International Journal of Automotive Technology最新文献

Based on the self-developed hydraulic variable valve mechanism of four-cylinder engine, this paper proposes a variable displacement valve control strategy based on the VOC-CDA mode of electro-hydraulic. The variation rules of in-cylinder pressure, oxygen mass fraction in exhaust gas, torque fluctuation and other parameters in the process of cylinder deactivation cycle and working mode conversion are analyzed, and the control parameters of inlet and exhaust valves at the best cylinder deactivation time are optimized. The energy saving mechanism of variable displacement technology is analyzed from the aspects of indicated thermal efficiency, mechanical efficiency and effective thermal efficiency. Based on the optimal intake and exhaust valve closing time, the engine can improve the fuel economy by 8.7% at medium and small loads. It provides a certain design reference for the development of variable displacement engine based on hydraulic variable valve mechanism.

Diesel engine NOx is the main harmful emission of motor vehicles. Accurate measurement of NOx emission is beneficial to the control of SCR (selective catalytic reduction) urea injection so as to reduce emissions. At present, NOx emission value is mainly obtained by NOx sensor or MAP calibration and these two methods have limitations in practical applications. In this study, PCA (principal component analysis) is used to reduce the dimension of diesel engine operating data of WHTC (the world harmonized transient cycle) bench test, which can make data visualized in three-dimensional space. Then transient diesel engine NOx prediction model is built based on LSTM, and GWO (grey wolf optimizer) is used to optimize the parameters of LSTM. The results showed that R² (determination coefficients) of the GWO-LSTM is 0.987; In the untrained data set, MAE (mean absolute error), MAPE (mean absolute percentage error) and RMSE (root mean square error) are 18.75 × 10^–6, 3.23% and 20.29 × 10^–6, respectively. The same accuracy index are be compared with PSO-BP and static map. It is proved that the GWO-LSTM model can accurately predict the transient NOx emission of diesel engine, and also has good generalization ability with reliability, which provides a reference for software instead of hardware to control diesel engine emission.

Numerous studies are currently focused on improving the performance and efficiency of electric vehicles (EVs). This research aims to evaluate the necessity for a practical testing methodology to simulate real-world driving scenarios by comparing the driving range measured on a chassis dynamometer with the ranges observed under various actual driving conditions. Tests were conducted on the chassis dynamometer using the multi-cycle test (MCT) mode, employing the urban dynamometer driving schedule (UDDS) and the highway fuel economy driving test (HWFET). Subsequently, we assessed the energy efficiency of three routes compliant with the real-driving emissions-light duty vehicles (RDE-LDV) regulations under real-world driving conditions. Our findings revealed disparities in energy efficiency ranging from 10.8 to 22.9% when driving on the same route and up to 29.3% when driving on different routes. This study highlights the importance of tailoring information provision, such as certification tests, to each country’s environmental context.

Accelerating performance and braking performance are the core performance of a vehicle, and tire load analysis is a prerequisite for performance studying. A calculation and correction method of dynamic tire loads is proposed in this paper. First, the numerical and experimental models of tire dynamic load identification are established, by measuring the acceleration signals at different positions of the steering knuckle arm, the tire deformation in three directions is inversely calculated. Second, the longitudinal force, lateral force and vertical force of the tire are estimated according to the tire stiffness and deformation. Finally, the tire loads are corrected by data filtering and tire stiffness adjustment. The results show that the average agreement between the calculated load and the test load is more than 90%. The calculation and correction method can provide a theoretical basis and reference for analyzing the dynamic change characteristics of tire load.

Although full automation has not yet been achieved, automated vehicles are a valid research area. Not only would automated vehicles provide ultimate driver convenience, but they would maximize energy efficiency by eliminating undesired human driving behaviors and optimally controlling the powertrain. From the perspective of control related to energy saving, speed profile optimization is important for improving system efficiency and satisfying passenger demands. This study employs Dynamic Programming (DP) to solve the constrained optimal problem for travel time, distance, and speed limit by exploring all possible control options. The solutions obtained by DP demonstrate consistent control patterns combining four control modes—acceleration, cruising, coasting, and braking, with cruising or coasting being selective depending on the boundary conditions. This study introduces DP-based simulation results and attempts to provide comprehensive interpretations of the optimal policy by analyzing the essential factors that affect the control problem, including boundary conditions, road load, and powertrain characteristics. Based on these interpretations, the control concepts can be explained as the optimal policy selecting the best control option based on system efficiency and boundary conditions. The results of DP are compared with a human-like driver model to show that the optimal speed profiles can effectively reduce energy consumption.

The vehicle fuel economy rating system in South Korea has adopted the US 5-cycle fuel economy system since 2012 to provide consumers with comprehensive information. However, due to resource constraints, derived 5-cycle equations have been utilized to approximate 5-cycle test results using the 2-cycle test. This study examines the accuracy of derived 5-cycle fuel economy equations for 20 recent vehicle models in Korea and updates them based on the correlation between 5-cycle and 2-cycle fuel consumption. The updated equations are expected to refine fuel economy ratings for up to three models, ensuring the label's reliability.

Selective catalytic reduction (SCR) catalysts is used widely to reduce NOx emissions from diesel engines. However, improvements in de-NOx performance are required to meet future standards of near-zero NOx emissions. This study examines the effectiveness of dual-point NH₃ injection technology, in which gaseous NH₃ is injected into both closed coupled and under floor SCR catalysts. The NOx removal efficiency of dual-point NH₃ injection is compared with that of single-point injection in a World Harmonized Transient Cycle test. The results show that dual-point injection of NH₃ gas can effectively reduce NOx emissions from diesel engines due to superior temporal and spatial distribution of NH₃ gas in an SCR catalyst.

To solve the problems that the YOLOv5 object detection network has low detection accuracy, false detection, and missed detection of small objects for trapped people and medical rescue supplies when there is interference in the light background during indoor rescue, this paper proposes a multi-scale small object detection network multi-scale small YOLOv5s (MS-YOLOv5s). A CAC3 module that integrates the attention mechanism is proposed to capture object feature information in both channel and spatial directions; the neck BiFPN feature pyramid network is improved to improve the model's ability to fuse features of different scales, and the activation function of the convolution module is replaced by SiLU, to improve the adaptive ability of the model for small object detection. The model is deployed on the mobile rescue detection platform. The experimental results show that the mAP @ 0.5 of MS-YOLOV5s is 7.8% and 24.9% higher than that of YOLOv5s at different scales and different postures of trapped people, and the FPS reaches about 12, which can meet the needs of indoor mobile detection, proving the effectiveness of the method proposed in this paper and the robustness of the network model.

This study investigates the impact of design parameter adjustments on the vehicle’s strength and body weight. To generate a lightweight design for a vehicle body, the bus body is examined and optimised. The direct optimisation process is used to obtain optimised vehicle bodies by changing material, component’s wall thickness and material diversity. The entire body of the vehicle is considered, but local optimisation is prioritised in this work because some parts are affected more than others under different loading conditions. Three different loading conditions are decided by considering normal loads on the vehicle bodies under normal driving conditions. The vehicle’s body structure weight is minimised while stresses and deformations are created in the boundaries. Three different materials are initially analysed and optimised. The multi-material vehicle body is designed after combining two materials with the best optimisation performance using optimisation rates. After obtaining the multi-material-based vehicle structure, its initial analysis and optimisation procedures are calculated as single-material-based vehicle structures. Finally, four different optimised vehicle body structures are obtained: three single-material based and one multi-material based. The effects of different loading conditions, and design parameters, such as component wall thickness, material type, and material diversity, are investigated, along with their advantages and disadvantages.

Reasonable test scenarios and objective evaluation methods can rapidly promote the development of autonomous vehicle technology. A new quantitative evaluation method for the comprehensive performance of autonomous vehicle is proposed in this paper. First, different test environments and test contents are combined to obtain vehicle test scenarios of different complexity. Then, the evaluation index system of autonomous vehicle is divided into target layer, total index layer, and index layer. After that, the weights of the index layer are determined by the objective weight method of Criteria Importance though Intercriteria Correlation (CRITIC) method, and the total weights of index layer are determined by the analytic hierarchy process (AHP) of subjective weight method. Finally, the improved grey relational theory method is used to quantitatively evaluate autonomous vehicles from four aspects: driving safety, riding comfort, intelligence, and efficiency. The quantitative evaluation of autonomous vehicles can reduce the influence of abnormal data on the correlation degree and increase the robustness of the evaluation algorithm. The evaluation results of the proposed method and the traditional fuzzy comprehensive evaluation method are compared by simulation experiment and evaluation. The results show that the proposed evaluation method in this paper is more objective and reasonable, which can quantitatively evaluate the comprehensive performance of autonomous vehicles.