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On the path to decarbonizing road transport, electric commercial vehicles will play a significant role. The first applications were directed to the smaller trucks for distribution traffic with relatively moderate driving and range requirements, but meanwhile, the first generation of a complete portfolio of truck sizes is developed and available on the market. In these early applications, many compromises were accepted to overcome component availability, but meanwhile, the supply chain can address the specific needs of electric trucks. With that, the optimization towards higher usability and lower costs can be moved to the next level. Especially for long-haul trucks, efficiency is a driving factor for the total costs of ownership. Besides the propulsion system, all other systems must be optimized for higher efficiency. This includes thermal management since the thermal management components consume energy and have a direct impact on the driving range.

Legislative challenges, changing customer needs and the opportunities opened-up by electrification are the major driving forces in today’s automotive industry. Fuel cell vehicles offer the potential for CO2 emission free mobility, especially attractive for heavy duty long-haul range application. The development of key components of fuel cell powered vehicles, namely the fuel cell stack itself as well as the related hydrogen/air supply and thermal management sub-systems, goes hand in hand with various challenges regarding performance, lifetime and safety. The proper layout and sizing of the stack and the related fuel and air supply system components, as well as the suitable dimensioning of the cooling system, are decisive for the overall system efficiency and achievable lifetime.

This paper presents the results of an investigation on the influence of a duct’s geometry and shape on its acoustic length, which differs from its physical length by a factor referred to as end-correction. In addition to traditional parameters such as length and diameter, the author has investigated the effect of additional geometry features which are less commonly addressed in the technical literature, such as a diameter contraction or a bent section along the duct. The relative microphone position with respect to the pipe orifice and to the ground surface of the measurement environment has been investigated, showing negligible impact on the measurement results. The sound wave propagation within a pipe featuring a diameter contraction has then been analysed, showing the relationship between the pipe contraction shape and location and the pipe acoustic length.

Current developments in automotive industry such as hybrid powertrains and the continuously increasing demands on emission control systems, are pushing complexity still further. Validation of such systems lead to a huge amount of test cases and hence extreme testing efforts on the road. At the same time the pressure to reduce costs and minimize development time is creating challenging boundaries on development teams. Therefore, it is of utmost importance to utilize testing and validation prototypes in the most efficient way. It is necessary to apply high levels of instrumentation and collect as much data as possible. And a streamlined data pipeline allows the fleet managers to get new insights from the raw data and control the validation vehicles as well as the development team in the most efficient way. In this paper we will demonstrate a data-driven approach for validation testing.

With the increased number of variants, the preservation of a brand-specific vehicle DNA becomes more and more important. Paired with growing customer expectations, brand DNA can be a crucial point in the decision-making process of buying a new vehicle. Whereas the customer will assess the DNA subjectively during driving by evaluating the vehicle drive quality (“driveability”), most manufacturers are not merely relying on subjective evaluations by having test drivers perform maneuvers with prototype vehicles. Nowadays, the assessment is performed objectively during the vehicle development process. As a supporting measure, the Anstalt für Verbrennungskraftmaschinen List (AVL) has made the objective assessment tool AVL-DRIVE commercially available. Up to now, the AVL-DRIVE ratings had to be manually analyzed and checked for outliers. Low ratings and high deviations to a priori specified target values are a good starting point for the search of outliers.

The particulate emissions of two brake systems were characterized in a dilution tunnel optimized for PM10 measurements. The larger of them employed a fixed caliper (FXC) and the smaller one a floating caliper (FLC). Both used ECE brake pads of the same lining formulation. Measured properties included gravimetric PM2.5 and PM10, Particle Number (PN) concentrations of both untreated and thermally treated (according to exhaust PN regulation) particles using Condensation Particle Counters (CPCs) having 23 and 10 nm cut-off sizes, and an Optical Particle Sizer (OPS). The brakes were tested over a section (trip-10) novel test cycle developed from the database of the Worldwide harmonized Light-Duty vehicles Test Procedure (WLTP). A series of trip-10 tests were performed starting from unconditioned pads, to characterize the evolution of emissions until their stabilization. Selected tests were also performed over a short version of the Los Angeles City Cycle.

The reduction of vehicle exhaust particle emissions is a success story of European legislation. Various particle number (PN) counters and calibration procedures serve as tools to enforce PN emission limits during vehicle type approval (VTA) or periodical technical inspection (PTI) of in-use vehicles. Although all devices and procedures apply to the same PN-metric, they were developed for different purposes, by different stakeholder groups and for different target costs and technical scopes. Furthermore, their calibration procedures were independently defined by different stakeholder communities. This frequently leads to comparability and interpretation issues. Systematic differences of stationary and mobile PN counters (PN-PEMS) are well-documented. New, low-cost PTI PN counters will aggravate this problem. Today, tools to directly compare different instruments are scarce.

This paper describes a novel approach for modeling an automotive HVAC unit. The model consists of black-box models trained with experimental data from a self-developed measurement setup. It is capable of predicting the temperature and mass flow of the air entering the vehicle cabin at the various air vents. A combination of temperature and velocity sensors is the basis of the measurement setup. A measurement fault analysis is conducted to validate the accuracy of the measurement system. As the data collection is done under fluctuating ambient conditions, a review of the impact of various ambient conditions on the HVAC unit is performed. Correction models that account for the different ambient conditions incorporate these results. Numerous types of black-box models are compared to identify the best-suited type for this approach. Moreover, the accuracy of the model is validated using test drive data.

The development of modern combustion engines (spark ignition as well as compression ignition) for vehicles compliant with future oriented emission legislation (BS6, Euro VI, China 6) has introduced several technologies for improvement of both fuel efficiency as well as low emissions combustion strategies. Some of these technologies as there are high pressure multiple injection systems or sophisticated exhaust gas after treatment system imply substantial increase in test and calibration time as well as equipment cost. With the introduction of 48V systems for hybridization a cost- efficient enhancement and, partially, an even attractive alternative is now available. An overview will be given on current technologies as well as on implemented test procedures. The focus will be on solutions which have potential for the Indian market, i.e. solutions which can be implemented with moderate application effort for currently available compact and medium size cars.

Autonomous driving systems and connected mobility are the next big developments for the car manufacturers and their suppliers during the next decade. To achieve the high computing power needs and fulfill new upcoming requirements due to functional safety and security, heterogeneous processor architectures with a mixture of different core architectures and hardware accelerators are necessary. To tackle this new type of hardware complexity and nevertheless stay within monetary constraints, high performance computers, inspired by state of the art data center hardware, could be adapted in order to fulfill automotive quality requirements. The European Processor Initiative (EPI) research project tries to come along with that challenge for next generation semiconductors. To be as close as possible to series development needs for the next upcoming car generations, we present a hybrid semiconductor system-on-chip architecture for automotive.

In this paper a method for the identification of most significant vehicle parameters influencing the behavior of a lateral control system of autonomous car is presented. Requirements for the design stage of the controller need to consider many uncertainties in the plant. While most vehicle properties can be compensated by an appropriate tuning of the control parameters, other vehicle properties can change significantly during usage. The control system is evaluated based on performance measures. Analyzed parameters comprise functional tire characteristics, mass of the vehicle and position of its center of gravity. Since the parameters are correlated, but Sobol’ sensitivity analysis assumes decorrelated inputs, random variation yields no reasonable results. Furthermore, the variation of each parameter or set of parameters is not applicable since the numbers of required simulations is increased significantly according to input dimension.

Electrification globally shows promise in reducing greenhouse and noxious emissions. Although there is immense potential in such technologies penetrating across vehicle segments in the Indian market, the key lies in offering scalable, cost effective battery solutions suiting the diverse product and customer needs. This paper describes the development and possible applications of a low voltage battery system that fulfills the current needs on the Indian market. Based on real-world driving profiles the energy and power output required for the target platform are determined. Keeping in mind the Indian operating conditions, safety requirements, driving behavior, charging infrastructure, operational costs, supplier network and serviceability, technical requirements for such systems are described. Also, benchmarking data of current battery systems help to optimize the mechanical, thermal, and electrical layouts.

From an acoustical point of view, the integration of seatbelt retractors in a vehicle is a real challenge that has to be met early in the vehicle development process. The buzz and rattle noise of seat belt retractors is a weak yet disturbing interior noise. Street irregularities excite the wheels and this excitation is transferred via the car body to the mounting location of the retractor. Ultimately, the inertia sensor of the locking mechanism is also excited. This excitation can be amplified by structural resonances and generate a characteristic impact noise. The objective of this paper is to describe a simulation method for an early development phase that predicts the noise-relevant low frequency local modes and consequently the contact of the retractor with the mounting panel of the car body via the finite element method.

The reduction of environmentally harmful gases and the ambitions to reduce the exploitation of fossil resources lead to stricter legislation for all mobile sources. Legislative development significantly affected improvements in emissions and fuel consumptions over the last years, mainly measured under laboratory conditions. But real world operating scenarios have a major influence on emissions and it is already well known that these values considerably differ from officially published figures [1]. There are regulated emissions by the European Commission by means of real driving scenarios for passenger cars. A methodology to measure real drive emissions RDE is therefore well approved for automotive applications but was not adapted for two-wheeler-applications yet [2]. Hence measurements have been performed on-road and on chassis dynamometer for motorcycles with the state of the art RDE measurement equipment to be prepared for possible future legislation.

Real world operating scenarios have a major influence on emissions and fuel consumption. To reduce climate-relevant and environmentally harmful gaseous emissions and the exploitation of fossil resources, deep understanding concerning the real drive behavior of mobile sources is needed because emissions and fuel consumption of e.g. passenger cars, operated in real world conditions, considerably differ from the officially published values which are valid for specific test cycles only [1]. Due to legislative regulations by the European Commission a methodology to measure real drive emissions RDE is well approved for heavy duty vehicles and automotive applications but may not be adapted similar to two-wheeler-applications. This is due to several issues when using the state of the art portable emission measurement system PEMS that will be discussed.

Over the past decades, interior noise from wind noise or engine noise have been significantly reduced by leveraging improvements of both the overall vehicle design and of sound package. Consequently, noise sources originating from HVAC systems (Heat Ventilation and Air Conditioning), fans or exhaust systems are becoming more relevant for perceived quality and passenger comfort. This study focuses on HVAC systems and discusses a Flow-Induced Noise Detection Contributions (FIND Contributions) numerical method enabling the identification of the flow-induced noise sources inside and around HVAC systems. This methodology is based on the post-processing of unsteady flow results obtained using Lattice Boltzmann based Method (LBM) Computational Fluid Dynamics (CFD) simulations combined with LBM-simulated Acoustic Transfer Functions (ATF) between the position of the sources inside the system and the passenger’s ears.

The limitation of global warming to less than 2 °C till the end of the century is regarded as the main challenge of our time. In order to meet COP21 objectives, a clear transition from carbon-based energy sources towards renewable and carbon-free energy carriers is mandatory. Polymer electrolyte membrane fuel cells (PEMFC) allow an energy-efficient, resource-efficient and emission-free conversion of regenerative produced hydrogen. For these reasons fuel cell technologies emerge in stationary, mobile and logistic applications with acceptable cruising ranges as well as short refueling times. In order to perform applied research in the area of PEMFC systems, a highly integrated fuel cell analysis infrastructure for systems up to 150 kW electric power was developed and established within a cooperative research project by HyCentA Research GmbH and AVL List GmbH in Graz, Austria. A novel open testing facility with hardware in the loop (HiL) capability is presented.

A local Gaussian process regression approach is presented, which allows to model nonlinearities of internal combustion engines more accurate than global Gaussian process regression. By building smaller models, the prediction of local system behavior improves significantly. In order to predict a value, the algorithm chooses the nearest training points. The number of chosen training points depends on the intensity of estimated nonlinearity. After determining the training points, a model is built, the prediction performed and the model discarded. The approach is demonstrated with a benchmark system and air charge test bed measurements. The measurements are taken from a turbocharged SI gasoline engine with both variable inlet valve lift and variable inlet and exhaust valve opening angle. The results show how local Gaussian process regression outmatches global Gaussian process regression concerning model quality and nonlinearities in particular.

Air charge calibration of turbocharged SI gasoline engines with both variable inlet valve lift and variable inlet and exhaust valve opening angle has to be very accurate and needs a high number of measurements. In particular, the modeling of the transition area from unthrottled, inlet valve controlled resp. throttled mode to turbocharged mode, suffers from small number of measurements (e.g. when applying Design of Experiments (DoE)). This is due to the strong impact of residual gas respectively scavenging dominating locally in this area. In this article, a virtual residual gas sensor in order to enable black-box-modeling of the air charge is presented. The sensor is a multilayer perceptron artificial neural network. Amongst others, the physically calculated air mass is used as training data for the artificial neural network.

Automotive embedded systems have become very complex, are strongly integrated, and the safety-criticality and real-time constraints of these systems raise new challenges. The OSEK/VDX standard provides an open-ended architecture for distributed real-time capable units in vehicles. This is supported by the OSEK Implementation Language (OIL), a language aiming at specifying the configuration of these real-time operating systems. The challenge, however, is to ensure consistency of the concept constraints and configurations along the entire product development. The contribution of this paper is to bridge the existing gap between model-driven systems engineering and software engineering for automotive real-time operating systems (RTOS). For this purpose a bidirectional tool bridge has been established based on OSEK OIL exchange format files.