for safety evaluation were proposed, and a series of exemplary calculations illustrated with time characteristics of the quantities describing the road vehicle set movement. These calculations show that the proposed method may be helpful for the assessment of braking safety depending on the selected factors relating to the operational condition (the way the trailer is loaded, failure of the brake system, road surface condition).

MESA Models with Magnetic Braking

Abstract Two magnetic braking models are implemented in MESA for use in the MIST stellar model grids. Stars less than about 1.3 solar masses are observed to spin down over time through interaction with their magnetized stellar winds (i.e., magnetic braking). This is the basis for gyrochronology and is fundamental to the evolution of lower-mass stars. The detailed physics behind magnetic braking are uncertain, as are 1D stellar evolution models. Thus, we calibrate our models and compare to data from open clusters. Each braking model tested here is capable of reproducing aspects of the data, with important distinctions; neither fully accounts for the observations. The Matt et al. prescription matches the slowly rotating stars observed in open clusters but tends to overestimate the presence of rapidly rotating stars. The Garraffo et al. prescription often produces too much angular momentum loss to accurately match the observed slow sequence for lower-mass stars but reproduces the bimodal nature of slowly and rapidly rotating stars observed in open clusters fairly well. Our models additionally do not reproduce the observed solar lithium depletion, corroborating previous findings that effects other than rotation may be important. We find additional evidence that some level of mass dependency may be missing in these braking models to match the rotation periods observed in clusters older than 1 Gyr better.

Modelling and PID Value Search for Antilock Braking System (ABS) of a Passenger Vehicle


 
 
 This paper presents the methodologies use in determining the PID value of an Antilock Brake System (ABS) of a Malaysian made passenger vehicle. The research work involves experimental work for data acquisitions, development of braking model, parameter tuning for both simulation model parameter and PID values search. A Malaysian made car is equipped with instrumentation used to collect vehicle behaviour during normal and hard braking manoeuvres. The data collected are the vehicle’s stopping distance and longitudinal speed. The data during the normal braking are used to validate a two degree of freedom (2 DOF) of vehicle’s braking model, while the data collected during the hard braking are used to search for the PID value used to control the operation of the ABS system. The developed simulation model of a braking system correlates well with the experimental data and the tuning done on the PID algorithm indicates that the ABS is controlled by the PI system.
 
 

Application of Artificial Neural Networks to Streamline the Process of Adaptive Cruise Control

This article deals with the use of neural networks for estimation of deceleration model parameters for the adaptive cruise control unit. The article describes the basic functionality of adaptive cruise control and creates a mathematical model of braking, which is one of the basic functions of adaptive cruise control. Furthermore, an analysis of the influences acting in the braking process is performed, the most significant of which are used in the design of deceleration prediction for the adaptive cruise control unit using neural networks. Such a connection using artificial neural networks using modern sensors can be another step towards full vehicle autonomy. The advantage of this approach is the original use of neural networks, which refines the determination of the deceleration value of the vehicle in front of a static or dynamic obstacle, while including a number of influences that affect the braking process and thus increase driving safety.

Research on control strategy of electric vehicle under braking state based on fuzzy control

Aiming at how to improve the efficiency of pure electric vehicles in the process of braking energy recovery and security problems, this paper takes brake laws ECER13 curve and ideal braking force distribution curve as constraint conditions, to design a kind of input is braking intensity z, battery SOC charge ratio, output for mechanical brake than kp, electric braking is larger than that of ki fuzzy control strategy, and with the fuzzy control strategy as the core to establish the model of regenerative braking, this model embedded in the ADVISOR of pure electric vehicles in the model, and the simulation under the condition of circulating CYC_UDDS. The results show that under the fuzzy control strategy, the effective recovery rate of regenerative braking energy increases by 5.4%, and the energy utilization rate of the vehicle increases by 1.9%.

Experimental evaluation of braking pad materials used for high-speed elevator

In this paper, an elevator safety gear braking testing rig was developed based on the disc-pad braking model in principles of energy equivalent and speed equivalent to evaluate the braking behavior of short carbon fiber (SCF) reinforced carbon/carbon (C/C) composite and Cu-based powder metallurgy (P/M) material. Note that the braking pressure and the initial braking speed were controlled between 10 MPa to 56 MPa and 3 m/s to 25 m/s respectively in the experiment, which covers the real braking conditions in high-speed elevator. Then friction behaviors of both braking materials were investigated. Especially, the dependence of the coefficient of friction (COF) on the braking pressure and initial braking speed were minutely studied. Interestingly, it was found the COFs increased with the initial braking speed, but decreased with the improved braking pressure. Besides, wear behaviors under different braking conditions for both materials were explored. Results showed the C/C composite pads were crushed at high initial braking speed (V ≧ 14 m/s) in this experiment, but the Cu-based P/M material could suffer higher initial braking speed, which suggested the Cu-based P/M material had more potential to be used as the braking material applied in high-speed elevator or even ultra-high speed elevator compared to C/C composite adopted in this paper.

Modeling and Model Validation of Thermal Behavior of Railway Disc During Single Braking

Abstract The current thermal model of railway disc braking is rather coarse as the heat source is treated to be uniformly distributed. By using a Gaussian mixture function, the thermal behavior of railway disc braking was modeled. Simulations and full-scale rig tests of emergency braking about metro train at 40–100 km/h were conducted. The differences between the maximum temperatures calculated by the Gaussian mixture heat source method (GMHS method) and measurements are 2.56–4.71 °C. The relative errors between the maximum temperatures calculated by the GMHS method and thermal mechanical coupling method (TMC method) are no more than 2.53%. The temperature curves obtained by the GMHS method oscillate about their centerline with the same oscillating period to the TMC method. The time cost by the GMHS method is only 0.91–3.05% of the TMC method at the same conditions. The results indicate that the proposed GMHS method is accurate and efficient, which is more suitable for engineering application.

Formation of millisecond pulsars with helium white dwarfs, ultra-compact X-ray binaries, and gravitational wave sources

ABSTRACT Close-orbit low-mass X-ray binaries (LMXBs), radio binary millisecond pulsars (BMSPs) with extremely low-mass helium white dwarfs (ELM He WDs) and ultra-compact X-ray binaries (UCXBs) are all part of the same evolutionary sequence. It is therefore of uttermost importance to understand how these populations evolve from one specie to another. Moreover, UCXBs are important gravitational wave (GW) sources and can be detected by future space-borne GW observatories. However, the formation and evolutionary link between these three different populations of neutron star (NS) binaries are not fully understood. In particular, a peculiar fine-tuning problem has previously been demonstrated for the formation of these systems. In this investigation, we test a newly suggested magnetic braking prescription and model the formation and evolution of LMXBs. We compute a grid of binary evolution models and present the initial parameter space of the progenitor binaries which successfully evolve all the way to produce UCXBs. We find that the initial orbital period range of LMXBs, which evolve into detached NS + ELM He WD binaries and later UCXBs, becomes significantly wider compared to evolution with a standard magnetic braking prescription, and thus helps to relieve the fine-tuning problem. However, we also find that formation of wide-orbit BMSPs is prohibited for strong versions of this new magnetic braking prescription, which therefore calls for a revision of the prescription. Finally, we present examples of the properties of UCXBs as Galactic GW sources and discuss their detection by the LISA, TianQin, and Taiji observatories.

Comparisons of Empirical Braking Models for Freight Trains Using P4a Distribution Valve

Comparisons of Empirical Braking Models for Freight Trains Using P4a Distribution Valve

Spin Down in Subgiant Stars: Tests of Physics and Main Sequence Braking Models

Spin Down in Subgiant Stars: Tests of Physics and Main Sequence Braking Models