Wheel Slip Control of Vehicle ABS Using Piezoactuator-Based Valve System

<div class="section abstract"><div class="htmlview paragraph">The control of automotive braking systems performance and wheel slip is a challenging problem due to the nonlinear of the braking process, vehicle body dynamics during braking and the tire-road interaction. When the wheel slip is not between the optimal limits during braking, the desired tire-friction force cannot be achieved, which influences the braking distance, the loss in steerability and maneuverability of the vehicle. A simple and at the same time realistic vehicle longitudinal braking model is essential for such challenging problem. In this paper, a new longitudinal rolling/braking lumped-vehicle model that takes vehicle aerodynamic forces in consideration is presented. The proposed model takes the rolling resistance force, the braking force and the aerodynamic lift and drag forces in consideration and investigates their impact on the vehicle longitudinal dynamics especially vehicle braking distance and time. An anti- lock sliding-mode controller is designed to provide wheel slip control during vehicle motion. This type of controller is chosen due to its expected robustness against varying road friction coefficient. The controllers provide an optimal braking torque control which minimize the braking distance by maintaining a desired slip ratio corresponding to the road condition. Based on this optimal braking control method, the impact of the vehicle aerodynamic forces (lift and drag) are investigated and presented.</div></div>

PurposeThe purpose of this study was to utilize driving simulator technology to evaluate braking time and distance, controlling for variables such as hand dominance and single versus both hand use.MethodsThis prospective observational study included healthy volunteers aged 18 and older with no recent upper extremity surgery. Data collected included age, hand dominance, and driving experience. Braking distance and reaction time were measured using Carnetsoft driving simulator software (Groningen, the Netherlands). The participants were instructed to use both hands, their dominant hand, or their non-dominant hand for each trial, accelerating to 60 miles per hour (mph) and decelerating to a stop, with 15 trials per participant, five per hand position. Linear mixed models were used to assess the association between hand use and braking time, accounting for multiple trials.ResultsThirty-three healthy volunteers participated in this study. No statistically significant differences were observed in acceleration reaction time, brake reaction time, stop reaction time, or braking distance across the hand-use conditions, both hands, dominant hand, and non-dominant hand.ConclusionThis study suggests that hand positioning does not significantly impact braking performance in healthy individuals under the conditions tested. This study highlights the potential use of driving simulators for evaluating specific driving abilities, which could inform rehabilitation and clinical assessments for individuals recovering from upper extremity surgeries, particularly as driver-assistive technologies evolve.

Recent experiences have shown that one of the main causes of heavy vehicle crashes is the braking performance. In particular, when having to decelerate in an emergency situation, such as when an unexpected object is in the road. Thus, the capability of a vehicle to come to a safe stop is one of the most important factors in preventing more accidents. Safe braking distance is influenced by many factors, such as brake pedal force, the vehicle’s loading conditions, the travel speed and the road surface conditions. The aim of this study was to analyse the effect of the driver’s brake pedal force on braking distance during an emergency situation, allowed for a wide range of heavy vehicle’s GVW and speed. This study is carried out by using a multi-body dynamics simulation of a Single Unit Truck based on the validated vehicle model. Braking performance was estimated in terms of braking distance on a straight road with a wet surface. The findings from the braking distance simulation suggest a non-linear relationship between brake pedal force and braking distance. Finally, it reveals that, depending on the wheel lock-up situation, braking distance increases with increasing brake pedal force, and that the braking distance on a wet road is significantly affected by both the heavy vehicle’s GVW and speed.

A new cooperative braking control strategy (CBCS) is proposed for a parallel hybrid electric vehicle (HEV) with both a regenerative braking system and an antilock braking system (ABS) to achieve improved braking performance and energy regeneration. The braking system of the vehicle is based on a new method of HEV braking torque distribution that makes the antilock braking system work together with the regenerative braking system harmoniously. In the cooperative braking control strategy, a sliding mode controller (SMC) for ABS is designed to maintain the wheel slip within an optimal range by adjusting the hydraulic braking torque continuously; to reduce the chattering in SMC, a boundary-layer method with moderate tuning of a saturation function is also investigated; based on the wheel slip ratio, battery state of charge (SOC), and the motor speed, a fuzzy logic control strategy (FLC) is applied to adjust the regenerative braking torque dynamically. In order to evaluate the performance of the cooperative braking control strategy, the braking system model of a hybrid electric vehicle is built in MATLAB/SIMULINK. It is found from the simulation that the cooperative braking control strategy suggested in this paper provides satisfactory braking performance, passenger comfort, and high regenerative efficiency.

Dynamic braking performance is well understood in conventional vehicles, but its characteristics in ultra-lightweight, energy-efficient prototype vehicles remain poorly documented, despite their growing role in energy efficiency competitions and urban mobility concepts. This study experimentally investigated stop braking performance under varying vehicle speeds and masses in a low-mass prototype vehicle (V1.0). Tests were conducted at four speed levels (10, 20, 30, and 40 km/h) and two mass configurations (135 kg and 165 kg), with each scenario repeated five times on a flat 100 m track. With an increase in speed from 30 to 40 km/h, the 135-kg configuration showed increases in braking distance of 11.14 m (133%), braking time of 1.92 s (47%), and disc pad temperature of 0.66 °C (1.5%). The 165-kg configuration showed corresponding increases of 14.21 m (152%), 3.02 s (75%), and 1.40 °C (3.3%). Across the full test range, increasing speed from 10 km/h to 40 km/h for the 135-kg configuration increased braking distance from 1.78 m to 19.5 m (+995%) and braking time from 1.63 s to 5.04 s (+209%). Increasing mass from 135 kg to 165 kg at 30 km/h increased braking distance by 0.97 m (11.6%) and braking time by 0.59 s (17.3%). Disc pad temperatures remained within a safe range, rising only from 41.1 °C to 42.5 °C (+3.4%) across the tested speeds. These quantitative findings provide critical data for optimizing braking system design in lightweight, energy-efficient prototypes, ensuring operational safety under various load and speed conditions.

In order to solve the problem of modelling, simulation and optimisation of magnetorheological brake (MR brake) which is a multi-domain coupling system, the braking performance and control parameters optimisation of MR brake were investigated under a quarter-car model. Firstly, based on Modelica/MWorks platform, using multi-domain unified modelling method, a multi-domain unified MR brake model with anti-lock braking system (ABS) was built. Then by using response surface method (RSM), the response surface function to express the relation between braking distance and three control parameters was formulated, and the optimisation problem of control parameters was solved at MWorks. Finally, according to the optimal control parameters and the structure parameters of MR brake designed by our group before, the simulation of the multi-domain unified MR brake model was done to analyse the change regularity of vehicle speed, slip ratio, braking distance, control current, braking time, etc. under the effect of controller. Results show that MR brake with optimal control parameters has a good braking performance and can meet the requirements of GB7258-2012 standard. This lays the foundation of application of MR brake in vehicles.

According to GOST 34434-2018 the brake distance of the freight train is determined by summing up increase of the brake distance at intervals of the braking time. Value of the braking distance will depend on the value of the temporary interval at which the braking time is divided from the begging of the braking to the full stop of the freight train. For this reason it is necessary to choose the temporary interval value at which calculated braking distance of the freight train will correspond to real values. The task was solved by the method of determination of the freight train braking distance for a given range of the intervals values Δti: from (0,07 – 1,2) with a step of 0,01 s and 0,1 s. It is shown that a value of the temporary interval influences the braking distance. The range of interval values was determined (0,07 – 0,1) s, at which braking distances have the maximum value for preserving stability, with this it was determined that beyond the range the values of braking distances were decreased. Integration of the differential equation of the freight train operation ac-cording to the new rules is performed by summing up increases of the braking distance at braking time intervals. It was proposed to determine the braking distance of the freight train according to the temporary interval which is 0,1 s.

Anti-lock braking system (ABS) braking tests with two subcompact passenger cars were performed on dry and wet asphalt, as well as on snow and ice surfaces. The operating conditions of the tyres in terms of wheel slip were evaluated using histograms of the wheel slip data. The results showed different average slip levels for different road surfaces. It was also found that changes in the tyre tread stiffness affected the slip operating range through a modification of the slip value at which the maximum longitudinal force is achieved. Variation of the tyre footprint length through modifications in the inflation pressure affected the slip operating range as well. Differences in the slip distribution between vehicles with different brake controllers were also observed. The changes in slip operating range in turn modified the relative local sliding speeds between the tyre and the road. The results highlight the importance of the ABS controller's ability to adapt to changing slip–force characteristics of tyres and provide estimates of the magnitude of the effects of different tyre and road operating conditions.

Electronic control modules (ECMs) are the most common type of event data recorders being installed on heavy duty trucks. The ECM controls electrical and mechanical systems on the engine while monitoring other vehicle systems. Some of the data collected and stored by ECMs can be of value in accident investigation and analysis even though these reports may not have been originally intended for this purpose. This paper discusses the specifics of data collection from the various ECMs and the reliability of such data when used for the purposes of accident analysis based on testing. A method was developed for applying the ECM data in order to assist in developing an accurate position-time history of the truck. For the study, a tractor-trailer combination equipped with a diesel engine with an ECM was used for multiple straight-line braking runs. A total of 18 different runs were considered, at 30 mph and 60 mph, on both wet and dry asphalt and in both loaded and unloaded conditions. Results suggest that it cannot be assumed that brake status is sampled at the same point as the speed was in the same reporting interval on an incident report. At speeds under 5 mph in the last non-zero reporting interval, the tractor trailer may be stopped even though a speed is shown. A wider range of wheel slip can be expected on an antilock brake system-equipped tractor during maximum braking effort, with the average wheel slip on an unloaded tractor-trailer combination being higher than that of a loaded tractor trailer. The findings also indicate that it is possible to calculate a range of values for the distances traveled to develop a position-time history of a tractor-trailer during a hard brake event.

Vehicle tailgating or simply tailgating is a hazardous driving habit. Tailgating occurs when a vehicle moves very close behind another one while not leaving adequate separation distance in case the vehicle in front stops unexpectedly; this separation distance is technically called “Assured Clear Distance Ahead” (ACDA) or Safe Driving Distance. Advancements in Intelligent Transportation Systems (ITS) and the Internet of Vehicles (IoV) have made it of tremendous significance to have an intelligent approach for connected vehicles to avoid tailgating; this paper proposes a new Internet of Vehicles (IoV) based technique that enables connected vehicles to determine ACDA or Safe Driving Distance and Safe Driving Speed to avoid a forward collision. The technique assumes two cases: In the first case, the vehicle has Autonomous Emergency Braking (AEB) system, while in the second case, the vehicle has no AEB. Safe Driving Distance and Safe Driving Speed are calculated under several variables. Experimental results show that Safe Driving Distance and Safe Driving Speed depend on several parameters such as weight of the vehicle, tires status, length of the vehicle, speed of the vehicle, type of road (snowy asphalt, wet asphalt, or dry asphalt or icy road) and the weather condition (clear or foggy). The study found that the technique is effective in calculating Safe Driving Distance, thereby resulting in forward collision avoidance by connected vehicles and maximizing road utilization by dynamically enforcing the minimum required safe separating gap as a function of the current values of the affecting parameters, including the speed of the surrounding vehicles, the road condition, and the weather condition.

Comparison of Braking Characteristics of Solo Vehicle and Selected Types of Vehicle Combinations

This research presents a rule-based Anti-lock Braking System (ABS) algorithm towards active vehicle safety in Heavy Commercial Road Vehicles (HCRVs). Wheel Slip Regulation (WSR) algorithms, that are constituents of an ABS, are typically either model-based or rule-based. Model-Based Algorithms (MBAs) utilise mathematical models that characterise vehicle dynamics and are intensive in their demand for real-time information. On the other hand, Rule-Based Algorithms (RBAs) operate on set rules with pre-defined thresholds and utilise data from sensors that are typically available on the vehicle. A great deal of advancement has been reported in literature related to MBAs. However, most commercially available RBAs are proprietary in nature and the finer details are seldom revealed. Hence, this work proposes an RBA, which is a combined Slip and Wheel Acceleration Threshold Algorithm (SWATA), including a framework for identifying the importance of thresholds and their magnitudes. SWATA was tested on a Hardware-in-Loop (HiL) setup across varying road and loading conditions, and it provided a maximum of 36% braking distance improvement compared to a case where it was inactive. An adaptive version – ASWATA – is also proposed that can adapt the thresholds according to the particular tyre-road interface. Additionally, a quantitative comparison of the proposed RBA with a Sliding Mode Control (SMC) based MBA, which was developed and tested on the same HiL setup, is presented. It was observed that the performance of the RBA was on par with that of the MBA for most test cases, but with minimal data requirements.

The problem of estimating brake pad wear of cars has been considered, using friction work approximated from the product of longitudinal braking force and distance travelled during braking. The braking force is estimated from a longitudinal dynamics model with inputs from an inertial measurement sensing unit with Kalman filter based sensor fusion, and standard vehicle on-board diagnostics data. Wear coefficients are fitted with Bayesian linear regression on measurements from two series: (I) 16 measurements of previously worn pads over approx. 4,800 km with average wear of approx. -0.5 mm and (II) seven measurements of almost new pads over approx. 1,850 km and approx. -0.15 mm of wear. The approximated friction work appears to correlate well with the wear. The wear coefficients converge quickly after just 4-5 measurements. Coefficients ranging from −4.95⋅10−5mm3/J to −2.08⋅10−5mm3/J are obtained across the cases, when assuming a coefficient of friction μ=0.6 obtained through pin-on-disc (POD) tests. The wear coefficients are validated using POD tests, showing good agreements with the indirectly estimated wear coefficients from vehicle longitudinal dynamics. Data from series (II) is used for prediction of remaining useful life (RUL), where one additional measurement is carried out after 16,552 km. The RUL prediction requires knowledge of the relationship between usage feature and distance travelled. Different approaches are investigated for the predictions: wear based on only distance travelled, linear relationship between usage feature and distance, and three levels of braking severity based on the usage data. Four of the approaches underestimate the distance significantly at around 4,000 to 8,000 km against the actual distance of 16,552 km, while the low severity estimate is closest at 20,460 km, agreeing with expectations due to the driving being primarily on highways.

<div class="section abstract"><div class="htmlview paragraph">The longitudinal dynamics control is an essential task of vehicle dynamics control. In present, it is usually applied by adjusting the slip ratio of driving wheels to achieve satisfactory performances both in stability and accelerating ability. In order to improve its performances, the coordination of different subsystems such as engine, transmission and braking system has to be considered. In addition, the proposed algorithms usually adopt the threshold methods based on less road condition information for simpleness and quick response, which cannot achieve optimal performance on various road conditions.</div><div class="htmlview paragraph">In this paper, an integrated longitudinal vehicle dynamics control algorithm with tire/road friction estimation was proposed. First, a road identification algorithm was designed to estimate tire forces of driving wheels and the friction coefficient by the method of Kalman Filter and Recursive Least Squares (RLS). Then, a rule based integrated control algorithm which coordinate the engine torque control, brake pressure control and transmission shifting control was built to improve the vehicle driving performance.</div><div class="htmlview paragraph">During the longitudinal dynamics control procedure, the transmission shifting control algorithm firstly decided whether the vehicle starting up at the 1st or the 2nd gear based on the road condition. Then, the engine torque control algorithm was applied to adjust the slip ratio of driving wheels. Its process was divided into three phases. In each phase, different control rules with integration of engine torque and brake torque were set by the combined feed forward and feedback methods to meet with requirements of accuracy, rapidity and stability. The brake pressure was determined by method of sliding mode control (SMC) for its rapid adjustment characteristic, in the meanwhile, it was also an important component to be considered in engine torque feedback control.</div><div class="htmlview paragraph">Finally, the algorithm was verified by using Matlab/Simulink and CarSim co-simulation, the results show that the proposed control algorithm could regulate slip ratios of driving wheels fast and accurately, and the vehicle driving performance could be improved effectively.</div></div>

Vehicle platoon is one of the innovations in the automated highway systems, which has the potential to reduce fuel consumption, alleviate traffic congestion and lighten the driver’s burden. How to control the vehicle effectively to ensure the stability of the queue is a challenge. Aiming to overcome the shortcomings of the platoon control method based on traditional sliding mode control, a non-singular terminal sliding mode control method optimized by the extreme learning machine is proposed in this paper. Firstly, the vehicle longitudinal dynamics are derived from the analysis of the forces acting on the vehicle in the longitudinal direction. A constant time headway policy is taken as the spacing policy. The modified non-singular terminal sliding mode control method has outstanding performance, simulation results demonstrate that the following vehicles can rapidly track the trajectory of the leading vehicle in the platoon with less spacing error and guarantee string stability. In this study, several experiments are set up to consider the disturbance and other uncertain practical factors. The performance of the proposed method is superior to the traditional sliding mode control method. Experimental results show that the proposed method can significantly reduce chattering and has good robustness under the circumstances of the disturbance.