The braking stability has significant importance for commercial vehicles, especially tractor-semitrailer. However, the brake lag of air brake system brings serious safety risk to the vehicle. To improve the braking stability of tractor-semitrailer, an optimized air brake system is proposed. Using characteristic of the fast exhaust response of spring brake cylinder of composite brake chamber, a normally open solenoid valve and a normally closed solenoid valve are connected with the spring brake cylinder of composite brake chamber of semitrailer to control the spring brake force, which responds more quickly than service brake force. A strategy is proposed to control the difference between the actual braking torque of the semitrailer brake and the target braking torque and is simulated based on AMESim and SIMULINK. An experiment is made to verify the effectiveness of the optimized system. The simulation shows that the improved scheme reduces the response time of semitrailer brake system by 0.19 s, and effectively restrains the lateral movement of the vehicle downhill braking and improves the stability of the braking direction of the vehicle. And the experiment indicates that the brake of semitrailer responds earlier than tractor, which means the brake lag is improved significantly.

Accurate driving cycles are key for effectively evaluating electric vehicle performance. The K-means algorithm is widely used to construct driving cycles; however, this algorithm is sensitive to outliers, and determining the K value is difficult. In this paper, a novel driving cycle construction method based on principal component analysis and hierarchical clustering is proposed. Real road vehicle data were collected, denoised, and divided into vehicle microtrip data. The eigenvalues of the microtrips were extracted, and their dimensions were reduced through principal component analysis. Hierarchical clustering was then performed to classify the microtrips, and a representative set of microtrips was randomly selected to construct the driving cycle. The constructed driving cycle was verified and compared with a driving cycle constructed using K-means clustering and the New European Driving Cycle. The average relative eigenvalue error, maximum speed acceleration probability distribution difference rate, average cycle error, and simulated relative power consumption error per 100 km between the hierarchical driving cycle and the real road data were superior to those of the K-means driving cycle, which indicated the effectiveness of the proposed method. Though the methodology proposed in this paper has not been verified in other regions, it provided a certain reference value for other research of the developing driving cycle.

With the development of electric vehicles, more attention has been paid to the role of the driving cycle in vehicle performance testing. At present, the K-means algorithm is often used in the development of driving cycles. However, it is sensitive to the outlier points and also difficult to determine the K value. To solve this problem, the hierarchical cluster method is applied in this study. First, the real-world driving data are collected and denoised through wavelet domain denoising. Then, the data are divided into micro-trips and the characteristic parameters are extracted. The hierarchical cluster method is adopted to classify the micro-trips into different categories. An appropriate number of micro-trips are selected from each group in proportion to each category to assemble the driving cycle. Finally, both the economic simulation and the statistical analysis prove the accuracy of the generated driving cycle and the feasibility of the development method proposed in this paper.

Brake time delay, which is a major shortcoming of air brake systems, may lead to precarious situations. In this study, the structure of an air brake system of a tractor–semitrailer was optimized by adding a shuttle valve and a two-position-three-port electromagnetic valve between the control pipeline and the charging pipeline downstream of the trailer control valve. The new electronically controlled structure clearly ensures that the semitrailer brakes faster, as validated by a simulation, bench test, and real-vehicle test. The simulation results reveal considerable improvements in the braking time, braking distance, longitudinal kinetic energy, lateral kinetic energy, and β phase plane. The bench test indicates that in the proposed structure, the average response time of service brake cylinders of the first and third axles of the semitrailer are 0.12 and 0.17 s, respectively. In addition, the real-vehicle test indicated that the service brake cylinders of the first and third axles responded 0.12 and 0.18 s earlier than those in the original system, respectively.

The development of intelligent tire technology has attracted increasing attention from researchers to build different tire models to obtain the state parameters of the tire and to try to correlate these parameters with sensors. To address the challenge of characterizing the evolution of wear in traditional tire mechanics models, this study proposes a physical model that incorporates tire wear. The model is an improvement over the traditional flexible ring model, incorporating brush theory. By establishing the mechanical equilibrium equation of the tread unit, a tire dynamic equation incorporating wear state variables is constructed. The strain–displacement relationship is analyzed to determine the correlation between the strain field and the displacement field. The results show that the strain signals obtained from the physical model and the finite element model maintain a high degree of consistency, validating the reliability and effectiveness of the proposed model. In addition, the correlation between the tire wear and strain signal characteristics was successfully revealed by comparing the physical model and the finite element model. The proposed model provides a theoretical foundation for future research on intelligent tires, as well as a basis for related studies on tire wear, tire lifespan, and tire mechanical properties.