Vehicle Maintenance Research Articles

Application of Decision Tree and Machine Learning in New Energy Vehicle Maintenance Decision Making

Abstract Several incidents of electric vehicle combustion across various regions in China have brought the safety concerns associated with new energy vehicles into sharp focus within public discourse. Addressing these concerns, this paper explores maintenance decision-making for new energy vehicles through the application of decision trees and machine learning techniques. Initially, the study analyzes how decision trees and machine learning are employed in crafting maintenance decisions for these vehicles. It involves collecting data through internet searches, followed by statistical analyses and preprocessing to set the groundwork for further inquiry. Furthermore, the research advances by developing and refining decision tree models, which facilitate the integration of fault diagnosis and maintenance decision-making processes for new energy vehicles. This effort culminates in the establishment of a robust decision tree model specifically designed for the maintenance of new energy vehicles, which is subsequently evaluated through a detailed case study. The results are presented: the approximation degree of new energy vehicle fault diagnosis based on the decision tree model is 90.58%, 90.67%, 88.09%, 91.28%, and 90.19% at the significant level of α taking the value of 0.01, 0.05, 0.100, respectively. This study provides theoretical guidance on the application of decision trees for the diagnosis and repair of faults in new energy vehicles so that the development of new energy vehicles in China can be ensured.

Research on Safety Evaluation Methods in the Maintenance of Hybrid Vehicles

Research on Safety Evaluation Methods in the Maintenance of Hybrid Vehicles

To the question of forming the structure of technical service in Palestine

The article analyzes the existing system of maintenance and repair of vehicles in Palestine. The factors influencing the production and technical base of technical service enterprises are considered, and ways of its optimization are proposed in order to reduce the costs of maintaining the vehicle fleet. An algorithm for constructing a mathematical model is proposed to describe the studied organizational and technological processes and methods for forming the structure of car technical service. Keywords maintenance, vehicle repair, service system, optimization, factors, organizational and technological processes, scientific research, cost reduction

СОВЕРШЕНСТВОВАНИЕ ПУНКТА ТЕХНИЧЕСКОГО ОБСЛУЖИВАНИЯ

Motor vehicle fleet reliability and maintenance cost reducing are of top priority in the context of dynamically developing production and market relations. Service centers play the leading role in production efficiency and rolling stock operation since service center units provide quality and efficiency of work and predetermine labor productivity, maintenance and repair costs. Often in repair practice there are cases when springs with exceeding permissible deviations from stiffness standards are installed on a car. It may happen due to imperfection or lack of special control means. There springs disrupt elastic and damping properties of suspensions, increasing vibration impact on driver, passengers and transported cargo, and also may cause increased wear of chassis and breakage of springs. The goal of this work is to increase productivity and quality of repair work, as well as reduce operating costs by improving maintenance system and reducing downtime associated with failures.

Application and analysis of cool storage device in emergency situation of high-speed trains

The article introduces the plan of emergency cold storage measures, analysis of fresh air volume, and simulation of the entire vehicle. It also analyzes the advantages and disadvantages of emergency cold storage measures from aspects such as vehicle transformation, use and maintenance, and cost. Based on the comparative analysis results of emergency cold storage measures, the application of cooling storage technology in emergency situations of Multiple unit has greater advantages, and has higher research and reference value. In addition, it can ensure the comfort in the vehicle within the emergency ventilation time by adjusting the existing emergency ventilation mode. The article introduces the scheme of emergency cold storage measures and the analysis of fresh air volume. The focus is on the simulation analysis of the application of phase change cold storage technology in emergency situations of high-speed trains. Theoretically, the application of cold storage technology in emergency situations of high-speed trains has significant advantages and has high research and reference value. In addition, with the adjustment of existing emergency ventilation modes, the comfort inside the train can be ensured during emergency ventilation time.

Research on teaching innovation of new energy vehicle testing and maintenance technology professional course by integrating online and offline teaching mode

Research on teaching innovation of new energy vehicle testing and maintenance technology professional course by integrating online and offline teaching mode

Investigating Fleet Management Challenges and their Impact on Service Delivery: A Case Study of a Selected Municipality in Limpopo Province, South Africa

Municipal governments in South Africa are crucial for community development and providing essential services. This project aimed to investigate the challenges faced by fleet management in selected municipalities. The study used a qualitative research approach, conducting semi-structured interviews with participants selected through non-probability sampling. Thematic data analysis was used to analyse the data, identifying key findings such as the lack of an effective fleet management strategy, inadequate vehicle management and maintenance, limited technological innovation in vehicle management, insufficient driver management and hiring criteria, and a lack of skills enhancement and training opportunities.

Accelerating Light-Duty Fleet Decarbonisation through Energy Efficiency Audits: Results and Methodology Assessment

The transport sector is responsible for 37% of the energy consumption in Portugal (70% of it due to road transportation), supplied almost completely by fossil fuels. Portugal must reduce these sector’s emissions by 98% to achieve carbon neutrality by 2050, thus making transportation a crucial sector for a successful decarbonisation of the economy. This scenario sparked action at ADENE – the Portuguese Energy Agency to create MOVE+, an auditing methodology that incentivises and guides a broad group of stakeholders to act on the decarbonisation of mobility, starting with light duty and freight fleets. It comprises a framework to rate fleets on energy efficiency which enables regular implementation and monitoring of decarbonisation measures in areas such as vehicle technology, telematics, driver training, tyre selection, and maintenance. This paper shows that the application of the MOVE+ methodology helped identify an electrification potential of 24% on average per fleet, according to the Best-in-Class (whereas the analysed sample shows 20% of electrification). A multiple linear regression model validates the correlation between MOVE+ obtained scores, in the evaluated dimensions, and the fleet’s specific CO2 emissions. The methodology also allows us to assess that Portugal is lagging to meet the carbon neutrality target for the transport sector by 2050. Such assessment allows us to estimate that, regarding light-duty fleets, at the current pace zero emissions will only be reached by 2080, thus highlighting the need for public policy adjustments that push towards faster decarbonisation.

Wireless HVAC compressor diagnostics using state of the art machine learning-based signal analysis Z-freq 2D

One of the priorities in detecting a faulty car engine is through a method known as diagnostic, and it is very crucial as each diagnostic able to provide information and assessment to identify problems in the car A/C compressor. Early detection of a compressor malfunction, is a fast way to prevent any heavy maintenance of vehicles either in the short or long term. This paper introduced a new statistical method to find the faulty in the vehicle’s A/C compressor which is known as Z-freq 2D. The foundation of Z-freq 2D is involving the implementation of a Z-notch frequency domain filter. This approach was enhanced by using a special sensor that can detect two axial axes known as the Phantom Vibration Sensor specifically designed to detect and monitor the performance of the A/C compressor of the vehicle. Using the sensor, the data were recorded at numerous parameter sets of compressor speed. The analyzed data shows that Z-freq 2D coefficient is increase as the speed of the compressor increase over the duration of time. Z-freq 2D can be used to detect the malfunction and the irregularities of vibration signals, which may be indicated that the compressor is failing.

Reliability-based model for optimizing resources in the railway vehicles maintenance

Reliability-based model for optimizing resources in the railway vehicles maintenance

Development and Usability Evaluation of Mobile Augmented Reality Contents for Railway Vehicle Maintenance Training: Air Compressor Case

Development and Usability Evaluation of Mobile Augmented Reality Contents for Railway Vehicle Maintenance Training: Air Compressor Case

Applying lean practices in vehicle maintenance services at Massy Motors in Trinidad and Tobago

Applying lean practices in vehicle maintenance services at Massy Motors in Trinidad and Tobago

STUDY OF THE DENSITY OF LOCATION OF CAR SERVICE ENTERPRISES IN NAMANGAN AND THE LIST OF SERVICES OFFERED

The problem of urban transport infrastructure is considered in terms of ensuring the rational organization of vehicle maintenance and repair based on the principle of optimal placement of car service enterprises in urban areas and the list of services offered. Factors have been identified that make it possible to solve the problem of the chaotic location of such enterprises.

Effect of Heavy Vehicles on Road Pavement and Implication on the Environment in North Central Nigeria

Transport infrastructure plays a crucial role in Nigeria’s economic development, mobility and environmental sustainability. Road pavement facilitates the movement of vehicles and ensure safe and efficient transportation of goods, services and people across the country. The study was conducted on Asa-dam Road Ilorin, Kwara State, Nigeria, primary source of data and random sampling techniques was employed to select 150 respondents. Findings from the study revealed that potholes, depression of the road surface and other road failures are caused by heavy vehicles. Majority of respondents (96.7%) perceived highest level of major damage are caused by heavy vehicles of 50 tons above while 45.3% perceived minor damage and 34.7% perceived medium damage by heavy vehicles of less than 30 tons. P-value of 0.000 is below the conventional threshold of p<0.05. R value of 0.892 with R2 value of 0.795 implied a strong and positive relationship exist between inadequate road pavement and the environment which increases vehicle maintenance cost, travel time and pollution. F-ratio value of 140.832 was statistically significant. The study concluded that heavy vehicles have significant effect on road pavement damage as a result of the weight and of goods they carry therefore affecting the environment. However, it is recommended that the current road pavement be scrapped and new layer of asphalt be laid to cater for heavy vehicle traffic while government should do more routine and periodic maintenance of the road pavement.

Questions about the organization and technology of vehicle maintenance and repair in the Republic of Tuva

Questions about the organization and technology of vehicle maintenance and repair in the Republic of Tuva

Revolutionizing Mobility: Big Data Applications in Transport Planning

Revolutionizing Mobility: Big Data Applications in Transport Planning

Performance Parameter Study of Signal Warning Detector (SWAD) and Circuit System

Safety is a factor that needs to be prioritised at the workplace. Every worker in the sector values a safe and secure work environment, so workplace safety is important for all of them. Highway maintenance workers' safety is critical since they are placed in the highway's work zone to perform maintenance tasks. There are many incidents involving maintenance workers when working on the highway since there is a poor danger detection system in place to alert workers during the working process. The goal of this research is to build an improved safety system for maintenance workers on the job. There are two objectives in this study, which are to study the parameters effect of applying a distance sensor in finding the best safety vehicle detection at an emergency lane and the reliability test of a signal warning detector (SWAD) casing for the best installation at a road maintenance vehicle. The SWAD set up and experimental performance field test have been done. The study was conducted by setting up the SWAD at Padang Kawad, UTHM, and testing its ability to detect the presence of a vehicle at different distances and sensor heights. The vibration test for SWAD circuit casing has be done using a vibration shaker. The results showed that the SWAD was able to detect the presence of a vehicle at 90 metres and at a sensor height of 0.7 metres. From the vibration testing for the long pane, we know that the maximum vibration of SWAD’s circuit casing can absorb, which is 13.074 Hz, and the speed of the vibration is 3.8319 m/s. The system can increase the level of safety among highway workers if it is implemented on highways for safety purposes involving highway workers and users of highways.

Teacher and Student Competence Improvement at SMK Muhammadiyah Karangkobar

Abstract. Vocational High School (SMK) is a Vocational High School that targets the formation of character and skills for its graduates. The learning system in Vocational Schools that includes practical material makes Vocational graduates ready to use and able to work and even create jobs. So that SMK graduates are targeted to be able to contribute to the local economy. Highly contradictory conditions were found at the Muhammadiyah Karangkobar Vocational School, Banjarnegara. Muhammadiyah Karangkobar Vocational School is still overwhelmed by the problem of limited learning support practice equipment. So far the practical Teaching and Learning Process (PBM) has only been carried out by watching videos due to the limited equipment and practical simulators available in schools. Occasionally PBM practices using the private vehicles of students/teachers who are willing to use their vehicles as practice media. This condition is still not optimal because the work done tends to be light work which does not adequately represent the material for the Department. This condition is of course not very good considering that the output of SMK students is skills that should be acquired through a structured and systematic practicum process. The solutions offered in these problems are, firstly, providing support equipment grants in practice, especially periodic maintenance of automotive light vehicles, and electric welding tools and bench work, and secondly, providing training to teachers and students of Muhammadiyah Karangkobar Vocational School on Machine Elements, supplemented with job sheets and preceded by the provision of material in advance. The Muhammadiyah Organization-Based Community Service Program (PPM-Muh) aims to increase the knowledge and skills of teachers and students of SMK Muhammadiyah Karangkobar in carrying out periodic service work and light vehicle tune-ups. The dedication method is carried out through the theoretical provision of engine maintenance through classroom learning, soft skills, demonstrations, and tune-up practical exercises. The targets of this training program are teachers and students of SMK Muhammadiyah Karangkobar.

QUALITY ASSESSMENT OF THE DISCIPLINE «FIRE AND RESCUE EQUIPMENT»

This article is aimed at conducting a comprehensive analysis of the course «Fire and Rescue Equipment» taught in the 4th year (7th semester) at the National University of Civil Defence of Ukraine. The course is intended for students majoring in Fire Safety, Fire Safety and Fire Fighting and Rescue Operations. The discipline is worth 3 ECTS credits and has 40 classroom hours, including 14 hours of lectures and 26 hours of practical classes. The course covers a wide range of topics, including the operation of firefighting equipment, vehicle maintenance, road safety, and the operation of firefighting equipment. The anonymous survey of offline cadets, which involved 97 respondents out of a total of 105, included an assessment of such parameters as the usefulness of the course for future service, the adequacy of the number of classroom hours, the logical structure of the course, the quality of teaching, the availability of the instructor for consultations, the effectiveness of the assessment system, etc. The survey results indicate a high assessment of the course’s usefulness for future service in the units of the State Emergency Service of Ukraine (SESU), which was expressed by 79.4% of participants. However, problems were identified with the availability of the lecturer for consultations and the instability of the OpenTEST 2.3.0 testing system, which led to difficulties in assessing students’ knowledge. The findings indicate the need to focus on the practical component of learning, improve the material and technical base for learning the subject, and change the assessment system. The respondents also suggested increasing the number of practical classes and improving the assessment system. The main conclusion of the study is to emphasise the importance of improving the educational process based on the opinions of the student audience to increase the effectiveness of teaching the course «Fire and Rescue Equipment».

Deteksi Kerusakan Ban Mobil Menggunakan Convolutional Neural Network dengan Arsitektur ResNet-34

The examination of tire damage can be categorized as part of vehicle maintenance with the aim of ensuring the tires are in good condition. Visual inspection using human observation has limitations, making it not always accurate and prone to errors in determining tire roadworthiness. This study designs a machine learning model using Convolutional Neural Network (CNN) with a ResNet-34 architecture to detect car tire damage. The parameters used in training this CNN model include the Adam optimizer, a learning rate of 0.0001, batch size 32, and 50 epochs. In this study, there are two predicted image classes: normal tires and damaged tires. The research results indicate that the CNN model with ResNet-34 architecture can predict both classes very well, as evidenced by the model evaluation results with an accuracy of 0.916, precision of 0.907, recall of 0.927, and an F1 score of 0.917. These results suggest that the CNN model with ResNet-34 architecture can be used as an effective tool for inspecting tire damage.