Development Of Automobile Technology Research Articles

Research on Dynamic Recognition and Tracking Technology for Complex Scenes of Automatic Driving

<p>With the development of automobile technology, intelligent vehicle and automatic driving technology will make due contributions to reducing traffic accidents. This paper aims to improve the dynamic identification and tracking technology in the current intelligent vehicle and automatic driving. First, it is improved based on the MobileNet V2 backbone network, and then a new tracking model framework is designed combining with the SiamRPN single target tracker. Secondly, it integrates space-time tracking clues to improve the stability and robustness of the algorithm. Finally, it constructs a pedestrian dynamic identification algorithm based on the dynamic pedestrian factors in the driving process. Through the training of data sets and video tracking experiments, the performance of the algorithm in this paper is proved quantitatively and qualitatively.</p> <p> </p>

Energy and Environmental Impact of the Promotion of Battery Electric Vehicles in the Context of Banning Gasoline Vehicle Sales

This study quantitively estimates the energy and environmental impacts of China’s promotion of battery electric vehicles (BEVs) in the context of banning the sale of gasoline vehicles (GVs). Combining the population ecological growth model and the life cycle assessment method, the potential of BEVs promotion in reducing fossil energy (FE) consumption and greenhouse gas (GHG) emissions under different timings of banning GV sales was dynamically simulated and analyzed. The results show that the current life cycle FE consumption and GHG emissions of BEVs are approximately 40.1% and 26.6% lower than those of GVs, respectively. Based on the development of automobile technology and the national energy plan, replacing GVs with BEVs can reduce GHG emissions and FE consumption by up to 43.61–55.81% and 46.33–55.45%, respectively. Compared with the scenario without BEV promotion, if sales of GVs in China are banned between 2040 and 2060, the point at which the carbon peak of the automobile market will be reached will be advanced by approximately two years, and the corresponding carbon peak value will be reduced by approximately 13.58–28.79 million tons of CO2-eq (MtCO2e). In addition, the annual FE savings and GHG emission reductions will reach approximately 2.99–6.35 million TJ and 276.54–488.77 MtCO2e by 2050. This research work will not only help authorities, managers, and the public to better understand the environmental and energy impacts of promoting new energy vehicles, but also provide a forward-looking reference for formulating comprehensive, systematic, and reasonable industrial planning to better promote a green and sustainable transformation of the automotive sector and solve the relevant energy and environmental problems.

Abnormal Noise Recognition of Door Closing for Passenger Car based on Image Processing

Background: With the rapid development of automobile technology, the problem of abnormal door-closing noise has attracted more and more attention. The abnormal door-closing noise is an important factor for judging the quality of a car, so accurate identification of abnormal noise is the premise of fundamentally solving the abnormal noise. Objective: To accurately identify the abnormal sound of car closing through the image processing method. Methods: To accurately identify the abnormal noise of car closing the method to recognize and classify images using Support Vector Machine (SVM) is proposed. This method extracts Histogram of Oriented Gradient (HOG), texture and Speed Up Robust Features (SURF). The three extracted feature vectors are combined and used as the input of SVM. The classifiers obtained by different kernel functions are used to predict the labels of the test set, respectively. Results: Calculating the ratio of the value on the diagonal of the confusion matrix to the total number of each row, and this ratio is the classification accuracy rate. Test accuracy rate is 85%, the results indicate that the accuracy is high. Conclusion: This paper uses image processing methods to extract HOG, GLCM, SURF features and merge them together as a new feature vector. The experimental results show that the SVM classifier using the Gaussian kernel function optimized by hyperparameters has a high accuracy rate and can be used to identify whether the door is closed with abnormal noise.

Research on performance of vehicle semi-active suspension applied magnetorheological damper based on linear quadratic Gaussian control

With the development of automobile technology, the traditional passive suspension cannot meet people’s requirements for vehicle comfort and safety. For this reason, a variable damping semi-active suspension applied magnetorheological damper is proposed. By collecting various performance parameters of the front suspension, the optimal feedback control matrix is obtained by applying linear quadratic Gaussian control strategy, and the optimal damping force output is also obtained to improve comfort and vehicle safety by reducing vibration. The semi-active suspension model of a quarter vehicles was established by MATLAB/Simulink, and the simulation experiment was carried out. The results show that the semi-active suspension system with magnetorheological damper is superior to the traditional passive suspension in terms of vibration absorption; meanwhile, the root mean square values of vehicle acceleration, suspension dynamic deflection, tire dynamic travel, and tire dynamic load are reduced, which effectively improve the vehicle ride stability.

Wheel Alignment Detection using Raspberry pi

Wheel Alignment detection using Raspberry Pi - The development of automobile technology is evolving and the influence of automobile stability to travel safely is increasing. A modern person usually has wheel alignments both for front and rear wheels. For that detection is needed, here comes the role of our device. Here 3 elements are important Camber, Castor and Toe which needs to be looked after for alignment. All four tires should be in straight line. A further thing which matters is Knuckle, Bearing and Jumper. By rash driving alignment gets disturbed which affects tire wear and tear. Here, user can get affected by frequent tire replacement which leads to cost on maintenance. Here, every tire calculations are different and they should be precise. For maintaining that using sensors calculations are maintained which can be done using Raspberry Pi and Python as implementation language.

A Brief Description of ESP Working Principle and Common Control Methods

With the development of automobile technology, automobile active safety has been paid more and more attention. ESP is an essential component of active safety. Currently, ESP has slowly gained popularity, vehicle safety has been significantly improved. In order to make people have more in-depth knowledge of ESP, the author through reading a large number of documents to complete the article. This paper focuses on the working principle of ESP, and a brief description of its common control methods.

Study on Hybrid Electric Vehicle Noise and Vibration Reduction Technology

The hybrid electric vehicle (HEV) is becoming one of the main trends of the development of automobile technology. The structure and operation principle of HEV are introduced. The noise and vibration (NV) of engine, motor, generator, power split device, converter assembly and battery in HEV were analyzed. According to the NV characteristics in HEV, the measurements for NV control technology such as the excitation source control technology and route control technology were summarized, which provides a reference for further studying of the NV in HEV.

Feasibility Study of Fuel Consumption Prediction Model by Integrating Vehicle-Specific Power and Controller Area Network Bus Technology

With the development of automobile technology, it becomes possible to estimate fuel consumption by using the driving parameters from the electronic control unit (ECU) and output the calculation results via the controller area network (CAN) bus. As a result, it is feasible to design an approach for estimating fuel consumption by integrating vehicle-specific power (VSP) and CAN bus technology because of the accessibility and stability of the CAN bus. To determine whether the CAN-based measured data can be used to build the relationship between VSP and fuel consumption to replace the traditional fuel consumption meter, a comparison of fuel consumption data collected from the ECU and the fuel consumption meter is conducted in this study. Results show that the relationship between the fuel consumption rate and VSP bin built by the CAN bus data is consistent with the relationship derived from the fuel consumption meter; this finding indicates that the CAN bus technology can be used to describe the relationship between vehicle activities and fuel consumption rates for light-duty vehicles. In addition, a comparison of CAN-based measured data with VSP-based predicted data shows that the prediction approach that integrates VSP and CAN bus technology needs an aggregation level of 60 s or longer, which thus can be used to estimate a long period of fuel consumption accumulation and a fuel consumption factor for various travel speeds and road types.

A New Approach to Teaching Undergraduate Course Vehicle Emissions and their Control

Vehicle emissions and their control (VEC) is an important course for majors about automobiles, such as vehicle engineering, Automobile Service Engineering and thermal energy and power engineering. In order to meet the development of automobile technology and culture the corresponding talents, the teaching method should be reformed and innovated. In this paper, the difficulties in VEC course teaching were summarized and analyzed, and the countermeasures and suggestions were put forward. The course content was redesigned and the laboratory experiment was re-arranged. The innovation training program of students was put forward. Some pedagogical techniques and evaluation methods for VEC course were proposed.

Experimental study of glass-fiber mat thermoplastic material impact properties and lightweight automobile body analysis

With the development of automobile technology, more and more light-weight materials are applied to automobile body. Glass mat thermoplastic (GMT) material is a promising material that has good mechanical strength, impact energy absorbing capacity and recuperability. It is more and more used in automobile body for the purpose of lightweighting and environmental protection. In this paper, the high strain rate mechanical property of one GMT material is studied using the split Hopkinson pressure bar technique. The test result is analyzed for its applicability in automobile body and a material replacing method from original steel sheet to GMT sheet is found. Then the computer simulation is carried out for a car crashing into a rigid wall before and after some of its parts made such material replacement. The simulation results show that the method presented in this paper for GMT material application in automobile body is applicable.