In order to adapt the development of vehicle driving automation technology for driving conditions under different levels of automation and based on the independently invented LF automatic pressure regulating valve (LF-APRV) for electronically controlled pneumatic brake systems (ECPBS), the dynamic PWM coupling pressure regulation method is proposed. This method realizes pressure regulation by adjusting the duty cycle of the control signal of the LF-APRV at different stages in the pressure regulation cycle. A co-simulation model was established to verify the feasibility of the method, and a test system was built to verify the correctness of the co-simulation model. Through the test, the pressure regulation performance of dynamic PWM coupling pressure regulation method and conventional on/off pressure regulation method was compared. The results show that the new method can improve the stability of pressure regulation, although the response time increases; under the new method, the overshoot of the pressure rising from 0 to 0.5 MPa was reduced by 69%, and the overshoot of the pressure decreasing from 0.5 MPa to 0.2 MPa was basically 0. Finally, tests and simulations showed that the dynamic PWM coupling pressure regulation method can meet the continuous graded braking requirements of vehicles, and the pressure response has good tracking performance on the target pressure.

In contrast to the traditional pneumatic braking system, the electronic-controlled pneumatic braking system of commercial vehicles is a new system and can remedy the defects of the conventional braking system, such as long response time and low control accuracy. Additionally, it can adapt to the needs and development of autonomous driving. As the key pressure regulating component in electronic-controlled pneumatic braking system of commercial vehicles, automatic pressure regulating valves can quickly and accurately control the braking pressure in real time through an electronic control method. By aiming at improving driving comfort on the premise of ensuring braking security, this paper took the automatic pressure regulating valve as the research object and studied the pressure change rate during the braking process. First, the characteristics of the automatic pressure regulating valve and the concept of the pressure change rate were elaborated. Then, with the volume change of automatic pressure regulating valve in consideration, the mathematical model based on gas dynamics and the association model between pressure change rate and vehicle dynamic model was established in MATLAB/Simulink and analyzed. Next, through the experimental test of a sample product, the mathematical models have been verified. Finally, the key structure parameters affecting the pressure change rate of the automatic pressure regulating valve and the influence law have been identified; therefore, appropriate design advice and theoretical support have been provided to improve driving comfort.

Based on the classification of automated driving by the SAE (Society of Automotive Engineers) and the working principle of the ECPBS (Electronically Controlled Pneumatic Brake system), the requirements and the control modes of the APRV (Automatic Pressure Regulating Valve) were concluded. Four structural configurations for APRV were proposed to meet the requirements of the ECPBS. To study the pressure regulating characteristics of the APRV of different structure configurations, a simulation model was established, and a test bench was built. Through experiments, the correctness and the reliability of the simulation model were verified. The pressure regulation characteristics of the APRV of different structure configurations under different control conditions were revealed, and the suitable levels in the SAE automated driving classifications for automatic pressure regulators of different structure configurations were determined; thus, the theoretical underpinning to improve driving safety and develop automated driving was provided.

The paper evaluates the braking ride comfort of commercial vehicle through total weighted acceleration root mean square and Derivative of acceleration (Jerk). Based on the vehicle dynamics model, tire model and braking implement model, the commercial vehicle braking pressure, braking pressure change rate and braking ride comfort of correlation model is established. The commercial vehicle dynamics simulation model for braking pressure change rate is established by using MATLAB/Simulink software. The simulation comparison of MATLAB/Simulink and IPG/TruckMaker verify the correctness and effectiveness of the correlation model. Taking the effect of single and double braking chamber pressure change rate as an example. The effect of the unusual change of pressure change rate of the front and rear axle single braking chamber and the coaxial and ipsilateral braking chamber on the commercial vehicle braking ride comfort is analyzed by comparativing. Some theoretical basis for commercial vehicle in intelligent braking and automatic driving is provided.

Deep learning networks have shown excellent performance in surface defect recognition and classification of certain industrial products. However, most industrial product defect samples are scarce and have a wide variety of defect types, making methods that require a large number of defect samples for training unsuitable. In this paper, a lightweight surface defect detection network (LRN-L) based on texture complexity analysis is proposed. Only a large number of defect-free samples, which can be easily obtained, are needed to detect defects. LRN-L includes two stages: texture reconstruction stage and defect localization stage. In the texture reconstruction phase, a lightweight reconstruction network (LRN) based on convolutional autoencoder is designed, which can reconstruct defect-free texture images; a loss function combining structural loss and L1 loss is proposed to improve the detection effect; we built a calculation model for image complexity, calculated the texture complexity for texture samples, and divided textures into three levels based on complexity. In the defect localization stage, the residual between the reconstructed image and the original image is taken as the possible region of the defect, and the defect localization is realized via a segmentation algorithm. In this paper, the network structure, loss function, texture complexity and other factors of LRN-L are analyzed in detail and compared with other similar algorithms on multiple texture datasets. The results show that LRN-L has strong robustness, accuracy and generalization ability, and is more suitable for industrial online detection.

With the relentless progression in autonomous driving and chassis control technologies, the safety requirements for commercial vehicle braking systems have intensified. Ensuring the safety and reliability of these systems during operation has become crucial. This study focuses on the automatic pressure regulating in commercial vehicles. To meet the evolving demands and safety standards of autonomous driving and chassis control technologies, this study incorporates theoretical methodologies including relevant standards and fault tree analysis. The research systematically categorizes and assesses failure modes of the automatic regulating valve, proposing a concept and framework for ensuring high redundancy safety. Validating the correctness and feasibility of the high redundancy safety scheme for the automatic regulating valve was accomplished through fault injection methods. Results indicate that the high redundancy safety scheme effectively diagnoses and manages faults, thereby guaranteeing the valve’s pressure regulation capability even under fault conditions. This approach provides invaluable insights into the safety and reliability design for commercial vehicles and their components, offering essential theoretical underpinnings for the progression of autonomous driving and chassis control technologies in commercial vehicles.