Types Of Cars Research Articles

Economic implications of a phased‐in EV mandate in Canada

AbstractCanada plans to phase out internal combustion engine vehicle (ICEV) sales in favour of electric vehicles (EVs) by 2035 as part of its climate policy. Herein I examine the economic implications of a phased‐in electric vehicle mandate. I show using partial equilibrium analysis that when both types of cars are available, auto companies will overproduce electric vehicles and earn scarcity rents on internal combustion engine vehicles that partially offset the revenue loss on electric vehicles. I then present a numerical general equilibrium model of the Canadian economy to assess the overall macroeconomic consequences of the policy. The results depend critically on the assumed pace at which electric vehicles achieve cost parity with internal combustion engine vehicles on a quality‐adjusted basis. An electric vehicle mandate will have manageable economic consequences if technology improves so rapidly that the mandate is unnecessary. If the mandate outpaces achievement of cost parity the economic consequences can be severe and would likely cause the auto manufacturing sector to shut down. The cost per tonne of emission reductions are at least 10 times the Canadian carbon tax rate while the mandate is binding. The analysis provides insight into why automakers have been willing hitherto to develop and sell electric vehicles even though they currently lose money on them.

Improved of Process Production Disc Car Whell Type PSD3K (City Car Type)

This research accelerates the production process with the aim of increasing productivity from Manufacturers engaged in the manufacture of automotive parts currently experiencing an increase in sales orders on the other hand facing problems in productivity due to cracked side dies in rim production to 1400 pcs. The cracking of the side die is due to thermal shock that occurs to accelerate the production process, as a result of which cracks occur in the side die. With the concept of conducting research in the field of direct production then analyzing the characteristics of mold materials, die characteristics, process characteristics, characteristics of finished products before and after changes by testing the results of the laboratory of measuring instruments and conducting trials of variations in machine setting parameters, variations in the production process and products produced. The experiment involved changing the standard temperature from 520 °C–545 °C to 532 °C–538 °C and reducing the immersion time from a minimum of 270–540 seconds to 332 seconds. It reduces the soaking time from 69 seconds to 46 seconds and the aging time from 190 seconds to 180 seconds, increasing the casting productivity from 194,870 Pcs/28 days to 213,311 Pcs/28 days from seven machines, thus meeting the customer's requirement of 200,000 Pcs/28 days without cracking side die. Durability testing on five product samples in accordance with TSD5605G standards confirms that the quality meets customer specifications. The results of this study prove that SKD6 matrial is much stronger than FCD550 against thermal shock. Keywords: thermal shock, die disc car wheel, manufacturing, automotive parts, casting productivity

Artificial intelligence abnormal driving behavior detection for mitigating traffic accidents

Annually, a tragic toll of 1.3 million lives is lost on roads across the globe, with tens of millions more suffering injuries or disabilities. The necessity for precise detection of abnormal driving behavior is paramount in reducing traffic accidents. This paper aims to bridge the gap between normal and abnormal driving patterns, offering near-flawless detection capabilities. This paper presents a novel AI tachograph prototype, the first of its kind, that can classify driving behavior into normal and abnormal in real time with an impressive accuracy of 99.99 %. This high level of accuracy is achieved by using a bias-reduction method. The bias-reduction method focuses on minimizing biases in the dataset, such as surrounding situations, location, driver information, and car types. This approach significantly enhances the prediction accuracy of existing machine learning algorithms. The dataset used for this research is quite extensive, consisting of anomaly data collected from 10,181 commercial vehicles and 12,530 drivers in just 0.1 s. This rich dataset is crucial for building a reliable model. The effectiveness of the proposed method was validated using 10-fold cross validation on 480 k to 540 k instances with 36 determinants. The results clearly demonstrated that reducing bias leads to higher prediction accuracy. The paper also plans to compare the prediction accuracy of balanced and imbalanced datasets. The findings from this research have broader implications as the proposed method can be applied generally to machine learning to improve prediction accuracy.

Оценка уровней шума в Санкт-Петербургском метрополитене

Purpose: to assess the impact of noise levels in St. Petersburg metro cars. Identify what types of cars used on various metro lines. Determine what types of rolling stock cars used in the metro. Determine how much the service life of the cars affects the noise level in the car. Conduct measurements of noise levels inside the carriages of rolling stock of various types on various metro lines. Correlate the obtained values with the established requirements of SP 2.5.3650–20 “Sanitary rules for the operation of subways” with the values of maximum permissible noise levels in cars. Conduct an analysis of the level of noise impact on humans in the metro and identify possible measures to reduce the noise level in the metro. Methods: measurements of noise levels at various stations and trains were carried out by a special instrumental method, using a digital integrating meter and an Octave 110A sound spectrum analyzer of 1st accuracy class according to GOST R 53188.1. Results: measurements of noise levels carried out in various types of cars on various branches of the St. Petersburg metro. An analysis of the results of field measurements of noise levels for equivalent and maximum levels in the metro shows that permissible noise levels are exceeded in the “Baltiets” car on the red metro line, in car 81-717/714 on the blue metro line; in car 81-717/714 on the purple metro line; in car 81-556.2/557.2/558.2 “Neva” on the green metro line. Practical significance: identification of the obtained data show necessary measures to reduce noise in the metro. Installation of sound-absorbing materials at stations and on trains. Replacing old trains with newer ones.

Возможности интеграции функции обмена местами в мобильное приложение «РЖД пассажирам»

Railway transport is traditionally preferred when travelling between 400 and 1000 km. Depending on financial possibilities and personal idea of comfort, passengers choose different types of cars. Despite the fact that the passenger is familiarised with the conditions of travel in advance (at the time of ticket purchase), requests to change seats with fellow travellers are often noted at the moment of boarding, which complicates the work of the car conductor, provokes violation of the Rules of Passenger Transportation and causes discomfort to persons with whom the passenger wants to agree on such an exchange. Despite the de facto existence of the problem, the carrier does not have statistical data on passengers' perception of seat exchange requests. This paper examines the need to introduce an additional parameter in the menu of the mobile application "RZD to Passengers" to enable early legitimate seat exchange in purchased tickets with provision for compensation for the passenger who expresses consent to the exchange in the incoming request. As a methodology of the research a set of methods of analysis, synthesis, deduction and induction was used. The author proposes to improve the quality of passenger service of long-distance trains by preventive solution of the issue of seat exchange, thereby eliminating the probability of conflict situations during the journey and reducing the number of violations of the Rules of Passenger Transport. This article may be of practical interest to companies providing passenger transport services on long-distance trains (e.g. JSC FPC, TC Grand Service Express, LLC Tverskoy Express).

Attribute annotation and bias evaluation in visual datasets for autonomous driving

This paper addresses the often overlooked issue of fairness in the autonomous driving domain, particularly in vision-based perception and prediction systems, which play a pivotal role in the overall functioning of Autonomous Vehicles (AVs). We focus our analysis on biases present in some of the most commonly used visual datasets for training person and vehicle detection systems. We introduce an annotation methodology and a specialised annotation tool, both designed to annotate protected attributes of agents in visual datasets. We validate our methodology through an inter-rater agreement analysis and provide the distribution of attributes across all datasets. These include annotations for the attributes age, sex, skin tone, group, and means of transport for more than 90K people, as well as vehicle type, colour, and car type for over 50K vehicles. Generally, diversity is very low for most attributes, with some groups, such as children, wheelchair users, or personal mobility vehicle users, being extremely underrepresented in the analysed datasets. The study contributes significantly to efforts to consider fairness in the evaluation of perception and prediction systems for AVs. This paper follows reproducibility principles. The annotation tool, scripts and the annotated attributes can be accessed publicly at https://github.com/ec-jrc/humaint_annotator.

Strategic decision-making for sustainable production and distribution in automotive industry: a machine learning enabled dynamic multi-objective optimisation

ABSTRACT Over the last decade, numerous researchers have disclosed that major automotive companies do not conform to regulatory or societal expectations regarding their environmental and social performances. This paper explores the dynamic capabilities of production distribution within the sustainability practices of automotive industries. It offers insights to better grasp and articulate the environmental, economic, and social dimensions of sustainable supply chains. The research framework encloses all supply chain phases, from raw material sourcing to retailing finished products. Three conflicting objective functions are identified: social advantages maximisation, cost minimisation, and emission minimisation. Specifically, the study tackles a dynamic multi-objective optimisation model where each automobile type faces a series of dynamic demands. The dynamic nature of the problem poses significant challenges to conventional evolutionary algorithms for detecting the optimal solutions over time. Therefore, we introduce an interconnected prediction-based dynamic non-dominated sorting algorithm (ICP-DNSGA-II). Finally, extensive computational experiments are conducted to assess the effectiveness of this holistic approach. The findings offer valuable insights for automotive industry stakeholders and policymakers, illustrating its potential to enhance operational efficiency and sustainability performance across the supply chain. Most importantly, this paper proposes an automated decision-making approach to generate optimal solutions with dynamic changes in market demands.

Change in the collision avoidance performance of autonomous emergency braking systems

Objective This study quantifies the change in collision avoidance performance of autonomous emergency braking (AEB) systems for traffic accidents in Japan since 2015. Method This study used data on Japanese traffic accidents compiled by Japan’s National Police Agency. The data included only accidents involving loss of or injury to human life; accidents involving only property damage were excluded. We restricted our analysis to collisions between two 4-wheel vehicles and considered only collisions for which we could determine whether the primary party’s car was equipped with an AEB system. Both Poisson and negative binomial mixed-effects regression analyses were conducted using the data for 2021 and 2022 to measure the collision avoidance performance of first registered cars in 2015 to 2020 equipped with AEB systems compared with cars without AEB systems first registered in 2015. Collision avoidance performance was measured for 2 types of intervehicle collisions: rear-end collisions and right-turn collisions. Collision avoidance performance for rear-end collisions was also measured for each of the 3 car types—Standard, small, and light cars. Results The collision reduction rate for rear-end collisions increases with the year of first registration and for cars equipped with AEB systems first registered in 2020 compared with non-AEB-equipped cars first registered in 2015 is 69.2% (95% confidence interval [CI] 67.0%–71.1%), indicating that the performance of AEB systems has dramatically improved in terms of preventing rear-end collisions. For right-turn collisions, the rate increased to 20.4% (95% CI 5.9%–32.6%) for cars equipped with AEB systems first registered in 2019. However, no clear trend is observed. Conclusions This study evaluated a time series of the collision reduction performance of AEB systems using an original methodology. Japan’s New Car Assessment Program (JNCAP) has included AEB’s effectiveness in reducing damage from traffic collisions as an evaluation item since FY2014. The results could demonstrate the effectiveness of JNCAP.

Robust and low-cost open-source device for detecting infectious microorganisms by loop-mediated isothermal amplification

Loop-Mediated Isothermal Amplification (LAMP) is a useful technique for detecting infectious microorganisms in human fluids since it performs similarly to conventional PCR, the results are obtained faster and no thermocyclers or complex devices are required. Since only two isothermal blocks (95 °C to lyse cells and 65 °C for DNA amplification) are needed, LAMP is particularly suited for applications in Low- and Middle-Income Countries (LMICs). To validate such assumption, we first designed and tested Arduino-controlled LAMP thermoblocks to process a considerable number of samples simultaneously with a low-energy consumption to enable routine use under worst-case conditions (no main power source and low ambient temperatures).The thermoblocks were tested when battery-powered at temperature down to 5 °C, showing high stability in well temperatures (<0.8 °C). The charge required for both thermoblocks to simultaneously achieve the target temperatures after switching on and to keep their working temperatures were 4.1 A·h and 2.4 A·h/h, respectively. Second, we implemented a low-cost viewer with LEDs and filters to detect the fluorescent LAMP reaction. All the components required for the instrument are for general purpose and readily available by e-commerce. Thus, the LAMP device allows for considerable autonomy by using a typical car battery in rural and itinerant healthcare or field hospitals in LMICs, even under difficult environmental conditions.

Correlation between carbon emissions, fuel consumption of vehicles and speed limit on expressway

This paper aimed to investigate the correlation between carbon emissions, fuel consumption, and speed limit. A theoretical model was derived based on the energy conservation law, which expresses the relationship between vehicle's fuel consumption and speed. Subsequently, a total of 40 sets of fuel consumption data were collected through field tests to verify the accuracy of the theoretical model at different speeds and different road longitudinal slope combinations. The fuel consumption was then converted to carbon emissions according to the carbon emission factors specified by Intergovernmental Panel on Climate Change (IPCC). In the field experiment, two types of cars and trucks, which are most common on the expressways in China, were selected. Finally, the travel speed under different posted speed limits was obtained through the previously established model, and the carbon emission changes of different vehicle types at different limited speeds are calculated. The results show that the speed limit has a significant impact on fuel consumption and carbon emissions. When the speed limit increased from 80 to 120 km/h, average vehicle speeds increased about 21%–27%, and fuel consumption and carbon emissions increased from approximately 33%–38%. Another interesting result was that the vehicle's fuel consumption and carbon emissions are only affected by speed. The results of the study explore the effect of speed limits on carbon emissions and provide evidence for road managers to set reasonable speed limits.

Comparative analysis of real-world vehicular emissions from BS-IV and BS-VI cars in India.

This study investigates real-world carbon dioxides (CO2) and nitrogen oxides (NOx) emissions from diesel (Bharat Stage-IV (BS-IV)) and petrol/gasoline (BS-IV and BS-VI) cars in Indian driving conditions using a portable emission measurement system (PEMS). The paired sample t-test revealed a significant difference ( < 0.05) in NOx and CO2 emissions among the three types of cars, except for CO2 emissions ( > 0.05) between BS-IV petrol and BS-VI petrol cars. The highest NOx emission rates were observed in all car types during acceleration (> 1m/s2) and deceleration (- 2m/s2). CO2 emission rates were also high during acceleration (> 1m/s2) for all car types. At low speeds (around 20 kmph), all car types had low emissions of CO2 and NOx, with acceleration and deceleration rates ranging from - 0.5 to 0.5m/s2. BS-IV diesel cars emit significantly higher NOx emissions compared to petrol cars, especially at vehicle-specific power (VSP) bin 0 (deceleration to idling mode) and during VSP bin 7 (acceleration mode). BS-IV diesel cars emit 228% and 530% higher NOx emissions than BS-IV and BS-VI petrol cars at VSP bins 0 and 7, respectively. CO2 emissions from BS-VI petrol cars were 10% lower than those from BS-IV petrol cars across all VSP bins, indicating moderate reductions. Furthermore, diesel cars emit 140% less CO2 emissions than petrol cars across various VSP bins. The findings highlight the need for cleaner technologies and responsible driving practices to address vehicular emission concerns.

Exploring the Potential of DNA Computing for Complex Big Data Problems: A Case Study on the Traveling Car Renter Problem.

The traveling car renter problem (TCRP) is a variant of the Traveling Salesman Problem (TSP) wherein the salesman utilizes rented cars for travel. The primary objective of this problem is to identify a solution that minimizes the cumulative operating costs. Given its classification as a non-deterministic polynomial (NP) problem, traditional computers are not proficient in effectively resolving it. Conversely, DNA computing exhibits unparalleled advantages when confronted with NP-hard problems. This paper presents a DNA algorithm, based on the Adleman-Lipton model, as a proposed approach to address TCRP. The solution for TCRP can be acquired by following a series of fundamental steps, including coding, interaction, and extraction. The time computing complexity of the proposed DNA algorithm is O(n2m) for TCRP with n cities and m types of cars. By conducting simulation experiments, the solutions for certain instances of TCRP are computed and compared to those obtained by alternative algorithms. The proposed algorithm further illustrates the potential of DNA computing, as a form of parallel computing, to address more intricate large-scale problems.

Bearing Steel Structures for Installation of Railway Strain Gauge Scales

Purpose. The main purpose of the publication is to compare the main technical and economic indicators of the two proposed structural variants of the support system for railway strain gauge scales for four-axle wide gauge railcars. This is due to the need to reconstruct and modernize the fixed assets of an industrial enterprise, in particular, to overhaul and replace old railway scales with modern electronic strain gauge scales. Also, the purpose of the work is related to the need to expand the range of railway cars for which the possibility of weighing is provided, including transport units of the foreign car fleet. Methodology. To achieve this goal, we analyzed the modern types of railroad cars for freight transportation, determined the main components of strain gauge scales for weighing the main types of cars, and developed a special support system to support the scale platform. The support system is provided in two design variants - with one spatial support frame and two separate flat support frames. Using the domestic design and computing complex SCAD, we built finite element models for both proposed design options. Based on the analysis of their stress-strain state, rational cross-sections were selected for each structural element, and the total mass was determined. Findings. A comparative analysis of the two developed structural solutions for the support system for modern railway strain gauges has revealed that the variant with two separate bearing frames has a lower weight by about 40 % compared to the variant with one spatial bearing frame. However, the manufacturability of its production is somewhat lower, since it involves 10 structural elements compared to 7 for variant No. 1. Originality. The numerical analysis made it possible to theoretically substantiate a more rational and efficient design solution for the support system for modern railway strain gauge scales. Practical value. A constructive variant of the steel support system has been developed and proposed for practical implementation, which is the most effective in terms of its technical and economic indicators for the existing conditions of an existing industrial enterprise. The developed design option was also coordinated with the project of major reconstruction of the building for weighing railroad cars.

A REVIEW ON HYBRID ELECTRIC VEHICLES USING VARIOUS ENERGY STORAGE: A MODERN APPLICATION OF RENEWABLE ENERGY SOURCES

Climate change, diminishing reserves of fossil fuels, and energy security demand alternatives to our current course of energy usage and consumption. Energy storage technology has become an enabling technology for renewable energy applications and enhancing power quality in the transmission and distribution power systems. There are various types of energy storage technology are present nowadays, including compressed air energy storage(CAES), flywheel energy storage(FES), pumped hydro energy storage(PHES), battery energy storage(BES), flow battery energy storage(FBES), super conducting magnetic energy storage(SMES), super capacitor energy storage(SCES), hydrogen energy storage, synthetic fuels, and thermal energy storage(TES) and today’s one of the most talked technology using these Energy storage system is Electric Vehicles. Electric vehicles are superior to internal combustion engines (ICE) in efficiency, endurance, durability, acceleration capability and simplicity. Also, they can recover some energy during regenerative braking and they are also friendly with the environment. There are now four types of electric cars: battery electric vehicles (BEVs), plug-in hybrid electric vehicles (PHEVs), conventional hybrid electric vehicles (HEVs), and fuel-cell electric vehicles (FCEVs). And there are three charging methods for electric vehicles, namely conductive, inductive, and battery exchange. This paper will show a detail study of different energy storage systems’ characteristics with their suitability as a storage unit of Electric vehicle.

ОБОСНОВАНИЕ КОНСТРУКЦИИ КРЫТОГО ГРУЗОВОГО ВАГОНА С УВЕЛИЧЕННЫМ ОБЪЕМОМ ГРУЗОВОГО ПОМЕЩЕНИЯ

The market of covered freight cars, as well as existing designs of this car type of domestic and foreign production is analyzed. Promising trends of making innovative designs of freight cars for the transportation of piece and container goods are found out. The original design of a covered freight car with an increased body space due to the use of the space between trucks is proposed. To reduce the complexity of loading and unloading operations, sliding sections of the side walls and roof are provided in the car design. To confirm the compliance of the proposed design with the requirements of regulatory and technical documents, the car was entered into the dimension, checking for automatic coupling at the junction of a straight line and a curve, passage in the coupling of an s-shaped curve and coupling of a straight line and a curve, and a single car along a circular curve of a small radius, as well as passing without self-decoupling of the hump of the sorting slide, the ramp exit of the train ferry. A safety assessment is carried out with regard to rolling the wheel onto the rail and overturning the car in curves. The car dynamic characteristics are found out by mathematical modeling methods. The assessment of the strength of the body load-bearing structure, lifting mechanisms of the floor sections, sliding sections of the roof and side walls is performed using the finite element method implemented in the environment of a specialized software package. The results obtained as a result of calculations and computer modeling confirmed the operability and safety of the proposed design of a covered freight car with an increased loading space.

Electric Vehicle Charging Infrastructure Study for Apartment Buildings

Changes in the engine type of cars aimed at climate goals also have an impact on the habit of electricity consumption at home. Charging electric cars from the residential grid also increases the total electricity consumption of the residential building. If all apartment owners in an apartment building want to charge their electric car at the same time, this may create a situation where the main protection of the apartment building is activated. The purpose of this research is to identify possible options to avoid this problem, based on different real-life data. For example: adding an energy storage to the electrical system of an apartment building is seen as one solution. Also supplement of an energy management software to the electrical and battery bank system to enables residents to schedule and prioritize their electric car charging times to avoid simultaneous high-demand periods. This system can also be used to optimize electricity distribution and consumption in apartment buildings under volatile electricity price conditions.

Rentro (Travel Anywhere)

Rentro (Travel Anywhere) Website is a project which aims in developing a computerized system to reduce the Rental problem facing by the tourists to take vehicles on rent after reaching that place. .This project has many features which are generally Not available at regular car rental stores , like facility of customer login and a facility of admin login .It also has a facility of admin login through which the admin can monitor the whole system .It also has facility of an online notice board where Admin can put up information about the cars available in the exhibition and their prices and updating all data that go through the rental process. It has also a facility where users after logging in their accounts can see the list of cars and its price and Availability of the car and also the customer can request the admin to add new type of cars by filling the cars request form. The admin after logging into his account can generate various reports such as cars report, users/ customer report. Overall, this project of ours is designed to help anyone make it easier during the process of buying or renting a car in the best possible way, as well as reducing human efforts and obtaining the best offers.

Using mobile devices for driving test assessment: a study of acceleration and GPS data

ABSTRACT There is a need to improve the validity of the driving test as a measure of an individual’s ability to drive safely. This paper explores the use of algorithms to analyze acceleration and GPS data from a smartphone and a GoPro to distinguish between different driving styles, as performed by experienced examiners portraying stereotypical driving test candidates. Measures from nine driving tests were analyzed, including (harsh) accelerations, jerk, mean speed, and speeding. Results showed that the type of car, instructed driving style, and driving route impacted the dependent measures. It is concluded that GPS and accelerometer data can effectively distinguish between cautious, normal, and aggressive driving. However, it is important to consider additional sensors, such as cameras, to allow for more context-aware assessments of driving behavior. Furthermore, we demonstrate methods to quantify variations in road conditions and provide suggestions for presenting the data to driving examiners.

Design and Analysis of the Exhaust Muffler for Two-Wheeler Vehicle

The muffler is an essential part of every type of car. On two-wheelers, however, it disperses flue gases throughout the atmosphere and reduces engine noise to a bearable level. It is occasionally called an exhaust muffler or a muffler. A silencer's main function is to block off noise produced when flue gas rushes past it quickly. Furthermore, the exhaust gases ought to be released into the atmosphere. The primary focus of this work is on two-wheeled vehicle exhaust mufflers. The current exhaust silencer design is subjected to CFD and fluid structure interaction analysis with engine-specific boundary conditions. The specifications will guide the creation of the muffler's design. ANSYS, a finite element analysis tool is used to measure and verify exhaust gas temperatures, velocities, and back pressure. Furthermore, a modal analysis is conducted to figure out how a geometric adaptation affects the fundamental frequency of the system. The actual testing consists of fabricating a customized exhaust silencer and evaluating it for noise and back pressure on a two-wheeler engine test rig.

Multi-objective green vehicle scheduling problem considering time window and emission factors in ship block transportation

Logistics distribution is one of the main sources of carbon dioxide emissions at present, and there are also such distribution problems in the shipbuilding process. With the increasing attention paid to environmental problems, how to effectively reduce the energy consumption of block transportation and improve the utilization rate of resources in the factory is the key problem that China’s shipbuilding industry needs to solve at present. This article considers the time windows for block transportation tasks, as well as the self-loading constraints of different types of flat cars, and establishes an optimization model that minimizes the empty transport time and energy consumption of the flat cars as the optimization objective. Then, an Improved Genetic Whale Optimization Algorithm is designed, which combines the cross and mutation ideas of genetic algorithms and proposes a whale individual position updating mechanism under a mixed strategy. Furthermore, the performance and computational efficiency of the algorithm are verified through comparative analysis with other classical optimization algorithms on standard test examples. Finally, the shipyard’s block transportation example proves that the energy-saving ship block transportation scheduling method can effectively improve the efficiency of shipbuilding enterprise’s block transportation and reduce the energy consumption in the block transportation process. It proves the engineering practicality of the green dispatching method proposed in this paper, which can further provide a decision-making method for shipyard managers.