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For the NOx removal from diesel exhaust, the selective catalytic reduction (SCR) and lean NOx traps are established technologies. However, these procedures lack efficiency below 200 °C, which is of importance for city driving and cold start phases. Thus, the present paper deals with the development of a novel low-temperature deNOx strategy implying the catalytic NOx reduction by hydrogen. For the investigations, a highly active H2-deNOx catalyst, originally engineered for lean H2 combustion engines, was employed. This Pt-based catalyst reached peak NOx conversion of 95 % in synthetic diesel exhaust with N2 selectivities up to 80 %. Additionally, driving cycle tests on a diesel engine test bench were also performed to evaluate the H2-deNOx performance under practical conditions. For this purpose, a diesel oxidation catalyst, a diesel particulate filter and a H2 injection nozzle with mixing unit were placed upstream to the full size H2-deNOx catalyst.

A physics-based model for SCR (Selective Catalytic Reduction) was developed based on five independent SGB (Synthetic Gas Bench) tests. There are NH3 adsorption & desorption test, NO oxidation test, NH3 oxidation test, SCR reaction (NOx & NH3) test and SV (Space Velocity) test. To validate the accuracy of SCR model’s prediction, transient reactor tests were conducted at four different input conditions. A newly developed SCR model showed more than 90% prediction accuracy in transient test conditions in view of cumulative NOx. Validation of SCR model was conducted on 1.6L light duty diesel vehicle in the WLTC (Worldwide Harmonized Light vehicles Test Cycle). Based upon this SCR model, vehicle level SCR calibrations used for urea dosing control were made and validated in the emission test cycles like WLTC.

Selective Catalytic Reduction (SCR) is a process where one injects an aqueous solution of urea into a diesel exhaust system in order to reduce NOx emissions. The urea solution known as AdBlue® or Diesel Exhaust Fluid (DEF) is stored in a DEF Tank that can under cold weather conditions freeze over. Since AdBlue® is unusable while frozen, we use heaters installed in the tanks to melt AdBlue® with government regulations mandating time required to melt AdBlue® in the tank. In this article, we investigate whether a CFD (Computational Fluid Dynamics) based methodology can accurately evaluate time required in melting AdBlue® for a given DEF Tank and heater coil design for a production vehicle as per standard testing procedure. Simulations used a coupled methodology with PowerFLOW® as the flow solver and PowerTHERM® as the thermal solver. The flow simulation did require an accurate modelling of phase change from solid to liquid for AdBlue®.

To fulfill stringent emission legislation requirements, it is essential to understand the relation between aging processes of the exhaust gas aftertreatment system (ATS) and its performance. The Stage V compliant heavy-duty non-road aftertreatment system, which was used in this study, is comprised of a diesel oxidation catalyst (DOC) placed directly after the engine, followed by a particulate filter with a selective catalytic reduction (SCR) active coating (SCRoF) and is completed by an SCR-coated substrate combined with an NH3 oxidation catalyst. Each of the ATS components has to work in synergy and interact with each other to fulfill the emission legislation requirements. During vehicle operation, the ATS is exposed to various chemical and physical factors, which deteriorate its performance over its lifetime. In this work, the accelerated aging methodology is presented.

The diesel engine is the core in the field of engineering machine power plants. While both at home and abroad for the cold start of diesel engine, the transient emission characteristics below 0 °C and above 2000m is almost a blank. Therefore, aimed at high altitude and low-temperature environment emission characteristics of cold start, this article has carried on the systematic analysis and research. In this paper, a simulation test system for the cold start of the diesel engine at low temperature at high altitude is established. The cold start experiments of a heavy diesel engine at different ambient temperatures (10°C, 0°C, -10°C and -20°C) and different altitudes (0m, 3000m, and 4000m) is carried out. In this paper, the gas emission of the diesel engine during the speed-up period of cold start is studied.

Future legislations such as EPA27 [1] and EURO VII [2] are further reducing NOx emission limits. At the same time, the focus of emission compliance over a broad range of operation conditions is becoming more stringent; with a specific focus onto the cold start. The reduction of NOx is reached over a Selective Catalytic Reduction (SCR) system, with NH3 as a reductant. NH3 is derived over the processing of Urea Water Solution (UWS) to NH3. The conversion of UWS to NH3 is a highly complex process, with the danger of deposit formation, which is especially challenging in Compact Urea Processing Units (CUPU). One of the key factors for the successful development of Compact Urea Processing Units is the precise application of simulation and testing methods. Therefore, existing testing methods e.g. for the determination of the urea processing capability or the deposit formation were optimized, new testing methods are being introduced and the parameters evaluated are being broadened.

In addition to the low and high beam functions, some modern headlamps also have the option of switching on only section of the high beam. The so-called adaptive high beam is intended to increase the detection distance of objects and through that drastically improve the road safety. At the same time, this function does not increase the glare for oncoming or preceding traffic. This is enabled through switching the different segments of the high beam on or off, depending on which and where other road users are recognized by the front camera. This massively increases the use of the high beam, thus increasing road safety. In this study, the increase in the detection distance of objects on a straight line is statically investigated with a test person study. Furthermore, the glare of each of these three light functions is observed.

In order to reduce the carbon footprint of the Internal Combustion Engine (ICE), biofuels have been in use for a number of years. One of the problems with first-generation (1G) biofuels however is their competition with food production. In search of second-generation (2G) biofuels, that are not in competition with food agriculture, a novel biorefinery process has been developed to produce biofuel from woody biomass sources. This novel technique, part of the Belgian federal government funded Ad-Libio project, uses a catalytic process that operates at low temperature and is able to convert 2G feedstock into a stable light naphtha. The bulk of the yield consists out of hydrocarbons containing five to six carbon atoms, along with a fraction of oxygenates and aromatics. The oxygen content and the aromaticity of the hydrocarbons can be varied, both of which have a significant influence on the fuel’s combustion and emission characteristics when used in Internal Combustion Engines.

Over the last decades, electric vehicles (EVs) have emerged as an alternative to internal combustion engine vehicles. EVs have different propulsion and fuel intake system when compared to internal combustion engine vehicles. Therefore, cradle-to-gate (CTG) and well-to-wheel (WTW) greenhouse gas emissions (GHGs) would be different. In this study, life cycle GHG emissions of vehicle cycle and fuel cycle are compared between EV and internal combustion engine (ICEV) powered by petrol and diesel as fuel. This study used the average curb weight of all three types of vehicles based on the availability and popularity in the Indian market (as a case study) for life cycle assessment. The Greenhouse Gases, Regulated Emissions, and Energy use in Transport (GREET) model developed by Argonne National Laboratory was adopted to conduct the life cycle assessment. The mileage of 150,000 km over the whole life period was assumed for all types of vehicles.

As the number of electric vehicles (EVs) within society rapidly increase, the concept of maximizing its efficiency within the electric smart grid becomes crucial. This research presents the impacts of integrating EV charging infrastructures within a smart grid through a vehicle to grid (V2G) program. It also observes the circulation of electric charge within the system so that the electric grid does not become exhausted during peak hours. This paper will cover several different case studies and will analyze the best and worst scenarios for the power losses and voltage profiles in the power distribution system. Specifically, we seek to find the optimal location as well as the ideal number of EVs in the distribution system while minimizing its power losses and optimizing its voltage profile. Verification of the results are primarily conducted using GUIs created on MATLAB.

As the automated vehicle (AV) industry continues to progress, it is important to establish the level of operational safety of these vehicles prior to and throughout their deployment on public roads. The Institute of Automated Mobility (IAM) has previously proposed a set of operational safety assessment (OSA) metrics which can be used to quantify the operational safety of vehicles. The OSA metrics provide a starting point to consistently quantify performance, but a framework to interpret the metrics measurements is needed to objectively quantify the overall operational safety for a vehicle in a given scenario. This work aims to present an approach to applying a calculation of the safety envelope component of the OSA metrics to rear-world collisions for use in such an assessment. In this paper, the OSA methodology concept is introduced as a means for quantifying the operational safety of a vehicle.

Autonomous Driving is the next big thing in the Automotive future. With growing automation, there is also growing need for In-cabin and Occupant monitoring. Impaired driving as a cause constitute a statistically major portion of the total accidents in the world. Additionally, the aging society of road users add to health concerns of possible drivers behind the wheel which might lead to severe accidents. Since the accident and the associated damage would have been occurred due to incapacitated drivers in the first place, there arises a need to know the state of drivers while driving to ensure the safety of him and other road users. Therefore, the monitoring of the driver's state and detection of any deviation from the suitable driving condition is significant to reduce the number of accidents on the road. One of the efficient ways to know the drivers’ state is to monitor the health - physical, mental and emotional, of the drivers essentially.

In this paper we present a project that interfaced the National Advanced Driving Simulator (NADS) with SynChrono, a module of the Project Chrono open source simulation platform, to enable real-time, physics-based simulation of multiple autonomous vehicles (AVs) interacting with manned vehicles. In this setup, a driver at NADS, at the University of Iowa, participates in a traffic scenario that involves AVs that run at the University of Wisconsin-Madison on a cluster supercomputer. The NADS simulator is a driving simulator giving the “most realistic driving simulation experience in the country” [1]. Thanks to its actuators, it can move across its 64-foot by 64-foot bay, rotate and tilt, to emulate vehicle movement and vibrations. In addition, the human driver drives in a full-size cab, surrounded by LED monitors, resulting in an immersive, high fidelity driving simulation experience.

Rising electric scooter popularity has seen a surge in electric scooter crashes. Crash reconstructionists increasingly have access to global positioning system (GPS) data for micromobile vehicle trips, and GPS devices can produce a wealth of data about cyclists’, scooterists’, and other riders’ road paths and route usage. However, prior research has demonstrated that GPS positional accuracy is less reliable for more nuanced roadway positioning, such as which lane a vehicle occupies, as well as within-lane movements, such as acceleration and deceleration⁠. This limitation presents a challenge for crash reconstructionists that may have access to GPS data and require second-by-second positional accuracy to determine such nuanced maneuvers and vehicle positioning in their analysis. The purpose of this study was to explore the positional accuracy of five GPS units for a micromobile vehicle during three different ride conditions: acceleration, deceleration, and constant speed.

The glare to pedestrians remains one of the biggest challenges since the invention of the automobile and the automobile lighting. As far as pedestrians are concerned, whether the roadside pedestrians or the pedestrians in the crossing area are almost like lambs to the slaughter. To balance the glare interference of automobile lighting and protecting pedestrians, modeling and simulation for the pedestrian glare have been theorized by the use of forest sunlight effects and a novel controlled dark photonic channel. Based on the modeling and simulation, a novel full-factors light environment control system and pedestrian glare-free lighting system have been derived.

As new technology is added to vehicles and traffic congestion increases, there is a concern that drivers will be overloaded. As a result, there has been considerable interest in measuring driver workload. This can be achieved using many methods, with subjective assessments such as the NASA Task Loading Index (TLX) being most popular. Unfortunately, the TLX is unanchored, so there is no way to compare TLX values between studies, thus limiting the value of those evaluations. In response, a method was created to anchor overall workload ratings. To develop this method, 24 subjects rated the workload of clips of forward scenes collected while driving on rural, urban, and limited-access roads in relation to 2 looped anchor clips. Those clips corresponded to Level of Service (LOS) A and E (light and heavy traffic) and were assigned values of 2 and 6 respectively.

In this paper, a reinforcement learning-based method is proposed to adapt autonomous vehicle passengers’ expectation of comfort through in-situ human-vehicle interaction. Ride comfort has a significant influence on the user’s experience and thus acceptance of autonomous vehicles. There is plenty of research about the motion planning and control of autonomous vehicles. However, limited studies have explicitly considered the comfort of passengers in autonomous vehicles. This paper studies the comfort of humans in autonomous vehicles longitudinal autonomous driving. The paper models and then improves passengers’ feelings about autonomous driving behaviors. This proposed approach builds a control and adaptation strategy based on reinforcement learning using human’s in-situ feedback on autonomous driving. It also proposes an adaptation of humans to autonomous vehicles to account for improper human driving expectations.

This paper covers research findings on digital projections on the road. Data is provided for the root cause analysis of non-existing distraction proven by several studies. The study describes if and in which geometrical space road projections are visible to other road traffic participants. Such participants can be e.g. oncoming, passing drivers or pedestrians standing aside the road. The paper data shows where projections are recognizable and assignable to the original intention of the projection. A grid was created to identify the areas where digital projections could be understood and where the digital projections were just illegible. A dominant factor is the grazing incidence. The photons are distributed over a larger area and only the driver’s view makes a virtual compression of the illuminated area in order to make the signals legible. The results show that distraction for other road participants is unlikely for any position outside very limited areas.

It has been shown that additional light signals are beneficial in the car 2 human communication. This study addresses detection, discomfort, brightness, recognition of intention and the perception of safety, of different symbols and dynamics used for communication. Splitted in two parts, the first use case is a lane crossing situation, where the car gives instructions to the pedestrian via an angular restricted external Human Machine Interface (eHMI) in the driver’s window. Results show that a symbol which blinks first and is then statically shown leads to fast and best detection. The intention of a red stop hand and green pedestrian is clearly understood. A combination of a near road-projection and the eHMI leads to confusion. An angle of 55° to 25° has been proven to be sufficient for displaying the information. In the second use case a cyclist is approaching the automated vehicle (AV) from behind and passes on a bicycle path.

Flashing emergency and warning lights are critical elements of public safety and traffic control during roadway incidents. These lights should not only alert drivers to their presence, but also should inform them of who and what is present on the scene, and should help to manage the responses of drivers as they navigate past the incident. First responder and driver safety depend upon all three of these functions, yet standards focus almost entirely on alerting drivers. A full-scale outdoor field study was carried out during daytime, during nighttime on dry pavement and during nighttime on wet pavement, using a mock-up roadside scene containing three police vehicles. The lights on the vehicles were adjusted to produce different levels of intensity, flash rate, and synchronization of lights across all three vehicles. In some cases, sequentially flashing lights were present.