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This paper discusses the significant impact of changes in a car's gross weight due to various factors such as special accessories, parts, and materials, and how these changes can affect the car's CO2 emissions. Changes in the gross weight of a car can have a profound influence on its environmental footprint, particularly in terms of carbon dioxide (CO2) emissions. This is because the weight of the vehicle directly affects its fuel efficiency and overall environmental performance. The paper highlights that within each carline, there are multiple variants offered to customers, and these variants come with distinct combinations of parts and accessories, adding to the customization options. To accurately determine the CO2 emissions for each variant, it's essential to have a predictive system in place to estimate the gross weight of the cars. To achieve this, the paper suggests using historical data related to the weight of each part used in manufacturing the cars.

Ergonomics plays an important role in safety, comfort, and convenience of occupants in passenger cars. Customers come in different sizes; have different preferences and exhibit different seating behaviors while driving a car. With sophisticated interior styling themes aimed at satisfying the increasing customer demands, dashboard packaging and its integration in the vehicle has become a challenging task. This has a deteriorating effect on the driver knee clearance since dashboard has penetrated more into cockpit area to house the complex integration. With drivers having significant workload, their postures are within a presumable range of prediction. However, there still exists ‘out-of-customary’ behaviors while driving a vehicle. Drivers tend to sit in a slouched posture, and this leads to an involuntary knee engagement resulting in activation of critical controls like EPB (Electronic Parking Brake). EPB is an Active Safety feature and on activating it, the vehicle stops immediately.

LiDAR stands for Light Detection and Ranging. It works on the principle of reflection of light. LiDAR is one among the other sensors like RADAR and Camera to help achieve a higher level (Level 3 & above) of Autonomous driving capabilities. LiDAR, as a sensor, is used to perceive the environment in 3D by calculating the ‘Time of flight’ of the Laser beam transmitted from LiDAR and the rays reflected from the Object, along with the intensity of reflection from the object. The frame of perception is plotted as a point cloud. LiDAR is integrated in front of the vehicle, precisely in the grill of the car having a high vantage point to perceive the environment to extract the best possible sensor performance. LiDAR sensor needs to be held within the front panel cutout with uniform gap and flush condition.

Many Vulnerable Road Users (VRUs) experience injuries and fatalities every year, making road safety a challenge in the World. According to the Ministry of Road Transport and Highway (MoRTH) during the year 2021, a total number of 4,12,432 road accidents have been reported in India, claiming 1,53,972 lives and causing injuries to 3,84,448 persons. In terms of road-user categories, the total fatality of the Pedestrian road-users was 18.9 per cent of persons killed in road accidents. One of the ways to handle the situation is to protect pedestrians utilizing active safety measures in the vehicle. In addition, active safety research heavily relies on perceptions of pre-crash scenarios. The objective of the study is to examine passenger car-to-pedestrian scenarios and model active safety system in a car to prevent or mitigate collisions.

The automotive industry has recently started implementing magnetic gears, in different types, as an alternative design for transmission systems. One such design being the Magnetic planetary gear permanent magnet (MPG-PM) machine. The current methodology and the relevant formulae help to design the magnetic planetary gear system, which does not have design considerations for permanent magnet machines and the influence of magnetic fields. The influence of design characteristics of PM machine, Magnetic field and its material plays a vital role in designing the MPG-PM for electric vehicle applications. A method of optimizing the Gear topology design parameters of a magnetic planetary gear permanent magnet machine (MPG-PM machine) is proposed. The Analytical calculations regarding the design parameters are proposed in relation to power, gear ratios, and other design constraints like packaging parameters i.e., outer diameter, the overall length of the machine.

Environmental Protection Agency (EPA) study indicates that a typical passenger vehicle emits about 4.6 metric tons of carbon dioxide per year. The Automotive industry facing a challenge of meeting stringent CO2 emission targets of 95g per kilometer for passenger car application. Thermal efficiency of internal combustion engine is one of the crucial technical parameters, which plays an important role in meeting CO2 emission targets. Global Automotive industry tends to achieve for cleaner, lower emission, low noise & improved performance for automotive products. Engine Overheating is affecting thermal efficiency & thus brake specific fuel consumption of the vehicle. Radiator is one of the critical components in Engine cooling system, which will ensure optimum operating range of internal combustion engine through precise control on coolant flow rate by Thermostat valve. Heat dissipation through radiator is directly proportional to volumetric mass flow rate of atmospheric air.

In passenger cars, exterior damage due to external objects is a common and repetitive problem for the costumer. A vehicle running over an unpaved or granular road undergoes such damages where the tyre picks up stones (Figure 1) [1] and ejects them towards the vehicle exterior surfaces. These stones cause mechanical damage to the vehicle: affecting aesthetics, accelerating corrosion, and reducing safety. This mechanical damage is more severe in case of electrical vehicles as batteries are placed at the underside of the vehicle. Figure 2 [2] shows an example damaged caused by stone chipping. Induced erosion due to chipping cause corrosion propagation on the peeled surface, Figure 2 shows an example of such corrosion. So far, physical testing and analytical mathematical methods are the most common ways to evaluate damages. However, there is a need of computationally inexpensive, repeatable, and accurate method, which can account for the complex system.

Ensuring compliance with the ISO 26262 automotive functional safety standard involves meeting specific quality and complexity standards for automotive source code. However, achieving compliance becomes challenging when dealing with auto-generated code, as the code generator may not consider the required product metrics. This often leads to high metric values that exceed the permissible range. Assessing the impact of design on Hersteller Initiative Software (HIS) metrics within the visual modeling environment becomes difficult, with metrics reports only available after code generation. This makes it hard to achieve compliance through model reworking and regeneration. To address this problem, a methodology is proposed. It defines modeling guidelines and an architecture for generating HIS-compliant code.

Salt Spray Test is being used since 1930’s to accelerate the corrosion testing of materials and to understand the longevity of applied coating. The sample in this kind of test is exposed to a salt mist in a controlled environment and its corrosion resistance is evaluated by measuring the corrosion rate. The Wet-Dry cycle in Salt Spray Test has the ability to simulate the drying and wetting which occurs in real driving scenario, leading to formation of a film of corrosion products which is useful in analyzing the kinetics of electrochemical reaction. Despite the advancement in severity of these tests to understand the atmospheric corrosion phenomena, they still consume time and resources. Secondly, sometimes these kind of tests do not consider into account the effect of Temperature, Humidity and other chemicals in play. Thus, numerical simulation plays a pivotal role in digitalizing the corrosion analysis to a certain extent.

This abstract provides a comprehensive comparison between RocksDB, LMDB, and MongoDB, three popular database systems, highlighting their differences in terms of architecture, performance, scalability, and use cases. RocksDB, an embedded key-value store developed by Facebook, and LMDB (Lightning Memory-Mapped Database), a memory-mapped key-value store, are both optimized for high-performance and low-latency workloads. These databases excel in scenarios where efficiency and speed are critical factors, such as caching, session stores, and other applications that require fast data access. RocksDB is known for its persistent storage on disk and seamless integration with various programming languages, while LMDB leverages memory-mapped files for exceptional performance but lacks distributed capabilities. On the other hand, MongoDB, a document-oriented NoSQL database, offers a flexible schema and a rich set of features for handling complex data structures.

The automotive world is progressing fast towards autonomous vehicles making sensors one of the critical components. There is a requirement for constant exchange of information between the vehicle and its surrounding environment, which is assisted by sensors such as Camera, LiDAR, and RADAR. However, exposure to harsh environmental conditions such as rain, dirt, snow, and bird droppings can hamper the functioning of the sensors and in turn interrupt accurate vehicle maneuvers. Sensor-cleaning mechanisms are required to be tested under various weather conditions and vehicle operating situations. Besides wind tunnel tests, digitalizing this whole process becomes important to take decision on design changes in early vehicle development stage. This work presents a digital methodology to test the LiDAR cleaning system in the advent of mud clearing at different vehicle speeds. The cleaning mechanism consists of a telescopic nozzle placed above the LiDAR translating back and forth.

The automotive industry uses supercharging in combination with various EGR strategies to meet the increasing demand for Diesel engines with high efficiency and low engine emissions. The charge air is heated by the EGR and the compression in the turbocharger to such an extent that high NOx emissions and a reduction in engine performance occurs. For this reason, the charge air cooler cools down the charge air before it enters the air intake manifold. In case of low pressure EGR, the charge air possesses a high moisture content and under certain operating conditions an accumulation of condensate takes place within the charge air cooler. During demanding engine loads, the condensate is entrained from the charge air cooler into the combustion chamber, resulting in misfiring or severe engine damage.

This paper investigates the pressure drop with and without condensation inside a charge air cooler. The background to this investigation is the fact that the stored condensate in charge air coolers can be torn into the combustion chamber during different driving states. This may result in misfiring or in the worst-case lead to an engine failure. In order to prevent or reduce the accumulated condensate inside charge air coolers, a better understanding of the detailed physics of this process is required. To this end, one single channel of the charge air side is investigated in detail by using an experimental setup that was built to reproduce the operating conditions leading to condensation. First, measurements of the pressure drop without condensation are conducted and a good agreement with experimental data of a comparable heat exchanger reported in Kays and London [1] is shown.

This paper describes the possibility to resolve aeroacoustic feedback with a commercial 2nd/3rd order finite volume CFD code [1]. After a first comparison to a NACA 0012 test case, tonal noise components of a realistic automotive side view mirror are validated with in-house wind tunnel measurements. A zonal RANS/LES approach is used to ensure a realistic flow around the exterior side mirror mounted on a Mercedes-Benz passenger car. The provided compressible large eddy simulations are using non-reflecting boundary conditions in combination with a sponge zone approach to reduce hydrodynamic fluctuations and are in great accordance to measurements. The possibility of localizing and investigating the underlying feedback mechanism enables the chance for a targeted design of different appropriate remedies, which are finally confirmed by means of experimental comparison.

The reliability of electronic components is of increasing importance for further progress towards automated driving. Thermal aging processes such as electromigration is one factor that can negatively affect the reliability of electronics. The resulting failures depend on the thermal load of the components within the vehicle lifetime - called temperature collective - which is described by the temperature frequency distribution of the components. At present, endurance testing data are used to examine the temperature collective for electronic components in the late development stage. The use of numerical simulation tools within Vehicle Thermal Management (VTM) enables lifetime thermal prediction in the early development stage, but also represents challenges for the current VTM processes [1, 2]. Due to the changing focus from the underhood to numerous electronic compartments in vehicles, the number of simulation models has steadily increased.

A powerful and efficient turbocharger turbine benefits the engine in many aspects, such as better transient response, lower NOx emissions and better fuel economy. The turbine performance can be further improved by employing secondary flow injection through an injector over the shroud section. A secondary flow injection system can be integrated with a conventional turbine without affecting its original design parameters, including the rotor, volute, and back disk. In this study, a secondary flow injection system has been developed to fit for an asymmetric twin-scroll turbocharger turbine, which was designed for a 6-cylinder heavy-duty diesel engine, aiming at improving the vehicle’s performance at 1100 rpm under full-loading conditions. The shape of the flow injector is similar to a single-entry volute but can produce the flow angle in both circumferential and meridional directions when the flow leaves the injector and enters the shroud cavity.

Underride accidents constitute around 5% and 4% of all accidents in India and the US respectively. Yet, the occupant fatality risk is the highest in this accident configuration when compared to other configurations for passenger cars. Especially in India, the fatality rate is even higher due to minimal usage of underride protection devices in the front, rear and sides of commercial vehicles along with poor passenger vehicle crashworthiness. This study specifically aims to compare the factors influencing occupant fatality in the rear underride accidents in India and the US. Given the large number of variables involved in an accident and their complex interaction in a small duration, it was realized that a statistical analysis of this nature will only give an insight into the accident risk trends. The influencing factors are identified by performing Principal Component Analysis (PCA), which is a linear feature extraction technique.

Future CO2 emission legislation requires the internal combustion engine to become more efficient than ever. Of great importance is the boosting system enabling down-sizing and down-speeding. However, the thermodynamic coupling of a reciprocating internal combustion engine and a turbocharger poses a great challenge to the turbine as pulsating admission conditions are imposed onto the turbocharger turbine. This paper presents a novel approach to a turbocharger turbine development process and outlines this process using the example of an asymmetric twin scroll turbocharger applied to a heavy duty truck engine application. In a first step, relevant operating points are defined taking into account fuel consumption on reference routes for the target application. These operation points are transferred into transient boundary conditions imposed on the turbine.

The oil transport phenomena in the chamfer beneath the oil control ring of a piston in a motored engine were investigated with a combined experimental-numerical approach. High-speed laser-induced fluorescence was used to visualize the oil distribution crank-angle-resolved on both thrust side and anti-thrust side of an optically accessible single cylinder engine. Corresponding three-dimensional volume-of-fluid CFD simulations were calibrated with the experiment and then utilized to analyze the cross sectional flows in the chamfer. Phenomena triggered by inertial forces and the lateral piston motion, e.g. oil transport from the piston to the liner (bridging) and the formation of a circular flow in the chamfer, are described in detail.

The overall efficiency of hybrid electric vehicles largely depends on the design and application of its energy management system (EMS). Despite the load coordination when operating the system in a hybrid mode, the EMS accounts for state changes between the different driving modes. Whether a transition between pure electric driving and internal combustion engine (ICE) powered driving is beneficial depends, among others, on the respective operation point, the route ahead as well as on the energetic expense for the engine start itself. The latter results from a complex interaction of the powertrain components and has a tremendous impact on the efficiency and quality of EMSs. Optimization based methods such as dynamic programming serve as benchmark for the design process of rule based control strategies. In case no energetic expenses are assigned to a state change, the resulting EMS suffers from being sub-optimal regarding the fuel consumption.