Automobile Technology Research Articles

Exploration on Application of High Pressure Water Jet Cleaning Technology

at present, the three-dimensional cleaning machine involved in tank car cleaning technology in China has full-automatic function, which includes two main structures: three-dimensional positioning machine and high-pressure cleaning machine. However, the tank car cleaning process used in the railway field still has many shortcomings. For example, serious pollution, serious energy consumption, insecurity, etc. In order to improve such defects, it is necessary to introduce new processes and improve the previous cleaning processes. The introduction of new technology can reduce environmental pollution and save capital cost. It can adapt to the development of the times and meet people's needs. Therefore, this paper expounds and analyzes the high-pressure water jet cleaning technology in railway tank cars from the aspects of application and improvement, and puts forward the corresponding improvement measures for reference.

Performance improvement on motor BLDC speed controller by using multi controller with summation technique

BLDC motor is the most widely used in the industrial world, especially in electric vehicles. With this increasing demand, a variety of research topics emerged in BLDC motors. One popular research is on BLDC motor speed control topics to maintain speed for its application, such as intelligent cruise technology in electric cars and conveyors for line assembly. However, from several existing studies, the BLDC Motor controller still uses a single controller model. The controller's output is purely from the controller without any improvement in characteristics and has a problem with the oscillating speed setpoint (error problem). In this study, the researcher proposed a combining control with the concept of summation output to handle this problem. With this concept, the control techniques used can improve each other so that better control can be produced following the control system assessment parameters. The authors used a Fuzzy Logic Controller, Artificial Neural Network (ANN), and PID, which were combined and obtained seven control systems. The results show that the control system can improve several parameters using the summation concept from the seven controllers model. It has a positive overall correlation when viewed in terms of the difference between the Error and the setpoint or MAE (Mean Absolute Error) as parameter assessment.

Evolution of Ride Services: From Taxicabs to Ride Hailing and Self-Driving Cars

In recent years decentralized Ride Hailing companies have gained significant market share at the expense of vertically-integrated Taxi companies. Yet, Ride Hailing companies also experienced substantial setbacks, and it is not clear what the endgame between these two competing business models will be. Further, emerging self-driving car technologies, which leads to another form of a vertically-integrated ride service poses further questions on how the industry will shape in the future. In this paper, we aim to gain insights about the evolution and the future of ride services under these two distinct business approaches. We model and analyze competition and entry between Vertically Integrated (VI) and decentralized Ride Hailing (RH) firms. Although the VI model has an advantage for being centralized, we find that when customers are patient, in competition, the RH firm predominantly gains the upper hand in the market with lower delays and higher prices, as well as higher market share and profits even if it has a cost disadvantage. Surprisingly, entry may reduce total vehicle supply, and tends to increase customer waiting times. When customers are impatient, the entry of an inefficient VI firm may even lead to a decrease in social welfare despite introducing competition. Our results provide insights into how decentralized Ride Hailing companies may have a strategic advantage to dominate the market due to their agility and the structure of their business model, and how this can sometimes hurt service quality. Conversely, regulators should also be cautious about subsidizing inefficient Taxi services or self-driving ride services with costly technologies.

How to Combine the Two Landmark Treatment Methods-Allogeneic Hematopoietic Stem Cell Transplantation and Chimeric Antigen Receptor T Cell Therapy Together to Cure High-Risk B Cell Acute Lymphoblastic Leukemia?

Allogeneic hematopoietic stem cell transplantation (allo-HSCT) has made tremendous progress in the last few decades and is increasingly being used worldwide. The success of haploidentical HSCT has made it possible to have “a donor for everyone”. Patients who received transplantation in remission may have a favorable outcome, while those who were transplanted in advanced stages of disease have a poor prognosis. Although chimeric antigen receptor T (CAR-T) cell therapy is currently a milestone in the immunotherapy of relapsed or refractory (R/R) B cell acute lymphoblastic leukemia (B-ALL) and has demonstrated high remission rates in patients previously treated in multiple lines, the relatively high relapse rate remains a barrier to CAR-T cell therapy becoming an excellent cure option. Therefore, combining these two approaches (allo-HSCT and CAR-T cell therapy) is an attractive area of research to further improve the prognosis of R/R B-ALL. In this review, we will discuss the current clinical practices of combining allo-HSCT with CAR-T cell therapy based on available data, including CAR-T cells as a bridge to allo-HSCT for R/R B-ALL and CAR-T cell infusion for post-transplant relapse. We will further explore not only other possible ways to combine the two approaches, including CAR-T cell therapy to clear minimal residual disease peri-transplantation and incorporation of CAR technology to treat graft-versus-host disease, but also the potential of CAR-T cells as a part of allo-HSCT.

An assessment of customers’ satisfaction for emerging technologies in passenger cars using Kano model

Purpose Automobile industry has been the backbone of manufacturing sector in any country. During the past decade, passenger car industry has emerged as the one of the growing sectors in the Indian economy. Technological features in the passenger cars industry has been evolving in the global market, and customers have been the most important stakeholders to judge the requirement of these features. Therefore, the purpose of this paper is to analyze the customers’ need for these emerging technologies using Kano model of customer satisfaction. Design/methodology/approach This paper has used the Kano model to assess the customer satisfaction for Indian passenger car companies. Overall, 250 customers of passenger cars from Northern India have been surveyed using well-structured questionnaire designed as per the Kano model. On the basis of responses, this study has categorized the technological attributes of passenger cars as attractive, must be, one-dimensional and indifferent. Findings “Auto Gear Shift” system has emerged as a must be attribute. “Premium surround system” has been categorized under one-dimensional attribute. “Communication between vehicles,” “integration with smart phone,” “connecting applications,” “dual-stage airbags,” “in-dash navigation system,” “rearview camera,” “heated and cooled seats,” “built-in fourth generation long term evolution,” “Wi-Fi system” and “automated window cleaning system” have emerged as attractive features. The customers have been indifferent about “gesture control,” “reality display on car wind screen” and “run-on-flat tyre.” In contradiction to the popular belief, this study has found that customers have shown Indifferent attitude toward “hydrogen fuel-operated cars” and “battery cars.” Research limitations/implications This present study gives insight about the acceptability of various emerging technological features in Indian car market. This study has fulfilled the existing dearth in assessing the customers’ insight about the implementation of these emerging technologies in Indian cars. This paper will be helpful to the manufacturers to inculcate the voice of the customers in designing the new technologies for the passenger cars. Originality/value Previous studies across the globe have applied Kano model for assessing customers’ satisfaction in various industries, but according to the authors’ knowledge, hardly any study was conducted in context of technological attributes for Indian passenger car companies.

Development of Human-Computer Interactive Interface for Intelligent Automotive

The wide application of information technology and network technology in automobiles has made great changes in the Human-computer interaction. This paper studies the influence of Human-computer interaction modes on driving safety, comfort and efficiency based on physical interaction, touch screen control interaction, augmented reality, speech interaction and somatosensory interaction. The future Human-com-puter interaction modes such as multi-channel Human-computer interaction mode and Human-computer interaction mode based on biometrics and perception techno-logy are also discussed. At last, the method of automobile Human-computer interaction design based on the existing technology is proposed, which has certain guiding significance for the current automobile Human-computer interaction interface design.

Design and Implementation of Edge-Fog-Cloud System through HD Map Generation from LiDAR Data of Autonomous Vehicles

Self-driving cars, autonomous vehicles (AVs), and connected cars combine the Internet of Things (IoT) and automobile technologies, thus contributing to the development of society. However, processing the big data generated by AVs is a challenge due to overloading issues. Additionally, near real-time/real-time IoT services play a significant role in vehicle safety. Therefore, the architecture of an IoT system that collects and processes data, and provides services for vehicle driving, is an important consideration. In this study, we propose a fog computing server model that generates a high-definition (HD) map using light detection and ranging (LiDAR) data generated from an AV. The driving vehicle edge node transmits the LiDAR point cloud information to the fog server through a wireless network. The fog server generates an HD map by applying the Normal Distribution Transform-Simultaneous Localization and Mapping(NDT-SLAM) algorithm to the point clouds transmitted from the multiple edge nodes. Subsequently, the coordinate information of the HD map generated in the sensor frame is converted to the coordinate information of the global frame and transmitted to the cloud server. Then, the cloud server creates an HD map by integrating the collected point clouds using coordinate information.

The impact of the corporate average fuel economy standards on technological changes in automobile fuel efficiency

This paper empirically examines the effect of the U.S. Corporate Average Fuel Economy (CAFE) standards on the technological progress in automobile fuel efficiency. Using detailed vehicle attributes data from 1978 through 2018, we find that more stringent fuel economy standards increase the rate of technological improvements in new passenger cars, and this effect is primarily driven by the response of U.S. automakers. We do not find evidence that CAFE standards have a similar effect on the technical change in light-duty trucks. Our results also indicate that higher gasoline prices have a significant and positive effect on the improvement of fuel-saving technology in both passenger cars and light trucks. Using our empirical estimates, we project that the recent rollback of Obama-era CAFE standards would forego an approximately 2-percent increase in cars’ fuel economy over the 2021–2025 period as a result of technological progress.

Computational study on the potential of aluminium alloy as a candidate material in automotive leaf spring

ABSTRACT Modern advancements and emerging trends in automobile technology have shifted the primary focus of the OEMs to make vehicles lighter, faster, and reliable. Weight has always been a major concern in commercial medium/heavy-duty vehicles. The leaf springs account for 20% of the sprung weight of the vehicle thereby making the suspension system one of the heavy components of an automobile. This paper focuses on analysing the potential of aluminium alloy as a candidate material in leaf spring so as to make the suspension system lighter and more reliable. Aluminium alloy is one of the appropriate materials to proceed with because of its lightweight, strength, and non-significant deformation during load cycles. Three-dimensional CAD model of standard leaf spring was created in DS CATIA V5R19 software and computational analysis were carried out in ANSYS Workbench 18.1 by defining material as plain carbon steel (structural steel) and Aluminium alloy for comparative study. The results of the analysis that the reduction in weight of the leaf spring using aluminium alloy was approximately 64.71% along with a significant reduction in equivalent stress induced at different loading condition with a maximum reduction of 45.30% equivalent stress at the fully loaded dynamic condition.

Vehicle Positioning System Based on Cubic Spline Interpolation Using Statistical Analysis

Vehicle monitoring and positioning become an essential factor in road management to secure and safeguard the vehicular network, which influences the coupling of reliability on the advanced automobile technologies. Furthermore, to predict the exact location of a car in a given time is challenging, because it depends on a myriad number of elements. Moreover, knowing the position of a vehicle helps passengers as well as increase vehicle network security. In this paper, we propose a mathematical model to predict the position of a car from a prepopulated dataset using spline interpolation. More interestingly, the prediction point of a mobile vehicle will be presented without any help from real-time monitoring devices. Simulation of vehicle positioning is done using bus trajectory data in a university environment in the University of Malaya to verify the feasibility and benefit of the proposed approach. Accordingly, a process of evaluation has been performed based on a plethora of components and existing works to show the effectiveness of the proposed method.

Student Perceptions of Driverless Car Technology

The subject of driverless cars is incredibly dynamic as evidenced by the great amount of emerging literature and news items about the topic. It touches disciplines such as technology, public policy, and auto-insurance. The purpose was to explore students’ perceptions of driverless car technology. This research surveyed students using Qualtrics and was administered to both lower- and upper-level classes. Data was tabulated and broken down by attributes such as gender, age, and race. The survey results indicate the likelihood of someone buying a driverless car across these attributes. A list of both anticipated advantages and disadvantages were also tabulated.

Performance Evaluation of Diesel Engine Using Novel Variable Compression Ratio Mechanism

Increasingly stringent emission and fuel economy standards brings opportunities and research in automobile engine technology development to make it more efficient and less polluting. There are various performance improvement strategies adopted by different researchers in order to get maximum power from the minimum quantity of fuel alongside substantial reduction in exhaust gas emission. The techniques such as CRDI (Common Rail Direct Injection), VVT (Variable valve timing) and such more are commercially viable and successfully incorporated in vehicles. Along the similar track, this paper highlights the importance of variable compression ratio diesel engine, method of achieving the variable compression ratio (VCR) as per load and speed conditions. Variable compression ratio (VCR) technology is one of the method for improving the automobile engine performance, efficiency, fuel economy with reduced emission for range of fuels. The basis of the VCR engine is to operate at different compression ratio, by altering the combustion chamber volume, as per need of most suitable operating conditions. Apart from this, the fuel injection location needs to be varied as per load and speed conditions. The synchronization of both VCR and variable fuel injector location (VFIL) becomes important. Knowing this fact, the study for the diesel Comet engine (3.7 kW@2100 RPM) is undertaken for variable clearance volume accompanied with VIPL. The work consists of design and development of mechanism consisting of auxiliary cylinder and auxiliary piston which will operate in and out of combustion chamber as per load and speed conditions. The detailed drawings and complete experimentation will be carried out to judge the improvement of performance of diesel engine with modification of variable clearance volume concept. The performance parameters consist of brake power, brake thermal efficiency and brake specific fuel consumption under various load conditions.

Intelligent Hybrid Fusion Algorithm with Vision Patterns for Generation of Precise Digital Road Maps in Self-driving Vehicles

Due to the significant increase in the use of autonomous car technology, it is essential to integrate this technology with high-precision digital map data containing more precise and accurate roadway information, as compared to existing conventional map resources, to ensure the safety of self-driving operations. While existing map technologies may assist vehicles in identifying their locations via Global Positioning System, it is however difficult to update the environmental changes of roadways in these maps. Roadway vision algorithms can be useful for building autonomous vehicles that can avoid accidents and detect real-time location changes. We incorporate a hybrid architectural design that combines unsupervised classification of vision data with supervised joint fusion classification to achieve a better noise-resistant algorithm. We identify, via a deep learning approach, an intelligent hybrid fusion algorithm for fusing multimodal vision feature data for roadway classifications and characterize its improvement in accuracy over unsupervised identifications using image processing and supervised vision classifiers. We analyzed over 93,000 vision frame data collected from a test vehicle in real roadways. The performance indicators of the proposed hybrid fusion algorithm are successfully evaluated for the generation of roadway digital maps for autonomous vehicles, with a recall of 0.94, precision of 0.96, and accuracy of 0.92.

Reduced Supply in the Organ Donor Market and How 3D Printing Can Address This Shortage: A Critical Inquiry into the Collateral Effects of Driverless Cars

Driverless cars, such as those currently operated by Uber and others as well as those being researched and developed by major and niche automobile manufacturers, are expected to dramatically reduce the number of highway fatalities in the coming years. While no one will fault any technology that safely and effectively protects and saves lives, many individuals with an array of medical conditions rely on organ donors to provide the liver, kidney, or other organs required to facilitate a life-saving organ transplant. Consequently, one collateral effect of the introduction of driverless car technology will be a reduction in the market supply of healthy organs for transplantation. In this paper, a venture capital lawyer, a medical researcher, and a bioengineer will establish the expected size of this reduction in supply, the associated harm resulting from this reduction, and discuss two promising technological solutions—bioprosthetics and 3D bioprinting of tissues and organs. In the case of both technologies, the authors will discuss the challenges and opportunities presented for institutional investors (private equity, venture capital, angel funds) and medical researchers in tackling the potential reduction in organ donations.

The Design of the Flyover Toll Plaza Model to Minimize the Construction Area of Toll Plaza

Now a day’s toll gates are very common on each and every national highway and users of these toll gates are paying the toll tax to the government or infrastructure companies. In the recent years the automobile technology has been developed lot, due to this reason the usage personal vehicles has been increased even though the public transportation system is available and traffic also has been increased on the roads in the recent years. Because of the increased traffic many roads are expanded according to the requirements and toll gates also are increased due to lack of sufficient time and funds with the government. These toll gates are occupying lot of agriculture land throughout the country. Many research articles focused on to reduced the traffic and electronic payment methods at toll gates, but this research article focused on the importance of the agriculture land and to minimize the construction area of tollgates and new model has been introduced to reduce the construction area of the toll plazas.

Reductions in CO2 Emissions from Passenger Cars under Demography and Technology Scenarios in Japan by 2050

Climate policy requires substantial reductions in long-term greenhouse gas (GHG) emissions, including in the transportation sector. As passenger cars are one of the dominant CO2 emitters in the transport sector, governments and the automobile industry have implemented various countermeasures, including decarbonization of fuels, more energy efficient vehicles, and transport demand management. However, the total impact of these measures in the long term remains unclear. This study aims to clarify the CO2 emissions reductions from passenger cars by 2050 in 1727 municipalities in Japan under a declining population. To estimate CO2 emissions, we model travel behavior and traffic situations reflecting the regional conditions of the municipalities, including population density and accessibility to public transport for the base year 2010. Assuming plausible scenarios for future populations and automobile technologies, we estimate CO2 emissions from passenger cars. We estimate that CO2 emissions will decline by 64–70% between 2010 and 2050, with automobile technologies playing the largest role. We find that the impact of urban compaction is marginal at the national level but varies by municipality. These results imply that, given regional variations, all countermeasures, including technology and demand management, must be used to achieve the long-term target of CO2 emissions reductions.

Front Vehicle Detection Algorithm for Smart Car Based on Improved SSD Model

Vehicle detection is an indispensable part of environmental perception technology for smart cars. Aiming at the issues that conventional vehicle detection can be easily restricted by environmental conditions and cannot have accuracy and real-time performance, this article proposes a front vehicle detection algorithm for smart car based on improved SSD model. Single shot multibox detector (SSD) is one of the current mainstream object detection frameworks based on deep learning. This work first briefly introduces the SSD network model and analyzes and summarizes its problems and shortcomings in vehicle detection. Then, targeted improvements are performed to the SSD network model, including major advancements to the basic structure of the SSD model, the use of weighted mask in network training, and enhancement to the loss function. Finally, vehicle detection experiments are carried out on the basis of the KITTI vision benchmark suite and self-made vehicle dataset to observe the algorithm performance in different complicated environments and weather conditions. The test results based on the KITTI dataset show that the mAP value reaches 92.18%, and the average processing time per frame is 15 ms. Compared with the existing deep learning-based detection methods, the proposed algorithm can obtain accuracy and real-time performance simultaneously. Meanwhile, the algorithm has excellent robustness and environmental adaptability for complicated traffic environments and anti-jamming capabilities for bad weather conditions. These factors are of great significance to ensure the accurate and efficient operation of smart cars in real traffic scenarios and are beneficial to vastly reduce the incidence of traffic accidents and fully protect people’s lives and property.

INVESTIGATION OF DIFFERENT LOW-COST LAND VEHICLE NAVIGATION SYSTEMS BASED ON CPD SENSORS AND VEHICLE INFORMATION

Abstract. Recently, many companies and research centres have been working on research and development of navigation technologies for self-driving cars. Many navigation technologies were developed based on the fusion of various sensors. However, most of these techniques used expensive sensors and consequently increase the overall cost of such cars. Therefore, low-cost sensors are now a rich research topic in land vehicle navigation. Consumer Portable Devices (CPDs) such as smartphones and tablets are being widely used and contain many sensors (e.g. cameras, barometers, magnetometers, accelerometers, gyroscopes, and GNSS receivers) that can be used in the land vehicle navigation applications.This paper investigates various land vehicle navigation systems based on low-cost self-contained inertial sensors in CPD, vehicle information and on-board sensors with a focus on GNSS denied environment. Vehicle motion information such as forward speed is acquired from On-Board Diagnosis II (OBD-II) while the land vehicle heading change is estimated using CPD attached to the steering wheel. Additionally, a low-cost on-board GNSS/inertial integrated system is also employed. The paper investigates many navigation schemes such as different Dead Reckoning (DR) systems, Reduced Inertial Sensor System (RISS) based systems, and aided loosely coupled GNSS/inertial integrated system.An experimental road test is performed, and different simulated GNSS signal outages were applied to the data. The results show that the modified RISS system based on OBD-II velocity, onboard gyroscopes, accelerometers, and CPD-based heading change provides a better navigation estimation than the typical RISS system for 90s GNSS signal outage. On the other hand, typical inertial aided with CPD heading change, OBD-II velocity updates, and Non-Holonomic Constraint (NHC) provide the best navigation result.

The climate change mitigation potential of sugarcane based technologies for automobiles; CO2 negative emissions in sight

Continuous effort to mitigate climate change relies onnew technologies able to satisfy human demand for energy services with high energy efficiency andreasonable costs. We show that blending a well-known technology with recently introduced and proven technical advances can mitigate climate change in the road transport sector. Furthermore, the achievement of a reasonable cost target is proved to be true when internal combustion engines (ICE) light duty vehicles (LDVs), powered by gasoline fuel, are replaced by plug-in hybrid LDVs (PHEV), powered by ethanol and electricity produced from sugarcane, using well established technology. The only improvements in such ethanol producing technology are the addition of woody biomass to extend the operation of sugar mills and the capture of carbon dioxide (CO2) generated during sugar fermentation into ethanol. Both actions are already adopted and well developed. The study quantifies greenhouse gas (GHG) emissions, expressed as carbon dioxide equivalent (CO2e) emissions and the present value cost for operation of a global fleet of 1 billion LDV over a 60-year period. The PHEV powered by sugar cane products reduces GHGs emissions partly through negative emissions, at a lower cost than gasoline fueled ICE vehicles or electric vehicles. Total potential GHG emission reduction is significant but lower than what is required for the transport sector to fulfill international commitments. Nevertheless, if 1 billion sugarcane-based PHEV hit the streets by the year 2060, 6.18 Gt CO2e/year can be avoided while the necessity of land for biomass plantation is kept at a reasonable value (86 Mha).

The Flying Car—Challenges and Strategies Toward Future Adoption

In recent years, our surface transportation infrastructure is suffering from overuse, extreme traffic congestion, and roadway disrepair. Instead of following the traditional infrastructure expansion policy, current transportation research focuses on developing innovative and novel solutions to the aforementioned issues. Current pathways to overcoming these issues include the gradual transition towards a number of emerging transportation technologies, such as, autonomous motor vehicles for human transport, as well as unmanned aerial vehicles (UAV’s) and drone technologies for surveillance, and package deliveries. However, as a long-term solution, transportation scientists are also investigating the once-seemingly futuristic notion of flying car technology - a convergent form of ground/air vehicle transportation, and assessing associated regulations. In this paper, an extensive review of current literature is conducted to explore the technological capabilities of flying cars – each requiring appropriate regulations and governance – to become fully sustainable. Specifically, issues pertinent to training, safety, environment, navigation, infrastructure, logistics/sustainability, and cybersecurity and human factors are explored. This paper concludes with a preliminary quantitative analysis exploring the public perceptions associated with flying cars – including anticipated benefits, concerns, and willingness to both hire and acquire the technology once available to consumers. Insights offered by this data will help inform next-generation policies and standards associated with the gradual advancement of flying cars.