Today's Vehicles Research Articles

CNOSSOS-FR: Are current road traffic noise emission coefficients still representative of today's vehicle fleet and roads?

CNOSSOS-EU is the common noise prediction method for producing strategic noise maps in Europe, according to Directive 2002/49/CE. Its road vehicle noise emission model involves a propulsion noise component and a rolling noise component, with coefficients specific to each vehicle category. As currently applied in France, it relies on the original EU coefficients published in the 2015 CNOSSOS-EU version and the rolling noise contribution is detailed in road surface classes in agreement with the national NMPB2008 method. As provided in the European method, corrective coefficients in frequency bands were determined per road surface class. The objective was to minimise the overall difference between NMPB2008 and CNOSSOS-FR emission predictions under similar conditions, the former method being previously used for periodic mapping. Now considering the later release of new EU reference coefficients and the difficulty of making the two methods involving different expressions and assumptions coincide, as well as questioning the need to update emission values resulting from measurements of the vehicle fleet taken 20-25 years ago, the study MINOOS is being carried out to assess the noise emission of the current vehicle fleet and reconsider French prediction coefficients accordingly. The paper describes the procedure and presents the first results.

Advanced Innovations in Electronic Control Units: Enhancing Performance and Reliability with AI

This paper proposes a methodology for the design of electronic control unit (ECU) hardware units with increased performance and reliability. Today's vehicles are equipped with dozens of ECUs that significantly influence the system's efficiency, reliability, performance, and safety. With the increased complexity of control algorithms and the environmental constraints that automotive systems operate, the robustness and efficiency of the ECUs are of utmost importance. In this work, an approach is proposed based on combining hardware redundancy, commercial field programmable gate arrays (FPGAs), and artificial intelligence strategies to provide increased redundancy checks and robust control. An additional redundancy is added to the hardware architecture of the ECU to include a parallel hardware unit. The two controlling units operate in parallel. The output of each of them is compared, allowing redundancy checks in the computation of the output variable (oV) of the system. The mathematical model of the ECU depicts the governing equations of the ECU in the form of differential equations, which results in a corresponding state-space configuration. These mathematical models are encoded into the field programmable gate array (FPGA) and processed in hardware, leading to an equivalent software-based implementation. To analyze the performance of both models within the ECU, an artificial neural network (ANN)-based strategy is proposed. The ANN depicts the governing equations of the ECU in the form of differential equations encoded in the form of sigmoidal functions. To analyze the reliability of the control action in the ECU, the temperature of the system is increased, which leads to a random variation of the system parameters. The variability of the ECU parameters leads to a deviation in the computation of the oV and the corresponding control action. The robustness of the control is determined in such conditions. A control law is determined to guarantee proper control action under variations in the governing equations of the system. This control law is represented by a simple algebraic equation, which can then be cast in various control strategies, such as look-up tables or fuzzy logic controllers. Several cases are simulated to assess the performance of the proposed control law for the hardware redundancy scheme, for the ANN-based equivalent software implementation approach, and for the additional fuzzy logic controller. The simulation results are analyzed concerning the requested oV and give insight into the performance and reliability of the proposed dedicated ECU design.

İki Farklı Reçine Kullanılarak Oluşturulan Hibrit Kompozit Malzemelerin Araç Tamponlarında Kullanımının Araştırılması

As efforts to reduce vehicle weight in today's vehicles accelerate, efforts to find new types of materials that can replace traditional materials have accelerated. In this study, carbon fiber was used as a reinforcement element together with glass fiber for lightening in vehicle bumpers. While vinyl ester and polyester were chosen as the matrix material for the piece to be produced, production was made by the hand lay-up method. The produced samples were first subjected to tensile test and their mechanical values were determined. The mechanical test results were introduced to the ANSYS program, and separate analyzes were made for the materials produced on the same bumper design and the results were compared. According to the results of the analysis, there was 2.13 times decrease in total deformations in glass fiber/carbon fiber/Vinyl ester hybrid composites compared to glass fiber/vinyl ester homogeneous composites. In terms of equivalent stresses, 8% reduction was achieved in the carbon fiber /glass fiber/Vinyl ester hybrid composite compared to the carbon/Vinyl ester homogeneous composite. It was concluded that the choice of reinforcement and matrix is important for creating bumper material and improving the mechanical values of the bumper

The evolution of embedded systems in automotive industry: A global review

The evolution of embedded systems in automotive industry: A global review

Thermoplastics For Up To 1,200 Degrees Celsius

On January 17, 2024, Freudenberg Sealing Technologies announced offering a new class of materials, intended to improve fire protection in electric vehicle drives. Its name is “Quantix ULTRA” and it reportedly resists melting even at extreme temperatures of up to 1,200 degrees Celsius. Processing the material in injection molding is claimed to be both versatile and economical. Given that today's vehicles call for lightweight construction, its lower density compared to metallic materials should be an advantage. The first series application is now underway, as a flame protection barrier for cooling system parts in an electric car's lithium-ion battery.

Validation of automotive centrals using hardware in the loop -BCM and Lights

The race for electrification and the need for innovation to attract customers has driven the automotive industry to do something different in vehicles, emerging emission control challenges and efficient technological availability are the pillars of innovation. With the need to upgrade industrial manufacturing systems, directly impacting vehicle production, established the search for new prototyping methodologies and use of virtual tools for testing, validation of components and vehicle systems are developed. The demand for electronic components controls units (ECU) is growing, due to the availability of intelligence and security in today's vehicles, directly impacting their development and the performance and functionality tests. To meet this new reality, in addition to the automotive test prototypes used during development, the automotive industry has been using different virtual environments to produce, verify, and validate its vehicles. Therefore, this paper applied integration and validation using the HIL test platform, focusing on the ECU Body Control Unit (BCM), analyzing its functionalities and possible failures of the internal and external light loads. After, a brief commentary will be made exposing other test medium platforms given as the Plywood Buck (PWB), checking the reliability, flexibility, installation time, and costs of the three test platforms Software in the loop (SIL), Model in the loop (MIL) , Hardware in the loop (HIL), in order to verify their advantages, challenges, and problems in the use and information to optimize the use of each platform and test medium.

Validation of Automotive Centrals Using Hardware in the Loop-Body Control Unit and Lights

The race for electrification and the need for innovation to attract customers has led the automotive industry to do something different with vehicles. New emissions control challenges and efficient technological availability are the pillars of creation. The growing demand to upgrade industrial manufacturing systems creates actions that directly impact vehicle production. With this comes the search for new prototyping methods and virtual tools for component testing and validation, and vehicle systems have established themselves. The demand for Electronic Control Units (ECU) is increasing due to the availability of intelligence and safety in today's vehicles, directly affecting their development, performance, and functional testing. In order to keep up with global changes, the automotive industry uses different virtual environments to produce, verify and validate their vehicles and test prototypes used during development. Therefore, in this paper, integration and validation were performed using the Hardware in the Loop (HIL) test platform, focusing on the ECU Body Control Unit (BCM). Then, a brief commentary reviews other test medium platforms, such as the Plywood Buck (PWB), and examines the reliability, flexibility, installation time, and cost of the three test platforms, software in the loop (SIL), Model in the loop (MIL), and HIL, to review their benefits, challenges, and issues in use and information to optimize the use of each platform and test medium.

Identification of traffic signs for advanced driving assistance systems in smart cities using deep learning.

The ability of Advanced Driving Assistance Systems (ADAS) is to identify and understand all objects around the vehicle under varying driving conditions and environmental factors is critical. Today's vehicles are equipped with advanced driving assistance systems that make driving safer and more comfortable. A camera mounted on the car helps the system recognise and detect traffic signs and alerts the driver about various road conditions, like if construction work is ahead or if speed limits have changed. The goal is to identify the traffic sign and process the image in a minimal processing time. A custom convolutional neural network model is used to classify the traffic signs with higher accuracy than the existing models. Image augmentation techniques are used to expand the dataset artificially, and that allows one to learn how the image looks from different perspectives, such as when viewed from different angles or when it looks blurry due to poor weather conditions. The algorithms used to detect traffic signs are YOLO v3 and YOLO v4-tiny. The proposed solution for detecting a specific set of traffic signs performed well, with an accuracy rate of 95.85%.

An ML-Aided Reinforcement Learning Approach for Challenging Vehicle Maneuvers

The richness of information generated by today's vehicles fosters the development of data-driven decision-making models, with the additional capability to account for the context in which vehicles operate. In this work, we focus on Adaptive Cruise Control (ACC) in the case of such challenging vehicle maneuvers as cut-in and cut-out, and leverages Deep Reinforcement Learning (DRL) and vehicle connectivity to develop a data-driven cooperative ACC application. Our DRL framework accounts for all the relevant factors, namely, passengers' safety and comfort as well as efficient road capacity usage, and it properly weights them through a two-layer learning approach. We evaluate and compare the performance of the proposed scheme against existing alternatives through the CoMoVe framework, which realistically represents vehicle dynamics, communication and traffic. The results, obtained in different real-world scenarios, show that our solution provides excellent vehicle stability, passengers' comfort, and traffic efficiency, and highlight the crucial role that vehicle connectivity can play in ACC. Notably, our DRL scheme improves the road usage efficiency by being inside the desired range of headway in cut-out and cut-in scenarios for 69% and 78% (resp.) of the time, whereas alternatives respect the desired range only for 15% and 45% (resp.) of the time. We also validate the proposed solution through a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">hardware-in-the-loop implementation</i> , and demonstrate that it achieves similar performance to that obtained through the CoMoVe framework.

Automation Acceptance Risk Assessment: stakeholders’ consultation and mitigation plans

Today's vehicles - in all modes of transport - are becoming increasingly connected and cooperative, as well as automated, raising a number of issues about the role of the "driver" of all kinds (i.e. operator, rider, pilot, captain) in such vehicles. In order to increase the public's acceptance of AVs, it is important to understand which factors significantly affect it. This is also the scope of this paper that presents the identified risks towards the user acceptance of AVs, as they have been primarily identified by internal and external (to the project) experts and as they have been also confirmed by the H2020 Drive2theFuture project technical and piloting activities.

State-of-the-art survey of in-vehicle protocols and automotive Ethernet security and vulnerabilities.

With the help of advanced technology, the automotive industry is in continuous evolution. Modern vehicles are not only comprised of mechanical components but also contain highly complex electronic devices and connections to the outside world. Today's vehicle usually has between 30 and 70 ECUs (Electronic Control Units), which communicate with each other over standard communication protocols. There are different types of in-vehicle network protocols and bus systems, including the Controlled Area Network (CAN), Local Interconnected Network (LIN), FlexRay, Media Oriented System Transport (MOST), and Automotive Ethernet (AE). Modern cars are also able to communicate with other devices through wired or wireless interfaces such as USB, Bluetooth, Wi-Fi or even 5G. Such interfaces may expose the internal network to the outside world and can be seen as entry points for cyber-attacks. In this paper, the main interest is in the AE network protocol. AE is a special Ethernet design that provides the bandwidth needed for today's applications, and the potential for even greater performance in the future. However, AE is a "best effort" protocol, which cannot be considered reliable. This implies that it is not trustworthy in terms of reliability and timely deliveries. The focus of this paper is to present a state-of-the-art survey of security threats and protection mechanisms relating to AE. After introducing and comparing the different protocols being used in the embedded networks of current vehicles, we analyze the potential threats targeting the AE network and describe how attackers' opportunities can be enhanced by the new communication abilities of modern cars. Finally, we present and compare the AE security solutions currently being devised to address these problems and propose some recommendations and challenges to deal with security issue in AE protocol.

Roadmap for Cybersecurity in Autonomous Vehicles

Autonomous vehicles are on the horizon and will be transforming transportation safety and comfort. These vehicles will be connected to various external systems and utilize advanced embedded systems to perceive their environment and make intelligent decisions. However, this increased connectivity makes these vehicles vulnerable to various cyber-attacks that can have catastrophic effects. Attacks on automotive systems are already on the rise in today's vehicles and are expected to become more commonplace in future autonomous vehicles. Thus, there is a need to strengthen cybersecurity in future autonomous vehicles. In this article, we discuss major automotive cyber-attacks over the past decade and present state-of-the-art solutions that leverage artificial intelligence. We propose a roadmap toward building secure autonomous vehicles and highlight key open challenges that need to be addressed.

Performance Comparison of Ultrasonic Sensor Accuracy in Measuring Distance

Digital technology is now very sophisticated. Its use is widely applied in all areas of human life. Starting from waking up, human activities and others always use technology. In carrying out their activities, modern humans now almost all use vehicles as a mode of transportation. Today's vehicles use a variety of sensors as a sixth sense. The results of detection using sensors on the vehicle are usually displayed on the dashboard of the vehicle. Modern humans currently use sensors to complete their needs. Besides that, the internet of things technology is growing rapidly in its role and development to support the needs of modern humans. Micro-controller technology is also experiencing rapid and massive development. One of the most common and most popularly used microcontrollers is Arduino. In many streets in Indonesia, people still use vehicles not equipped with many sensors. One of them is a simple parking sensor that many old vehicles don't have. Parking sensor problems are needed at the time of parking so that the vehicle that will be parked does not hit other objects or vehicles. There are many types of ultrasonic sensors. The purpose of this research is to make a prototype ultrasonic sensor that is applied to vehicles and compare some of the most accurate ultrasonic sensors in measuring the distance between the vehicle and the object being measured.

PENGUJIAN PERBANDINGAN KETAHANAN BERBAGAI BUSI SEPEDA MOTOR DENGAN MENGGUNAKAN ALAT BUSI TESTER

The development of automotive technology is very fast, we can find this in today's vehicles that use a lot of very sophisticated technology, namely in terms of engines, electricity, and its newest features, especially on two-wheeled vehicles. Therefore, the user community is required to be more selective in choosing a vehicle both in terms of quality and quantity. Including in the selection of spare parts on vehicle engines must use good quality, this is useful as a motorbike power booster, especially in the ignition system, namely spark plugs as a vital tool that sprinkles sparks in the combustion chamber. Recently, many spark plugs have been found that are not good enough so that the power generated by the vehicle is reduced. The purpose of this test is as a Comparative Test of the Endurance of Various Motorcycle Spark Plugs by using a spark plug tester so that it can be seen that the spark plug is suitable or not used in the vehicle which aims to get maximum performance.

Heuristic‐Based Architecting for Autonomous Vehicle Systems

AbstractHumans have always had a need to improve travel, whether that be for ourselves or for the goods we need. Technological advancements have all fundamentally performed the task of moving people and goods with the objective to continuously improve convenience and be more efficient. There is another pending revolution in human mobility, one that is leading towards autonomous transportation where the human driver is replaced, and the driving of the vehicle is performed autonomously by machine. With continued research and technology, automotive original equipment manufacturers (OEMs) have started to implement autonomous enabled features to transform today's vehicles traveling our roads into driverless vehicles. This paper evaluates the fundamental problem of architecting a system responsible of transporting occupants and cargo from point A to point B via autonomous vehicles (AVs) and compares it to current architecture being proposed/produced by OEMs. The work begins by studying the user needs of an AV and mapping those needs to required system functions. Then, guiding heuristics and lessons learned are used to critique the current architecture. The results show that the current OEM approach is to simply create smarter vehicles within a non‐intelligent infrastructure, and the authors, when guided by system architecting heuristics, suggest that development of an elegant, robust, long‐term AV system will require a significant increase in scope to a higher system level than the OEMs appear to be addressing at the present time.

Farklı Malzemelerle Biyel Kolunun Deformasyon ve Gerilme Analizi

Today's vehicle technology is based on internal combustion engines. However, hybrid models have been introduced to the market in recent years. The purpose of these models is to reduce fuel consumption. Hybrid vehicles are based on the principle of simultaneous operation of an electric and gasoline engine. According to this working principle, it is predicted that the use of internal combustion engines will continue for a long time. For these reasons, studies on fossil fuel-powered engines are still ongoing and are expected to continue in the future. Appropriate design and material selection come to the fore in studies on the engine and the machine elements that make up the engine. Therefore, it is the design and the suitability of the material used and the weight that should be considered in the production of the parts that make up the engine. The most important part to be considered while designing the engine elements is to maximize the effect of the engine on the vehicle, namely the performance, and to carry out the necessary studies to reach this level. For this, the design of the elements that make up the engine and the connecting rod, which is the subject of this study, is of great importance. Although the design factor in a connecting rod alone, which is a part of the engine and is expected to withstand the stresses formed in the engine, does not seem to be effective, the performance of the engine in terms of design and therefore weight is also affected by this situation. In this study, necessary analyzes were made in terms of performance by designing the connecting rod. Using four different materials; aluminum alloy, titanium alloy, steel alloy and cast iron, connecting rods designed using an ANSYS Workbench software were analyzed. In the analysis, studies on stress and deformation were carried out. As a result, it was concluded that the aluminum alloy material is the most suitable design in terms of both weight and material supply.

WIRELESS CHARGING OF BATTERY

In reaction to the depletion of natural resources, electric vehicles offer a viable alternative. Practical and dependable methods to charge EV batteries are crucial in order to boost the usage of EVs in daily life, and wireless power transfer (WPT) is being investigated as a solution to charge batteries. In this project, a wireless charger prototype system is built and implemented. The necessity for a cable and plug charger, galvanic separation of the onboard electronics, weight, and cost of this charger, and massive energy storage system (ESS) packs are all present in today's electric vehicles. This paper has designed and developed an antenna system suitable for vehicles using resonant magnetic coupled wireless power transfer technology to an electric vehicle charging system. The use of WPT in EVs provides a clean, convenient and safe operation. At the core of the WPT systems are two coils namely primary and secondary. For the safe and efficient transfer of energy the rated power, both sides have to be tuned by resonant capacitors. The selection of operating frequency is a key criterion for all applications as it affects the size and dimensions of the coils and the selection of the components for the power electronic circuit. Resonant wireless transmission systems for vehicle charging technology are being developed. Keywords— Wireless power transmission(WPT)

Design and Simulation of the Controller Proportional - Integral - Differential (PID) for Unmanned Surface Vessels

Unmanned Surface Vessels (USVs) are devices that use advanced, automated technologies for control and monitoring, with very little human intervention in this system. Today's un drone vehicles are developed for security, defense, trade, and civilian life purposes. Unmanned Surface Vessels is a device that uses advanced and automated technologies to control and monitor. This paper identifies the proportional - integral - differential controller. Results using MATLAB / SIMULINK simulation software.

Development and Validation of Generic Maneuvering Flight Noise Abatement Guidance for Helicopters

An extensive flight-test campaign has been conducted to look into developing actionable advice for pilots of today's vehicles to reduce their acoustic footprints. Ten distinct vehicles were tested at three different test ranges, with nine of the vehicles' data being documented here. Twelve pairs of turning conditions were tested to determine their effect on blade–vortex interaction noise. Each turning flight condition was evaluated using the peak A-weighted, band-limited (50–2500 Hz), sound pressure level measured throughout the maneuver. This metric was a surrogate for blade–vortex interaction (BVI) noise, and the difference between the peak values of each turning pair was investigated. That peak value difference was subsequently corrected by the offset from the intended vehicle altitude at turn initiation from the actual altitude at initiation. The corrected amplitudes were investigated and grouped into six validated actionable guidance principles that can be given to pilots to immediately reduce their acoustic footprint during operations. This generic guidance works by keeping the rotor well away from the wake throughout the maneuver, thus increasing miss distance and reducing the occurrence of objectionable BVI noise.

Understanding Traffic Signs by an Intelligent Advanced Driving Assistance System for Smart Vehicles

Recent technologies have made life smarter. vehicles are vital components in daily life that are getting smarter for a safer environment. Advanced Driving Assistance Systems (ADAS) are widely used in today's vehicles. It has been a revolutionary approach to make roads safer by assisting the driver in difficult situations like collusion, or assistance in respecting road rules. ADAS is composed of a huge number of sensors and processing units to provide a complete overview of the surrounding objects to the driver. In this paper, we introduce a road signs classifier for an ADAS to recognize and understand traffic signs. This classifier is based on a deep learning technique, and, in particular, it uses Convolutional Neural Networks (CNN). The proposed approach is composed of two stages. The first stage is a data preprocessing technique to filter and enhance the quality of the input images to reduce the processing time and improve the recognition accuracy. The second stage is a convolutional CNN model with a skip connection that allows passing semantic features to the top of the network in order to allow for better recognition of traffic signs. Experiments have proved the performance of the CNN model for traffic sign classification with a correct recognition rate of 99.75% on the German traffic sign recognition benchmark GTSRB dataset.