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Increasing urbanisation and the growing environmental awareness in society require new and innovative vehicle concepts. In the present work, the design freedoms of additive manufacturing (AM) are used to develop a front axle wheel suspension for a novel modular vehicle concept. The development of the suspension components is based on a new method using industry standard load cases for the strength design of the components. To design the chassis components, first the available installation space is determined and a suitable configuration of the chassis components is defined. Furthermore, numerical methods are used to identify component geometries that are suitable for the force flow. The optimisation setup is selected in a way that allows to integrate information, energy and material-carrying conductors into the suspension arms. The conductors even serve as load-bearing structures because of the matching design of the components.

The electrification of vehicles marks the introduction of new products to the automotive market and a continued effort to optimize their performance. The electric motor is an important component with which a further optimization of efficiency, power density and cost can be achieved. Additional benefits can be realized in the laminated core. This paper presents an innovative method to produce laminated stacks by a chain of processes different from conventional ways. The process chain presents a sequence of precision blanking, buffering, heat treatment and gluing. The effect of these processes is compared with existing solutions that typically contain some individual features but usually not the combination that enhances the overall effect. The heat treatment decreases residual stresses from previous process steps and reduces power losses in the laminated core. Depending on the design, benefits around 20% are found.

This study focuses on evaluation of various fuels within a conventional gasoline internal combustion engine (ICE) vehicle and the implementation of advanced emissions reduction technology. It shows the robustness of the implemented technology packages for achieving ultra-low tailpipe emissions to different market fuels and demonstrates the potential of future GHG neutral powertrains enabled by drop-in lower carbon fuels (LCF). An ultra-low emission (ULE) sedan vehicle was set up using state-of-the-art engine technology, with advanced vehicle control and exhaust gas aftertreatment system including a prototype rapid catalyst heating (RCH) unit. Currently regulated criteria pollutant emission species were measured at both engine-out and tailpipe locations. Vehicle was run on three different drive cycles at the chassis dynamometer: two standard cycles (WLTC and TfL) at 20°C, and a real driving emission (RDE) cycle at -7°C.

The functional extension of vibration reduction in continuous slip operation in modern wet-running clutch systems under dynamic excitation is being investigated by the authors. Therefore, a mixed virtual-physical validation environment has been developed using the IPEK X-in-the-Loop Framework and will be presented as part of this contribution. Thus, the validation environment enables the consideration of interactions with the residual systems, especially the residual drive train. In this contribution, the validation environment is used to investigate whether and how an attribute variation in the subsystem, respectively the tribological system, can provide improved vibration reduction without increased power dissipation due to damping but other reducing mechanisms favored. The results show significant differences in vibration reduction behavior whereas the power losses are almost the same between the investigated tribological system.

The rapidly growing amount of software in cars reshapes the automotive industry. The software has a significant influence on the production lines, due to the time required to flash it onto the vehicle and its capabilities to test vehicle functions during production. In this paper we identify the main pain points regarding software in the manufacturing process by performing a structured analysis on the experiences made at a major car manufacturer over last two years. Consequently, the paper analyses the possible approaches to address the challenges.

X-Domain describes the merging of different domains (i.e., braking, steering, propulsion, suspension) into single functionalities. One example in this context is torque-vectoring. Different goals can be pursued by applying X-Domain features. On the one hand, savings in fuel consumption and an improved vehicle driving performance can be potentially accomplished. On the other hand, safety can be improved by taking over a failed or degraded functionality of one domain by other domains. The safety-aspect from the viewpoint of requirements is highlighted within this contribution. Every automotive system being developed and influencing the vehicle safety must fulfill certain safety objectives. These are top-level safety requirements (ISO 26262-1) specifying functionalities to avoid unreasonable risk. Every safety objective is associated with an Automotive Safety Integrity Level (ASIL) derived from a Hazard Analysis and Risk Assessment (HARA).

In marine or stationary engines, consistent engine performance must be guaranteed for long-haul operations. A dual-fuel combustion strategy was used to reduce the emissions of particulates and nitrogen oxides in marine engines. However, in this case, the combustion stability was highly affected by environmental factors. To ensure consistent engine performance, the in-cylinder pressure measured by piezoelectric pressure sensors is generally measured to analyze combustion characteristics. However, the vulnerability to thermal drift and breakage of sensors leads to additional maintenance costs. Therefore, an indirect measurement via a reconstruction model of the in-cylinder pressure from engine block vibrations was developed. The in-cylinder pressure variation is directly related to the block vibration; however, numerous noise sources exist (such as, valve impact, piston slap, and air flowage).

Historically, whenever the automotive solutions’ state of art reaches a saturation level, the integration of new verticals of technology has always raised new opportunities to innovate, enhance and optimize automotive solutions. The predictive powertrain solutions using connectivity elements (e.g., navigation unit, e-Horizon or cloud-based services) are one of such areas of huge interest in automotive industry. The prior knowledge of trip destination and its route characteristics has potential to make prediction of powertrain modes or events in certain order and therefore it can add value in various application areas such as optimized energy management, lower fuel consumption, superior safety and comfort, etc.

The power density of electric machines is a critical factor in various applications, i.e. like the power train. A major factor to improve the power density is boosting the electric current density, which increases the losses in the limited volume of the electric machine. This results in a need for an optimized thermal design and efficient cooling. The dissipation of heat can be achieved in a multitude of ways, ranging from air cooling to highly integrated cooling solutions. In this paper, this variety is shown and analyzed with a focus on water cooling. Further various structures in electric machines are presented. A planar testbench is built to systematically analyze water cooling geometries. The focus lies in providing different power loss distributions along cooling channels, accurate temperature readings in a multitude of locations, as well as the pressure drop across the channel.

The concept of hot surface assisted compression ignition (HSACI) was previously shown to allow for control of combustion timing and to enable combustion beyond the limits of pure homogeneous charge compression ignition (HCCI) combustion. This work investigates the potential of HSACI to extend the operating limits of a naturally aspirated single-cylinder natural gas fueled HCCI engine. A zero-dimensional (0D) thermo-kinetic modeling framework was set up and coupled with the chemical reaction mechanism AramcoMech 1.3. The results of the 0D study show that reasonable ignition timings in the range 0-12°CA after top dead center (TDC) in HCCI can be expressed by constant volume ignition delays at TDC conditions of 9-15°CA. Simulations featuring the two-stage combustion in HSACI point out the capability of the initial heat release as a means to shorten bulk-gas ignition delay.

India contributed to 11% of the global road accidents and was ranked 1st among road deaths according to the latest World Health Organization (WHO) report 2018. Indian National Highways (NH) is a meagre 5% of the country’s road network but accounts for 55% of the road accidents and 61% of the road deaths. Majority of the freight traffic is ferried by Commercial Vehicles (CV) or trucks along these highways and this in turn increases the probability of them being involved in a road accident. The country’s economy is forecasted to thrive in the coming years and hence the requirement of CVs is aligned to international categorisation in the supply chain and shall play a pivotal role. In the year 2019, 13,532 road deaths were associated with CV occupants. The trucking industry is an unorganized sector wherein the illegal overloading of vehicles and over-the-limit driving hours pose a serious threat to road users.

Software-in-the-Loop (SiL) test environments are the ideal virtual platforms for enabling continuous-development, -integration, -testing -delivery or -deployment commonly referred as Continuous-X (CX) of the complex functionalities in the current automotive industry. This trend especially is contributed by several factors such as the industry wide standardization of the model exchange formats, interfaces as well as architecture definitions. The approach of frontloading software testing with SiL test environments is predominantly advocated as well as already adopted by various Automotive OEMs, thereby the demand for innovating applicable methods is increasing. However, prominent usage of the existing monolithic architecture for interaction of various elements in the SiL environment, without regarding the separation between functional and non-functional test scope, is reducing the usability and thus limiting significantly the cost saving potential of CX with SiL.

A gray-box optimization procedure based on evolutionary algorithms for the initial design of a suspension concept for four wheel independently driven and steered vehicles is developed. With the presented optimization method, the energy consumption together with state of the art knowledge about the parametrization and design of vehicle suspension systems leads to an optimization setup closely to real world requirements while the vehicle’s topology is exploited. To this, the modelling presented in [1] is considered as a geometric suspension model. Furthermore, to take advantage of the potential of such vehicles, an autonomous closed-loop setup with integrated motion control is utilized. During the optimization, the chassis parameters with the most impact on energy consumption and driving dynamics, namely camber, caster, scrub radius and the steering axis inclination (SAI) depending on a varying caster angle and SAI in relation to the steering angle, will be focused.

As an important means of engine development and optimization, modelbuilding plays an increasingly important role in reducing carbon dioxide emissions of the internal combustion engines (ICEs). However, due to the non-linearity and high dimension of the engine system, a large amount of data is required to obtain high model accuracy. Therefore, a modelling approach combining the experimental data and prior knowledge was proposed in this study. With this method, an artificial neural network (ANN) model simulating the engine brake specific fuel consumption (BSFC) was established. With mean square error (MSE) and Kullback-Leibler divergence (KLD) serving as the fitness functions, the 86 experimental samples and constructed physical models were used to optimize the ANN weights through genetic algorithms.

The fuel economic and emission performance of an innovative electric hybrid vehicle (HEV), Dualhybrid, with two internal combustion engines (ICEs) under cold start conditions was studied. Sub-models including powertrain, lubrication and cooling system as well as exhaust system were built and integrated into the models of Dualhybrid and two other reference models: Base model and Fullhybrid model. Coupled lubrication and the exhaust systems of the two ICEs are proposed. The effect of the combination of oil heating and electric heating on the fuel consumption of Dualhybrid was investigated. The results show that the coupled lubricating system of Dualhybrid is beneficial to improve the fuel economy in cold start. The method of hybrid heating can provide a sufficient heating power of the cabin in the initial stage of cold start without declining the fuel economic performance significantly.

The prime factor which influences noise and vibrations of electro-mechanical drives is wear at the components. This paper discusses the numerical methods developed for abrasion, vibration calculations and the coupling between wear and Noise Vibration and Harshness (NVH) models of the drive unit. The vibration domain model, initially, focuses on the calculations of mechanical excitations at the gear shafts which are generated via a nonlinear dynamic model. Furthermore, the bearings are studied for the influences on their stiffness and eventually their impact on the harmonics of the drivetrain. Later, free and forced vibrations of the complete drivetrain are simulated via a steady-state dynamic model. Consequently, the paper concentrates on the abrasion calculations at the gears. Wear is a complex process and understanding it is essential for determining the vibro-acoustics characteristics.

Due to the new CO2 targets for vehicles, electrification of powertrains and operation strategies for electrified powertrains have drawn more attention. This article presents a predictive multi-objective operation strategy for hybrid electric vehicles (HEVs), which simultaneously minimizes the fuel consumption and the cycle aging of traction batteries. This proposed strategy shows better performance by using predictive information and high robustness to inaccuracy of predictive information. In this work, the benefits of the developed operation strategies are demonstrated in a strong hybrid electric vehicle (sHEV) with P2-configuration. For the cycle aging of a lithium-ion battery, an empirical model is built up with Gaussian processes based on experimental data.

A major source for soot particle formation in Gasoline-Direct-Injection (GDI) engines are fuel-rich zones near walls as a result of wall wetting during injection. To address this problem, a thorough understanding of the wall film formation and evaporation processes is necessary. The wall temperature before, during and after fuel impingement is an important parameter in this respect, but is not easily measured using conventional methods. In this work, a recently developed laser-based phosphor thermography technique is implemented for investigations of spray-induced surface cooling. This spatially and temporally resolved method can provide surface temperature measurements on the wetted side of the surface without being affected by the fuel-film. Zinc oxide (ZnO) particles, dispersed in a chemical binder, were deposited onto a thin steel plate obtaining a coating thickness of 17 μm after annealing.

Premature and uncontrolled flame initiation, called pre-ignition (PI), is a prominent issue in the development of spark-ignited engines. It is commonly assumed that this abnormal combustion mode hinders progress in engine downsizing, thus inhibiting development of more efficient engines. The phenomenon is primarily observed in highly turbocharged spark ignited (SI) engines in the full load regime at low engine speeds. Subsequent engine knock induces extremely high peak pressures, potentially causing severe engine damage. The mechanisms leading to this phenomenon are not completely understood; however, it is quite plausible that a multiphase process is responsible for the pre-ignition. One effect could be the interaction between injected fuel drops and the oil film on the cylinder liner. Under certain conditions, droplets of oil or oil/fuel mixture can detach or splash from the film, leading to pre-ignition at the droplet surface towards the end of the compression phase.

The fuel spray behavior in the near nozzle region of a gasoline injector is challenging to predict due to existing pressure gradients and turbulences of the internal flow and in-nozzle cavitation. Therefore, statistical parameters for spray characterization through experiments must be considered. The characterization of spray velocity fields in the near-nozzle region is of particular importance as the velocity information is crucial in understanding the hydrodynamic processes which take place further downstream during fuel atomization and mixture formation. This knowledge is needed in order to optimize injector nozzles for future requirements. In this study, the results of three experimental approaches for determination of spray velocity in the near-nozzle region are presented. Two different injector nozzle types were measured through high-speed shadowgraph imaging, Laser Doppler Anemometry (LDA) and X-ray imaging.