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In order to achieve high customer satisfaction and to avoid high warranty costs caused by component failures of the power-train of hybrid electric vehicles (HEV), car manufacturers have to optimize the dimensioning of these elements. Hence, it is obligatory for them to gain knowledge about the different types of vehicle usage being predominant all over the world. Therefore, in this paper we present a Data Mining system that employs a Random Forest (RF) based dissimilarity measure in the dimensionality reduction technique t-Distributed Stochastic Neighbor Embedding (t-SNE) to automatically identify and visualize different types of vehicle usage by applying these methods to aggregated logged on-board data, i.e., load spectrum data. This kind of data is calculated and recorded directly on the control units of the vehicles and consists of aggregated numerical data, like the histogram of the velocity signal or the traveled distance of a vehicle.

In this paper a new numerical methodology to compute component temperatures of a rotating cardan shaft is described. In general temperatures of the cardan shaft are mainly dominated by radiation from the exhaust gas system and air temperatures in the transmission tunnel and underbody. While driving the cardan shaft is rotating. This yields a uniform temperature distribution of the circumference of the shaft. However most simulation approaches for heat protection are nowadays steady-state computations. In these simulations the rotation of the cardan shaft is not considered. In particular next to the exhaust gas system the distribution of the temperatures of the cardan shaft is not uniform but shows hot temperatures due to radiation at the side facing the exhaust gas system and lower temperatures at the other side. This paper describes a new computational approach that is averaging the radiative and convective heat fluxes circumferentially over bands of the cardan shaft.

Air spring systems gain more and more popularity in the automotive industry and with the ever growing demand for comfort nowadays they are almost inevitable. Some significant advantages over conventional steel springs are appealing for commercial vehicles as well as for the modern passenger vehicles in the luxury class. Current production air spring systems exist in combination with hydraulic shock absorbers (integrated or resolved). An alternative is to use the medium air not only as a spring but also as a damper: a so-called air spring air damper. Air spring air dampers are force elements which could be a great step for the chassis technology due to their functionality (frequency selectivity, load levelling, load independent vibration behaviour, load dependent damping). Some of their design which avoid dynamic seals by the using of rubber bellows contribute to a better ride comfort.

Due to the diversity of Heavy Duty Vehicles (HDV), the European CO2 and fuel consumption monitoring methodology for HDVs will be based on a combination of component testing and vehicle simulation. In this context, one of the key input parameters that need to be accurately defined for achieving a representative and accurate fuel consumption simulation is the vehicle's aerodynamic drag. A highly repeatable, accurate and sensitive measurement methodology was needed, in order to capture small differences in the aerodynamic characteristics of different vehicle bodies. A measurement methodology is proposed which is based on constant speed measurements on a test track, the use of torque measurement systems and wind speed measurement. In order to support the development and evaluation of the proposed approach, a series of experiments were conducted on 2 different trucks, a Daimler 40 ton truck with a semi-trailer and a DAF 18 ton rigid truck.

Securing the desired strength and durability characteristics of suspension components is one of the most important topics in the development of commercial vehicles because these components undergo multiaxial variable amplitude loading. Leaf springs are essential for the suspension systems of trucks and they are considered as security relevant components in the product development phase. In order to guide the engineers in the design and testing department, a simulation method is developed as explained by Bakir et al. in a recently published SAE paper [1]. The main aim of the present study is to illustrate the validation of this simulation method for the durability of leaf springs based on the results from testing and measurements. In order to verify this CAE Method, the calculated stresses on the leaf springs are compared with the results of strain gage measurements and the fatigue failures of leaf springs are correlated with the calculated damage values.

The objective of the presented research is to analyze the cause-and-effect chain of the emergence of tire marks and to indentify how the intensity of a friction-related tire mark on asphalt or concrete pavements can provide additional information related to forces or slips at the marking wheels. Focusing on tire marks due to abrasive wear, the influences on the intensity of tire marks are analyzed based on three categories: vehicle dynamic parameters, tire and road properties, which determine the sensitivity of tire marking for a specific tire-road combination for constant vehicle dynamic parameters; and optical parameters, influencing the contrast of a given tire mark. The analysis includes a new objective method for the assessment of the tire mark intensities derived by photos of tire marks, generated with a tire measurement trailer. Additionally a test rig was developed to determine the tire marking sensitivity with reference marks under controlled friction conditions.

While the market share for diesel engines for LD vehicles in Europe has grown continuously in the past years, the market share in North America is still negligible. Until now, it has been possible to fulfill the limits for nitrogen oxides (NOx) both in Europe and in North America by engine measures alone, without using an active NOx aftertreatment system. With the introduction of Tier II Bin 8 and Tier II Bin 5 emissions legislation in the US in 2007, most new diesel applications will now require NOx aftertreatment. One of the possible technologies for the reduction of nitrogen oxides in lean exhaust gas is the NOx storage catalyst which has become the generally-accepted choice for engines with gasoline direct injection systems and which is also utilized in the current diesel Bluetec I systems from Daimler. For heavier applications urea-SCR is the preferred technology to fulfill NOx legislation limits.

An overview of Daimler?s progression to advance powertrain technology in a growth industry shows many different solutions to improvement in transportation. Daimler continues to make breakthroughs in technology development and application building on 125 years of automotive development. Optimization of current powertrains will enable a significant gain in CO2/mi reductions, that dependent on product mix can be augmented with additional technologies. There is however no bypass to some form of electrification, enabling efficiency gains and alternative forms of power supply. Development of hybrid powertrains continues in an established manner and enhanced development of further electrified powertrains are in development. Organizationally and technically, significant skills and adjustments need to continue to be undertaken enabling OEMs and in particular the supply base to develop optimized solutions efficiently. The outlook is bright for novel component development and innovation.

NH₃/urea SCR is a very effective and widely used technology for the abatement of NOx from diesel exhaust. The SCR mechanism is well understood and the catalyst behavior can be predicted by mathematical models - as long as operation above the temperature limit for AdBlue® injection is considered. The behavior below this level is less understood. During the first seconds up to minutes after cold start, complete NOx abatement can be observed over an SCR catalyst in test bench experiments, together with a significant increase in temperature after the converter (ca. 100 K). In this work these effects have been investigated over a monolith Cu-zeolite SCR catalyst. Concentration step experiments varying NO, NO₂ and H₂O have been carried out in lab scale, starting from room temperature. Further, the interaction of C₃H₆ and CO with NOx over the SCR has been investigated.

Since 2013 the new Daimler Aeroacoustic Wind Tunnel (AAWT) is in operation at the Mercedes-Benz Technology Center in Sindelfingen, Germany. This construction was the second stage of a wind tunnel center project, which was launched in 2007 and started with the climatic wind tunnels including workshop and office areas. The AAWT features a test facility for full-scale cars and vans with a nozzle exit area of 28 m2, a five-belt system, and underfloor balance to measure forces with best possible road simulation. With a remarkable low background noise level of the wind tunnel, vehicle acoustics can be investigated under excellent conditions using high-performance measurement systems. An overview is given about the building and the design features of the wind tunnel layout. The aerodynamic and aeroacoustic properties are summarized. During the first years of operation, further improvements regarding the wind tunnel background noise and vehicle handling were made.

In order to reduce fuel consumption in Fuel Cell Electric Vehicles, effective distribution of power demand between Fuel Cell and Battery is required. Energy management strategies can improve fuel economy by meeting power demand efficiently. This paper explains development of various energy management strategies for Fuel Cell Electric Vehicle with Lithium Ion Battery. Drive cycles used for optimization and analysis of the strategies are New European Drive cycles (NEDC), Japanese Drive cycles (JAP1015), City Drive cycles, Highway Drive cycles (FHDS) and Federal Urban Drive cycles (FUDS). All Fuel consumption and ageing calculations are done using backward model implemented in MATLAB/SIMULINK.

Brake system development and testing is spread over vehicle manufacturers, system and component suppliers. Test equipment from different sources, even resulting from different technology generations, different data analysis and report tools - comprising different and sometimes undocumented algorithms - lead to a difficult exchange and analysis of test results and, at the same time, contributes to unwanted test variability. Other studies regarding the test variability brought up that only a unified and unambiguous data format will allow a meaningful and comparative evaluation of these data and only standardization will reveal the actual reasons of test variability. The text at hand illustrates that a substantial part of test variability is caused by a misinterpretation of data and/or by the application of different algorithms.

Downsizing and direct injection in modern DISI engines can lead to fuel impinging on the cylinder walls. The interaction of liquid fuel and engine oil due to fuel impinging on the cylinder wall causes problems in both lubrication and combustion. To analyze this issue with temporal and spatial resolution, we developed a laser-induced fluorescence (LIF) system for simultaneous kHz-rate imaging of fuel and oil films on the cylinder wall. Engine oil was doped with traces of the laser dye pyrromethene 567, which fluoresces red after excitation by 532 nm laser radiation. Simultaneously, the liquid fuel was visualized by UV fluorescence of an aromatic “tracer” in a non-fluorescent surrogate fuel excited at 266 nm. Two combinations of fuel and tracer were investigated, iso-octane and toluene as well as a multi-component surrogate and anisole. The fluorescence from oil and fuel was spectrally separated and detected by two cameras.

The TOP TIERTM Diesel fuel standard was first established in 2017 to promote better fuel quality in marketplace to address the needs of diesel engines. It provides an automotive recommended fuel specification to be used in tandem with regional diesel fuel specifications or regulations. This fuel standard was developed by TOP TIERTM Diesel Original Equipment Manufacturer (OEM) sponsors made up of representatives of diesel auto and engine manufacturers. This performance specification developed after two years of discussions with various stakeholders such as individual OEMs, members of Truck and Engine Manufacturers Association (EMA), fuel additive companies, as well as fuel producers and marketers. This paper reviews the major aspects of the development of the TOP TIERTM Diesel program including implementation and market adoption challenges.

This paper makes a contribution toward a more efficient chassis durability process for the development of passenger cars, in which the simulation of relevant load data is a time-consuming part. This is especially due to the full vehicle model complexity which is usually determined by the demands of rough road simulations. However, for the load calculation on a racetrack, time saving model approaches that are more simplified might be sufficient. Our investigation comprises two levels of vehicle model complexity: one with all chassis parts modeled in a multibody system environment and one characteristic curve based model in an internal simulation environment. Both approaches consider an original chassis control system as a Software-in-the-Loop model. By the evaluation of real-world experiments the main influence factors in terms of durability are demonstrated. With the help of those highly sensitive durability criteria the measurement and simulation results are then compared.

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.

Aerodynamic design and thermal management are some of the most important tasks when developing new concepts for the flow around tractor-trailers. Today, both experimental and numerical studies are an integral part of the aerodynamic and thermal design processes. A variety of studies have been conducted how the aerodynamic design reduces the drag coefficient for fuel efficiency as well as for the construction of radiators to provide cooling on tractor-trailers. However, only a few studies cover the combined effect of the aerodynamic and thermal design on the air temperature of the under hood flow [8, 13, 16, 17, 20]. The objective of this study is to analyze the heat transfer through forced convection for a scaled Cab-over-Engine (CoE) tractor-trailer model with under hood flow. Different design concepts are compared to provide low under hood air temperature and efficient cooling of the sub components.

Safety-critical embedded software has to satisfy stringent quality requirements. All contemporary safety standards require evidence that no data races and no critical run-time errors occur, such as invalid pointer accesses, buffer overflows, or arithmetic overflows. Such errors can cause software crashes, invalidate separation mechanisms in mixed-criticality software, and are a frequent cause of errors in concurrent and multi-core applications. The static analyzer Astrée has been extended to soundly and automatically analyze concurrent software. This novel extension employs a scalable abstraction which covers all possible thread interleavings, and reports all potential run-time errors, data races, deadlocks, and lock/unlock problems. When the analyzer does not report any alarm, the program is proven free from those classes of errors. Dedicated support for ARINC 653 and OSEK/AUTOSAR enables a fully automatic OS-aware analysis.

The number of full electric and hybrid electric vehicles is rapidly growing [1][2][3]. The new technologies accompanying this trend are increasingly becoming a focal point of interest for rescue services. There is much uncertainty about the right techniques to free trapped occupants after an accident. The same applies to vehicle fires. Can car fires involving vehicles with a lithium ion traction battery be handled in the same way as conventional vehicle fires? Is water the right extinguishing agent? Is there a risk of explosion? There are many unanswered questions surrounding the topic of electric vehicle safety. The lack of information is a breeding ground for rumours, misinformation and superficial knowledge. Discussions on various internet platforms further this trend. Tests were conducted on three lithium ion traction batteries, which were fuel-fired until burning on their own. The batteries were then extinguished with water, a surfactant and a gelling agent.

The reduction of fuel consumption as well as the rising demands of customers regarding a vehicle’s driving dynamic and the legislator’s continually rising demands are a current issue in vehicle development. Hybrid vehicles offer a possibility to rise to this challenge. Realistic driving cycles are of utmost importance for the calibration of a hybrid vehicle’s operational strategy. Deriving replacement speed cycles from extensive customer data sets seems to be an approach for solving these problems. The contribution at hand describes the derivation of replacement cycles by using stochastic models, probabilistic (weighted) drawings and a combinatorial optimisation. The novelty value is that the characteristic influences of all drivers are being considered in the generation due to the stochastic modelling.