Braking Control Research Articles

Bipolar modulation of brushless DC motor with integrated control of motoring and regenerative braking

Bipolar modulation of brushless DC motor with integrated control of motoring and regenerative braking

Detection and Mitigation of Sensor and CAN Bus Attacks in Vehicle Anti-Lock Braking Systems

For a modern vehicle, if the sensor in a vehicle anti-lock braking system (ABS) or controller area network (CAN) bus is attacked during a brake process, the vehicle will lose driving direction control and the driver’s life will be highly threatened. However, current methods for detecting attacks are not sufficiently accurate, and no method can provide attack mitigation. To ensure vehicle ABS security, we propose an attack detection method to accurately detect both sensor attack (SA) and CAN bus attack in a vehicle ABS, and an attack mitigation strategy to mitigate their negative effects on the vehicle ABS. In our attack detection method, we build a vehicle state space equation that considers the real-time road friction coefficient to predict vehicle states (i.e., wheel speed and longitudinal brake force) with their previous values. Based on sets of historical measured vehicle states, we develop a search algorithm to find out attack changes (vehicle state changes because of attack) by minimizing errors between the predicted vehicle states and the measured vehicle states. In our attack mitigation strategy, attack changes are subtracted from the measured vehicle states to generate correct vehicle states for a vehicle ABS. We conducted the first real SA experiments to show how a magnet affects sensor readings. Our simulation results demonstrate that our attack detection method can detect SA and CAN bus attack more accurately compared with existing methods, and also that our attack mitigation strategy almost eliminates the attack’s effects on a vehicle ABS.

A Cyborg Insect Reveals a Function of a Muscle in Free Flight

While engineers put lots of effort, resources, and time in building insect scale micro aerial vehicles (MAVs) that fly like insects, insects themselves are the real masters of flight. What if we would use living insect as platform for MAV instead? Here, we reported a flight control via electrical stimulation of a flight muscle of an insect-computer hybrid robot, which is the interface of a mountable wireless backpack controller and a living beetle. The beetle uses indirect flight muscles to drive wing flapping and three major direct flight muscles (basalar, subalar, and third axilliary (3Ax) muscles) to control the kinematics of the wings for flight maneuver. While turning control was already achieved by stimulating basalar and 3Ax muscles, electrical stimulation of subalar muscles resulted in braking and elevation control in flight. We also demonstrated around 20 degrees of contralateral yaw and roll by stimulating individual subalar muscle. Stimulating both subalar muscles lead to an increase of 20 degrees in pitch and decelerate the flight by 1.5 m/s2 as well as an induce in elevation of 2 m/s2.

Research on service braking control strategy for heavy-duty truck on long downhill based on genetic algorithm

Research on service braking control strategy for heavy-duty truck on long downhill based on genetic algorithm

Composite braking control strategy of a novel electromechanical-hydraulic coupling driving electric vehicle

Composite braking control strategy of a novel electromechanical-hydraulic coupling driving electric vehicle

Research on service braking control strategy for heavy-duty truck on long downhill based on genetic algorithm

When heavy-duty trucks operate on a long downhill section of expressways, the drum temperature often experiences a sharp rise due to the frequent work of the service braking. Hence, how to operate the brake pedal to avoid heat fading becomes an important issue. To resolve this problem, service braking control strategy based on the genetic algorithm is proposed. It is found that the pedal force and the speed range have a significant effect on the temperature rise, the braking frequency, and the cumulative working time. Therefore, jointly considering the constancy of braking efficiency, the driver fatigue degree and driving safety, a novel control strategy is proposed to optimise the brake pedal force, the desired speed range and the average speed of the heavy-duty truck. The results reveal that the proposed control strategy can effectively reduce the temperature rise, the frequency of brake and the driving intensity for driver.

Research on parallel braking control of distributed drive electric vehicles

For distributed drive electric vehicles, according to the actual needs of the composite braking system of electric vehicles, the braking safety is the mainstay, and the energy recovery is carried out at the same time, and the distributed parallel braking control strategy is proposed. The strategy adopts a hierarchical control structure, with the upper control aiming at brake safety and the lower control aiming at brake energy recovery. The designed parallel brake control policy takes into account the distribution of braking force in the front and rear axles, as well as constraints such as braking strength, battery SOC value, and motor. Finally, a simulation analysis is carried out to verify the braking efficiency and energy recovery effect.

Active trailer braking control for car-trailer combination based on multi-objective fuzzy algorithm

Active trailer braking control for car-trailer combination based on multi-objective fuzzy algorithm

Active trailer braking control for car-trailer combination based on multi-objective fuzzy algorithm

Active trailer braking control for car-trailer combination based on multi-objective fuzzy algorithm

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.

Stability control of a vehicle with tire blowout based on active steering and differential braking

The vehicle with tire blowout will have dangerous working conditions such as yaw and tail flick, which will seriously endanger the safety of driving. A tire blowout model was established based on the UniTire model and the change of tire blowout mechanical characteristics. A Carsim/ Simulink joint simulation platform was built to study the dynamic response of the vehicle after the front wheel tire blowout under curve driving. A combined control strategy of outer-loop trajectory control and inner-loop differential braking control based on sliding mode fuzzy control algorithms and fuzzy PID control algorithms was proposed to ensure that the vehicle can still follow the original trajectory stably after tire blowout. The results show that the tire blowout of the front wheel on the same side as the turning direction has a great influence on the instability and yaw of the vehicle, and the designed control strategy can effectively control the running track of the vehicle with tire blowout and the vehicle stability.

Intelligent Detection Method for Roll Stability of Unmanned Vehicle based on Fuzzy Control

When the unmanned vehicle is disturbed by the outside world or carries out dangerous actions such as steering and continuous lane changing, the yaw stability of the unmanned vehicle decreases and the dangerous situation such as rollover is easy to occur. In this paper, the intelligent detection method for roll stability of unmanned vehicles based on fuzzy control is studied. The roll control system of the unmanned vehicle based on a double-layer control strategy is designed. The roll stability of the unmanned vehicle is controlled by an upper-layer fuzzy controller and lower-layer differential braking control. The dynamic model and tire model are built in MATLAB/Simulink to restore the running characteristics of unmanned vehicles. Based on the operation characteristics, the roll stability of the unmanned vehicle’s roll control system based on fuzzy control is tested from three aspects: steady-state response, roll stability and dynamic stability coefficient. The experimental results show that the transverse load’s transfer rate of the proposed method is reduced by more than 0.2% compared with the contrast method, the yaw angular velocity, centroid’s roll angle and roll angle measured under the two working conditions are closer to the actual values, which shows that the method has better control effect and detection accuracy.

Active Braking for Soft Landing on the Surface of Mars: Part 2: Braking Control

Active Braking for Soft Landing on the Surface of Mars: Part 2: Braking Control

Experimental investigation of supercapacitor based regenerative energy storage for a fuel cell vehicle equipped with an alternator

Recently, researchers have devoted more attention to supercapacitors (SCs) to integrate with batteries in energy storage systems (ESSs) for vehicle applications. In this study, we attempted to characterize the use of SCs in the ESS for a PEM fuel cell vehicle equipped with an alternator to maximize the performance of regenerative braking. We applied lithium-ion batteries (LIBs) and SCs as energy storage devices to examine their effect on ESS. Then we used a hysteresis brake to apply controllable braking force on the flywheel to form hybrid braking (HB) and made efforts to study its behavior to suggest a braking control strategy. We also ran the whole system over the rotational speed to cover the range of driving speed. At last, we sized the SCs for the most commonly used fuel cell electric vehicle (FCEV) in Korea, i.e., Hyundai NEXO, based on the results obtained from the above study by alternator efficiencies.

A novel electro-hydraulic compound braking system coordinated control strategy for a four-wheel-drive pure electric vehicle driven by dual motors

The electro-hydraulic compound braking system of a pure electric vehicle can recover the energy released during braking and store it in the battery through the motor, thereby improving the vehicle's energy utilization efficiency. However, how to coordinate the control of motor braking and hydraulic braking during vehicle braking to ensure the optimal balance of vehicle braking safety and energy recovery efficiency is still an urgent problem to be solved in the field of new energy vehicles. This paper takes the four-wheel-drive pure electric vehicle driven by dual motors as the research object and proposes a coordinated control strategy for an electro-hydraulic hybrid brake system with efficient energy recovery. The proposed coordinated control strategy is composed of two parts: the braking force distribution control strategy that comprehensively considers braking safety and charging efficiency optimization and the coordinated control strategy of regenerative braking system (RBS) and anti-lock braking system (ABS) based on model predictive control. The results show that the proposed coordinated control strategy has superior braking performance, and improves the energy recovery efficiency by more than 22.76% compared with the conventional coordinated control strategy, proving the effectiveness of efficient energy recovery under the premise of ensuring stability and safety.

Prescribed Performance Active Braking Control with Reference Adaptation for High-Speed Trains

Active braking control systems are vital for the safety of high-speed trains by leading the train operation at its maximum adhesion state. The train adhesion is a nonlinear function of the slip ratio and varies with the uncertain wheel-rail contact conditions. A nonlinear active braking control with rapid and accurate tracking performance is highly required for train braking systems. This paper proposes a novel prescribed performance active braking control with reference adaptation to obtain the maximum adhesion force. The developed feedback linearization controller employs a prescribed performance function that specifies the convergence rate, steady-state error, and maximum overshoot to ensure the transient and steady-state control performance. Furthermore, in the designed control approach, a continuous-time unscented Kalman filter is introduced to estimate the uncertainty of wheel-rail adhesion. The estimation is utilized to represent uncertainty and compensate for the prescribed performance control law. Finally, based on the estimated wheel-rail adhesion, an on-line optimal slip ratio generation algorithm is proposed for the adaptation of the reference wheel slip. The stability of the system is provided, and experiment results validate the effectiveness of the proposed method.

Safe distance prediction for braking control of bridge cranes considering anti‐swing

Cranes are widely deployed for lifting and moving heavy objects in dynamic environments with human coexistence. Suddenly appeared workers, vehicles, and robots can affect the safety of the cranes. To avoid possible collisions, the cranes must have prediction ability to know how dangerous the situation is. In this paper, we address the safety issues of bridge cranes based on its online physical states and control model. Due to the swing of the payload, the safe braking distance cannot be a constant value. Therefore, we here propose a model prediction control (MPC)-based anti-swing method for non-zero initial states, where a new reference trajectory and a new cost function for optimization are proposed, such that the proposed MPC method can control the crane to follow the proposed reference trajectory and achieve a stable stop state with anti-swing. Furthermore, an offline learning mechanism is introduced to learn a statistical model between the velocity of the crane and the safe braking distance achieved by using the proposed MPC braking control method. In this way, we can predict how far the crane would require to safely stop without swing based on its current velocity, which is the safe distance prediction to evaluate the dangerous level of the dynamic obstacle. Experiments using both a simulated crane and a real crane demonstrate that the proposed safe braking distance prediction method is effective for safe braking control of the bridge cranes.

Co-simulation model coupling of flexible rope hoisting system and hydraulic braking system for a mine hoist

The hoist is an important equipment in the mine pit. Since the containers are lifted or lowered with flexible steel wire ropes, there are shocks and vibrations during operation, especially in the emergency braking stage, the shocks and vibration will be more severe. Mine hoist is a complex system; therefore, it is difficult to obtain all its dynamics information only by investigating the flexible hoisting subsystem or hydraulic brake subsystem. Therefore, it is very necessary to establish an accurate model to predict these characteristics of the hoist, this will provide useful tools for hoist design and maintenance. Therefore, a joint modeling methodology is proposed and implemented in this paper. A hoisting system model considering the non-linear factors such as contact characteristics and flexibility was established in RecurDyn. The hydraulic braking system model and control system model were established in AMESim, and the co-simulation model was constructed by the interface module. In this co-simulation model, not only the flexible hoisting subsystem and hydraulic brake subsystem are included, but also the coupling effect of subsystems is considered. Finally, taking the lifting condition as an example, execute emergency braking research on the hoisting system under experiment, mathematical model, and co-simulation model, respectively. Comparing the co-simulation model with the mathematical dynamics model, and the experimental test results, research indicates that the joint simulation model of coupled hoisting system and hydraulic braking system can effectively reflect the dynamic characteristics of the actual hoisting system. It provides an effective tool for hoist design, optimization, performance analysis, and operating condition simulation. In addition, the methods and techniques used in the co-simulation modeling procedure are portable. Therefore, the paper is of significance for the mine hoist.

Automatic target adjusting braking of a shunting stock with an adaptive control law

The article deals with the problem of automation of target adjusting braking of a shunting stock. It is proposed to build it on the basis of an adaptive control algorithm capable of functioning under the current uncertainty of the parameters of the control object. It is based on a scheme with a current parametric identification assigned by an implicit reference model and using “simplified adaptivity conditions”. For the synthesis of the control, the approach implemented in a standard locomotive system for automatic braking control to maintain the target speed of movement depending on the distance to the target point is used. The results of simulation modelling are presented.

Regen-braking-capable ZF Brake Control System for Electric Vehicles by VW

Regen-braking-capable ZF Brake Control System for Electric Vehicles by VW