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The UN R155 regulation is the first automotive cyber security regulation and has made security a mandatory approval criterion for new vehicle types. This establishes internationally harmonized security requirements for market approval. As a result, the application of the regulation presents manufacturers and suppliers with the challenge of demonstrating compliance. At process level the implementation of a Cyber Security Management System (CSMS) is required while at product level, the Threat Assessment and Risk Analysis (TARA) forms the basis to identify relevant threats and corresponding mitigation strategies. Overall, an issued type approval is internationally recognized by the member states of the UN 1958 Agreement. International recognition implies that uniform assessment criteria are applied to demonstrate compliance and to decide whether security efforts are sufficient.

Previous studies have shown that dosing AdBlue into the exhaust system of diesel engines to reduce nitrogen oxides can lead to an increase in the number of particles (PN). In addition to the influencing factors of exhaust gas temperature, exhaust gas mass flow and dosing quantity, the dosed medium itself (AdBlue) is not considered as a possible influence due to its regulation in ISO standard 22241. However, as the standard specifies limit value ranges for the individual regulated properties and components for newly sold AdBlue, in reality there is still some margin in the composition. This paper investigates the particle number increase due to AdBlue dosing using several CPCs. The increase in PN is determined by measuring the number of particles after DPF and thus directly before dosing as well as tailpipe. Several AdBlue products from different sources and countries are measured and their composition is also analyzed with regard to the limit values regulated in the standard.

In recent years, the urgent need to fully exploit the fuel economy potential of the Electrified Vehicles (xEVs) through the optimal design of their Energy Management System (EMS) have led to an increasing interest in Machine Learning (ML) techniques. Among them, Reinforcement Learning (RL) seems to be one of the most promising approaches thanks to its peculiar structure, in which an agent is able to learn the optimal control strategy through the feedback received by a direct interaction with the environment. Therefore, in this study, a new Soft Actor-Critic agent (SAC), which exploits a stochastic policy, was implemented on a digital twin of a state-of-the-art diesel Plug-in Hybrid Electric Vehicle (PHEV) available on the European market. The SAC agent was trained to enhance the fuel economy of the PHEV while guaranteeing its battery charge sustainability.

Over the past decade, significant progress has been made in developing algorithms and improving hardware for automated driving. However, conducting research and deploying advanced algorithms on automated vehicles for testing and validation remains costly, especially for academia. This paper presents the efforts of our research team to integrate the newest version of the open-source Autoware software with the commercially available DataSpeed Drive-by-Wire (DBW) system, resulting in the creation of a versatile and robust automated vehicle research platform. Autoware, an open-source software stack based on the 2nd generation Robot Operating System (ROS2), has gained prominence in the automated vehicle research community for its comprehensive suite of perception, planning, and control modules. The DataSpeed DBW system directly communicates with the vehicle's CAN bus and provides precise vehicle control capabilities.

Autonomous driving technology is more and more important nowadays, it has been changing the living style of our society. As for autonomous driving planning and control, vehicle dynamics has strong nonlinearity and uncertainty, so vehicle dynamics and control is one of the most challenging parts. At present, many kinds of specific vehicle dynamics models have been proposed, this review attempts to give an overview of the state of the art of vehicle dynamics models for autonomous driving. Firstly, this review starts from the simple geometric model, vehicle kinematics model, dynamic bicycle model, double-track vehicle model and multi degree of freedom (DOF) dynamics model, and discusses the specific use of these classical models for autonomous driving state estimation, trajectory prediction, motion planning, motion control and so on.

Human driving behavior's inherent variability, randomness, individual differences, and dynamic vehicle-road situations give human-machine cooperative (HMC) driving considerable uncertainty, which affects the applicability and effectiveness of HMC control in complex scenes. To overcome this challenge, we present a novel data-enabled game output regulation approach for HMC driving. Firstly, a global human-vehicle-road (HVR) model is established considering the varied driver's steering characteristic parameters, such as delay time, preview time, and steering gain, as well as the uncertainty of tire cornering stiffness and variable road curvature disturbance. The robust output regulation theory has been employed to ensure the global DVR system's closed-loop stability, asymptotic tracking, and disturbance rejection, even with an unknown driver's internal state. Secondly, an interactive shared steering controller has been designed to provide personalized driving assistance.

Intelligent vehicle-to-everything connectivity is an important development trend in the automotive industry. Among various active safety systems, Autonomous Emergency Braking (AEB) has garnered widespread attention due to its outstanding performance in reducing traffic accidents. AEB effectively avoids or mitigates vehicle collisions through automatic braking, making it a crucial technology in autonomous driving. However, the majority of current AEB safety models exhibit limitations in braking modes and fail to fully consider the overall vehicle stability during braking. To address these issues, this paper proposes an improved AEB control system based on a risk factor (AERF). The upper-level controller introduces the risk factor (RF) and proposes a multi-stage warning/braking control strategy based on preceding vehicle dynamic characteristics, while also calculating the desired acceleration.

To address the issue of PID control for automotive vibration, this paper supplements and develops the evaluation of automotive vibration characteristics, and proposes a vibration response quantity for evaluating the energy dissipation characteristics of automotive vibration. A two-degree-of-freedom single wheel model for automotive vibration control is established, and the conventional vibration response variables for ride comfort evaluation and the energy consumption vibration response variables for energy dissipation characteristics evaluation are determined. This paper uses the Adaptive Differential Evolution (ADE) algorithm to tune the PID control parameters and introduces an adaptive mutation factor to improve the algorithm's adaptability. Several commonly used adaptive mutation factors are summarized in this paper, and their effects on algorithm improvement are compared.

As the automotive industry accelerates its virtual engineering capabilities, there is a growing requirement for increased accuracy across a broad range of vehicle simulations. Regarding control system development, utilizing vehicle simulations to conduct ‘pre-tuning’ activities can significantly reduce time and costs. However, achieving an accurate prediction of, e.g., stopping distance, requires accurate tire modeling. The Magic Formula tire model is often used to effectively model the tire response within vehicle dynamics simulations. However, such models often: i) represent the tire driving on sandpaper; and ii) do not accurately capture the transient response over a wide slip range. In this paper, a novel methodology is developed using the MF-Tyre/MF-Swift tire model to enhance the accuracy of ABS braking simulations.

Considering the current trend towards the electrification of commercial vehicles, the development of Beam eAxle solutions has become necessary. The utilization of an electric drive unit in heavy-duty solid axle-based commercial vehicles presents unique and demanding challenges. These include the necessity for elevated peak and continuous torque while meeting packaging constraints, structural integrity requirements, and extended service life. One such solution was developed by BorgWarner to address these challenges. This paper offers a comprehensive overview of the design and development process undertaken for this Dual Motor Beam eAxle system. This includes the initial comparison of various eAxle solutions, the specifications of components selected for this design, and the initial results from dyno and vehicle development.

Recently, with the advancement of autonomous driving technology, the function of external lamps has been changed. Previously, the focus was on the visibility of drivers, but with the advancement of autonomous driving technology, the concept of autonomous driving systems has been developed. Accordingly, the trend of automotive lamp lighting systems has been developed in terms of design, e-HMI (exterior-human machine interface), It is developing in accordance with three major fields such as sensor connection. Therefore, this paper will cover the prior development of road content projection headlamps that enable e-HMI implementation to reflect these new trends. Since the technology is mass-produced and sold by several manufacturers, our company also needs to quickly develop and apply the technology in advance. Only four types of symbols are allowed in European law.

To ensure adequate visibility without excessive glare, vehicle headlights are designed to use a specific source of illumination. The optical designs of headlights gather the luminous flux produced by the light source to produce a useful beam pattern that meets the relevant requirements and standards for vehicle forward lighting. With the advent of solid state, light emitting diode sources for general illumination, an increasing number of LED replacement headlight bulb products has emerged over the past decade. In most cases, these LED replacement bulbs are not permitted for legal use on public roadways, but some countries have begun to permit specific LED replacement bulbs to be used legally on the road for specific makes, models and production years of certain vehicles. If they can be demonstrated to produce a beam pattern that meets the photometric requirements for a legal headlight, they are permitted to be used legally for on-road use.

To promote real time monitoring, In use performance ratio monitoring “IUPRm” checks has been enforced in India from Apr’23 as a part of BS6-2 regulation. Since IUPRm is representative of diagnostic frequency in real driving conditions and usage pattern. therefore, a clear understanding of real-world driving is required to define IUPRm targets. This paper shares methodology and Validation steps for defining IUPRm routes for Indian market. Methodology objective is to standardize the market operating conditions over a particular region. Selected Methodology consist of three steps: For defining IUPRm route framework, first step is to have a pre-market survey to know current In use performance ratio “IUPR” status and improvement areas in existing market vehicles. Second step is to define market representative localized on road routes based on the finding of Pre-market survey.

A systematic review based on the PRISMA protocol was used to evaluate compounds developed for 3D printing with the incorporation of cellulose nanofibrils into polymers to be used in the automotive sector. The processing parameter is a data of great relevance for the development of durable structural parts and this study can be carried out using the state of the art on this subject. This way, the research was carried out using a search strategy from three different databases (Web of Science, Scopus and Science Direct) limiting studies between the years 2019 and 2023. The keywords used in these searches were: "3D Print" OR "FDM" OR "Fused Deposition Modeling" OR "FFF" OR "Fused Filament Fabrication" AND "Natural Nanofiber" OR "Natural Nanofibril" OR "Cellulose Nanofiber" OR "Cellulose Nanofibril". The same criteria described were also used to search for patents on the PatentScope, Google Patents and Espacenet platforms.

The pursuit of maintaining a zero-sideslip angle has long driven the development of four-wheel-steering (4WS) technology, enhancing vehicle directional performance, as supported by extensive studies. However, strict adherence to this principle often leads to excessive understeer characteristics before tire saturation limits are reached, resulting in counter-intuitive and uncomfortable steering maneuvers during turns with variable speeds. This research delves into the phenomenon encountered when a 4WS-equipped vehicle enters a curved path while simultaneously decelerating, necessitating a reduction in steering input to adapt to the increasing road curvature. To address this challenge, this paper presents a novel method for dynamically regulating the steady-state yaw rate of 4WS vehicles. This regulation aims to decrease the vehicle's sideslip angle and provide controlled understeer within predetermined limits.

The use of hydrogen in internal combustion engines is an effective approach to significantly support the reduction of CO2 emissions from the transportation sector using technically affordable solutions. The use of direct injection is the most promising approach to fully exploit hydrogen potential as a clean fuel, while preserving targets in terms of power density and emissions. In this frame, the development of an effective combustion system largely relies on the hydrogen-air mixture formation process, so to adequately control the charge stratification to mitigate pre-ignitions and knock and to minimize NOx formation. Hence, improving capabilities of designing a correct gas jet-air interaction is of paramount importance. In this paper the analysis of the evolution of a high-pressure gas jet produced by a single-hole prototype injector operated with different pressure ratios is presented.

Symbolic code execution is a powerful cybersecurity testing approach that facilitates the systematic exploration of all paths within a program to uncover previously unknown cybersecurity vulnerabilities. This is achieved through a Satisfiability Modulo Theory (SMT) solver, which operates on symbolic values for program inputs instead of using their concrete counterparts. However, in complex code bases, this approach faces significant limitations, such as program path explosions or unavailable dependencies, which can result in conditions that the SMT solver cannot reason about. Consequently, SMT solvers are often considered as too costly to implement for automotive testing use cases and are rarely employed within this domain. In contrast, fuzz testing has recently gained traction in the automotive industry as an invaluable testing technique for identifying previously unknown vulnerabilities. Its initial setup is straightforward and typically yields useful findings.

The aim of this study is to determine if the degradation of one or more dampers of a passenger car with ABS leads to a statistically significant reduction of vehicle safety. Therefore, a compact and a mid-size car are tested on a flat test track and on an uneven test track by straight braking maneuvers at different levels of damper degradation. Both test tracks are scanned using a 3D laser scanner. For every level of damper degradation (on each test track) a new set of tires is used, a preconditioning routine is applied and 30 successful measurements are conducted to allow using statistical methods to evaluate the results. The results show that any level of damper degradation with each type of car and test track leads to a significant increase in braking distance and, therefore, to a significant reduction of vehicle safety. The braking distance extension varies heavily with the level of damper degradation and the road properties.

The world is on a “take-make-waste,” linear-growth economic trajectory where products are bought, used, and then discarded in direct progression with little to no consideration for recycling or reuse. This unsustainable path now requires an urgent call to action for all sectors in the global society: circularity is a must to restore the health of the planet and people. However, carbon-rich textile waste could potentially become a next-generation feedstock, and the mobility sector has the capacity to mobilize ecologically minded designs, supply chains, financing mechanisms, consumer education, cross-sector activation, and more to capitalize on this “new source of carbon.” Activating textile circularity will be one of the biggest business opportunities to drive top- and bottom-line growth for the mobility industry.

The safety of commercial aviation industry has come under extensive scrutiny and how the system safety process is applied. One specific system safety regulation concerns how unsafe system operating conditions are meeting regulatory requirements. Minimal regulatory guidance was available on this topic and an industry committee (American Society for Testing of Materials) decided to provide a consensus standard with input from a cross-section of airplane manufacturers, suppliers, and regulatory authorities on what is meant by an unsafe system operating condition and how compliance can be shown to the regulation(s). The committee determined that an unsafe system operating condition is when a failure condition severity increases (to hazardous or catastrophic) due to crewmember(s) inaction. For example, if a hazard has occurred it is possible the severity can increase to an unacceptable level as the crewmember(s) are not aware of the hazard.