Heavy goods vehicles exhibit poor braking performance in emergency situations when compared to other vehicles. Part of the problem is caused by sluggish pneumatic brake actuators, which limit the control bandwidth of their antilock braking systems. In addition, heuristic control algorithms are used that do not achieve the maximum braking force throughout the stop. In this article, a novel braking system is introduced for pneumatically braked heavy goods vehicles. The conventional brake actuators are improved by placing high-bandwidth, binary-actuated valves directly on the brake chambers. A made-for-purpose valve is described. It achieves a switching delay of 3–4 ms in tests, which is an order of magnitude faster than solenoids in conventional anti-lock braking systems. The heuristic braking control algorithms are replaced with a wheel slip regulator based on sliding mode control. The combined actuator and slip controller are shown to reduce stopping distances on smooth and rough, high friction (μ = 0.9) surfaces by 10% and 27% respectively in hardware-in-the-loop tests compared with conventional ABS. On smooth and rough, low friction (μ = 0.2) surfaces, stopping distances are reduced by 23% and 25%, respectively. Moreover, the overall air reservoir size required on a heavy goods vehicle is governed by its air usage during an anti-lock braking stop on a low friction, smooth surface. The 37% reduction in air usage observed in hardware-in-the-loop tests on this surface therefore represents the potential reduction in reservoir size that could be achieved by the new system.

Designing and testing an advanced pneumatic braking system for heavy vehicles

The in-vehicular networked control system is among the most critical embedded processes The controller area network (CAN) has prevailed intra-vehicle communication for decades Meanwhile, requirements of future transportation systems are expected to emphasise the in-vehicle communication complexity, which endangers the reliability/safety of the intelligent navigation At first, this study reviews the recent solutions proposed to overcome the CAN expanding complexity Challenges that tomorrow's intelligent vehicles may raise for CAN reliability are investigated The comprehensive coverage of current research efforts to remove the impact of these challenges is presented Further, the in-vehicle system reliability of future automated vehicles is also related to the fault diagnosis performances Hence, different classes of system-level diagnosis strategies are compared relatively to the requirements of automotive embedded networks Furthermore, to thoroughly cover CAN reliability engineering issues, focus is given to the automotive validation techniques The hardware in the loop, real-time analysis and computer-aided-design tools intervene in various phases along the in-vehicular network life cycle Parameters that stand behind the efficiency and accuracy of these techniques in validating the new generation of vehicles are analysed The authors finally draw some deductive predictions about the future directions related to the reliability of the intelligent transportation system in-vehicular communication

https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-its.2019.0565

Controller area network reliability: overview of design challenges and safety related perspectives of future transportation systems

Because of the nonlinear feature of tire force, the anti-lock braking system (ABS) research based on wheel slip control (WSC) is widely used even without the measured wheel slip and road friction. Combined with the WSC technology, the four-wheel ABS with the fuzzy sliding mode (FSM) control method is introduced in this paper. Unlike most single-wheel independent ABS, this design has more advantages when braking under the unusual road conditions, such as the transition of road conditions, the split-road conditions between the left-side wheels and the right-side wheels, even the extreme situation in which road conditions of each wheel are different, as it has the smooth-braking judgment module that is designed for wheel-to-wheel control. Besides, based on the nonlinear function of the tire-road interaction (TRI) model, the designed road condition detection module provides characteristics of the braking road that are required in the ABS operation. The model of vehicle and tire is established in Simulink by using parameters of a vehicle: BYD F0. The effectiveness of the proposed four-wheel ABS is validated through the combined use of MATLAB and RT-lab and via substantial simulations and RT-LAB co-simulations.

Four-Wheel Anti-Lock Braking System With Robust Adaptation Under Complex Road Conditions

The road adhesion coefficient is a key factor influencing automatic emergency braking (AEB) and anti-lock braking system (ABS) safety control of trucks. With the fading factor introduced, and the covariance gain adjusted in real time, the strong tracking unscented Kalman filter (STUKF) algorithm is modified to estimate the road adhesion coefficient more accurately. Composed of an ABS fuzzy sliding mode controller (SMC) and an AEB controller, an AEB/ABS coordinated control strategy with an adhesion coefficient estimation is designed for a three-axle heavy vehicle. The control effects are verified through experiments on various road conditions based on a hardware-in-loop test platform. The test results show that the proposed control strategy has a better braking efficiency than the traditional AEB/ABS and AEB control strategy without adhesion coefficient estimation and can decrease braking distance by 8.4% and braking time by 5.9%, which is beneficial to the vehicle longitudinal safety. 

Automatic emergency braking/anti‐lock braking system coordinated control with road adhesion coefficient estimation for heavy vehicle

To improve the accuracy and actual road equivalence of vehicle performance testing using test benches, a double-drum test bench that meets the test requirements of vehicle control system prototypes and in-use vehicles was designed. Dynamic models of the single-wheel test bench and the vehicle test bench were established, and mechanisms were theoretically analyzed for single-wheel variable adhesion and vehicle load transfer for equivalent testing using the variable placement angle. The mechanism of electromechanical inertia compensation was studied to realize stepless simulation of vehicle inertia and simulate dynamic load while braking. The simulation model of the vehicle test bench system was established based on MATLAB/Simulink. Simulations were carried out to verify the anti-lock braking system (ABS) performance test functionality of the test bench under high adhesion, bisectional, and low adhesion conditions. Referring to the simulation conditions, ABS tests under actual test bench and road conditions were carried out. Results demonstrated that the mechanism of variable load transfer simulation by electromechanical inertia compensation improves the equivalent accuracy compared to that of its road test equivalent, verifying the feasibility of the simulation mechanism. This study could help further improve the accuracy and reduce the cost of vehicle performance testing, thus greatly benefitting the vehicle development and testing industry.

Double-Drum Test Bench for Variable Load Transfer Simulation by Electromechanical Inertia Compensation.

A direct yaw moment controller/anti-lock braking system (DYC/ABS) coordinated cornering brake control scheme is proposed for three-axle vehicles to improve the handling performance while shortening the brake distance. A proportional–integral method is designed in DYC control. The cornering stiffness of the two-degrees of freedom vehicle model is fitted in real time. The Dugoff tire model is used to establish the relationship between the yaw moment and wheel slip ratio; an optimal allocation method is proposed to allocate the force requirements to each tire. To verify the effect, vehicle responses under various speeds and turning radii are analysed with DYC/ABS coordinated control, ABS control, and no control based on co-simulation of TruckSim and MATLAB/Simulink. According to the chattering caused by sliding mode control, two sliding mode controllers using saturation function and modified exponential reaching law are, respectively, designed to obtain the braking moment in ABS control. A pneumatic braking hardware-in-loop (HIL) test system is developed; the effectiveness of the strategy is verified by experiments. The results show that the coordinated control can reduce lateral acceleration, brake distance, and brake time when the vehicle runs under cornering brake; thus has an excellent effect on balancing the handling stability and braking safety.

https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/iet-its.2018.5406

Research on a coordinated cornering brake control of three‐axle heavy vehicles based on hardware‐in‐loop test

This study proposes a coordinated control strategy to improve the safety, handling stability, riding comfort of the heavy-duty vehicle. The strategy is based on the coordination of direct yaw moment control (DYC) and anti-lock braking system. The model predictive control (MPC) method for DYC considering sideslip angle and yaw rate is presented. The sideslip angle and yaw rate are adopted to be the indicators for handling stability, constraints considering the maximal force of actuator are implemented in the MPC. The control scheme is examined on a non-linear three-directional coupled model in the environment of MATLAB/Simulink and TruckSim. The relationship between yaw moment and wheel slip ratio is obtained by the Dugoff model, which can be easily implemented in hardware-in-loop (HIL) tests. HIL tests are conducted to verify the improvement introduced by the coordinated control with MPC. Vehicle responses under various speeds and turning radii are analysed by comparison of proportional–integral control and MPC. The results specify that the proposed coordinated control scheme with MPC could obtain better lateral stability.

https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-its.2019.0712

Model predictive coordinated control of heavy-duty vehicle using non-linear three-directional coupled model

Trajectory prediction for traffic participants is a critical task for autonomous vehicles. The long-term trajectory prediction is challenging due to limited data and the dynamic characteristics of traffic participants. This paper presents an innovative interactive multiple model algorithm considering inter-vehicle interaction and driving behavior for the traffic participant's short-term and long-term trajectory prediction. The field experiment is conducted to acquire the human driver data, which is then preprocessed and analyzed with statistical methods. The clustering result of the critical gap is used to include the interactions between them, on which the gap satisfaction probability function is designed and aimed at describing the satisfaction probability of the current lane. The driving behavior is another promising candidate to improve the long-term prediction accuracy. The clustering results of the lane change duration are used to establish the lane changing models considering the driving behavior, the driving behavior probability function is designed based on the probability of each model. Then the two functions are incorporated into the adaptive transition probability matrix, where the quantitative probabilistic relations between the gap satisfaction probability and the driving behavior probability are established. The adaptive transition probability matrix is then used in the interactive multiple model algorithm. Based on the improved interactive multiple model, the personalized trajectory prediction for the traffic participant is obtained. The effectiveness of the framework is validated by simulation and field experiment.

Junwu Zhao

Papers

Research on a coordinated cornering brake control of three‐axle heavy vehicles based on hardware‐in‐loop test

Model predictive coordinated control of heavy-duty vehicle using non-linear three-directional coupled model

Interaction-Aware Personalized Trajectory Prediction for Traffic Participant Based on Interactive Multiple Model