In order to solve the problem that steering electric control system cannot be validated in road simulation test, this paper proposed a road simulation test bench test scheme of the steering system to verify the accuracy of the steering system based on the automobile road simulation durability test technology and the principle of automobile bus communication. Firstly, the control circuit of the steering system was built in the road simulation test bench; Then, the bus tool software was used to output the control signal of the steering system controller into the steering system according to time sequence; Finally, the effectiveness of the test scheme was verified by the strain of the steering system and the torque signal of the steering wheel. The result shows that the method enables to activate the EPS function in the traditional test rig.

In order to verify the coordination, accuracy and smoothness of the operation of the intelligent chassis assisted driving system of the autonomous vehicle, this paper proposed a method to test the control precision and stability of intelligent chassis assisted driving system. Firstly, the communication protocol of the an integrated modular intelligent chassis was detected using CANoe, secondly, the function and performance test of the control algorithm was verified through vehicle collaboration control algorithm, and finally, a number of accuracy control tests including straight driving speed, turning, steering system, braking and so on were conducted. The results show that the intelligent chassis can achieve ±1 km/h speed control, has functions of normal braking, obstacle avoidance bypass, and steering error within 1°, further validating the feasibility of the proposed method.

To address the issue that hybrid vehicle driveline durability test cannot cover the customers’ usage scenario, a customer-relevant, forward-development method based on vehicle networking data has been designed. This paper started with typical usage conditions, combining it with analysis of driveline fatigue damage, to develop and standardize combinations. Based on the user’s driving habits and proving ground load spectrum, this study explored how to translate these users’ driving habits into whole-vehicle durability test specifications that meet service life requirements. Finally, the process for establishing vehicle durability test specifications within a proving ground was determined, and a rational and effective test specifications for hybrid vehicle driveline was established.

Vehicle dynamic model and proving ground road model were built based on virtual proving ground (VPG) technology, and body fatigue & durability simulation was conducted, then an analysis were conducted to address the issue of multiple risk points and large damage values in the fatigue simulation of a vehicle project. Ultimately, it was found that excessive load on the suspension jounce bumper was the direct cause of large body damage. Based on VPG technology, virtual tuning was carried out on the jounce bumper, reducing the frequency of the jounce bumper under compression limit by increasing the jounce stoke of the bumper, thus reducing fatigue damage. The road durability test verification shows that the optimization scheme improves body durability performance and vehicle ride comfort.

To solve the problem that a single sensor cannot provide continuous and stable position information. In this paper, an innovative method is proposed to build a high-precision positioning system by integrating three kinds of data, namely global satellite navigation system, Inertial Measurement Unit (IMU) and prior map point cloud matching, through the Error State Kalman Filter (ESKF) algorithm. At the same time, by introducing the correction matrix method, the pose problem can be corrected to avoid the system failing to obtain effective observations in the case of Global Navigation Satellite System (GNSS) failure or prior map matching delay, etc., so that the system can maintain stability and be in a high-precision state. The experimental results show that the proposed method can still maintain high precision in the case of failure of the observed value. Compared with the traditional single sensor positioning method and the common GNSS/IMU combined positioning method, the proposed method has higher robustness and reliability, and can better meet the positioning requirements of autonomous vehicles in complex environments.

Traditional methods based on points cannot balance the detection speed and accuracy in LiDAR semantic segmentation. To address this issue, this paper proposes a multimodal fusion LiDAR semantic segmentation network. Semantic features are extracted through the point-grid module, spatial and contextual information is aggregated through the attention mechanism module, semantic segmentation is achieved through the 2D Fully Convolutional Network (FCN) feature fusion pyramid, and finally, information loss is reduced through the fusion of 2D and 3D features, and the weights are updated to optimize the model using the loss function. Verification of SemanticKITTI dataset indicates that this model achieves an average crossover ratio of 63.3%, and takes into account of real-time property and accuracy as compared with other algorithms, which significantly improves the accuracy of LiDAR semantic segmentation.

To improve the air brake system safety and intelligence control of commercial vehicle, this paper introduced the working principle of electric control air dryer and proposed the air regeneration air consumption ratio as the evaluation index of drying efficiency. Through the establishment of dryer simulation model, the paper analyzed the difference of drying efficiency between mechanical dryer and electric control air dryer. And in combination with the measured results of the dew point drop of compressed air in the vehicle air reservoir, the performance advantages of the electric control air dryer was verified. This paper introduced the technical advantages of electronic controlled dryers in preventing brake pipeline icing, saving fuel, and predictable maintenance and repair.

This paper introduced the development of object detection datasets and the establishment of basic evaluation metrics, and based on this, it reviewed different categories of object detection algorithms. Single-stage and two-stage detection algorithms, as well as corresponding optimization algorithms, were analyzed separately. Highlighting the iterative process of detection speed and accuracy, the paper elaborated the challenges and difficulties in object detection algorithms. A summary and outlook for the improvement of the method itself and the optimization design under the application requirements of the algorithm were proposed in the paper, which indicated training supervision of object detection, the difficulty of detecting small targets by the algorithm. At the same time, the paper also indicated the coordination between detection speed and accuracy in real-time detection tasks and multimodal fusion application, as well as the important significance of the interpretability of algorithm operation for further improving the algorithm.

In order to make the strength of an MPV traction device meet the design objective and ensure that the traction device does not fracture and fail under extreme working conditions, ABAQUS implicit analysis was used to conduct strength analysis and improved design analysis of the traction device under different working conditions. The test verification results show that increasing the material thickness significantly improves the strength of the traction device. However, it is necessary to adopt the optimization methods of structural features such as flanging, punching and adding reinforcing ribs.

To develop a complete and effective reliability analysis method for automotive component life data, this paper selected the reliability of clutch spider on a heavy-duty tractor as the research object. For the life data of the clutch spider that were collected in customer usage tests, the optimal model was selected by comparing different distribution model and the conformity fitting its lifetime data. And then, the statistical analysis was carried out to obtain the information of the reliability, such as B10 life and average life, etc., which was used for the reliability evaluation according to different user scenarios. The result indicate that the parametric model method based on specific distribution has a small sample size requirement and high accuracy of result, and the results of reliability evaluation to which user scenario is introduced can provide a reliable basis for vehicle improvement design according to market positioning.