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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.

Emissions tests were performed to study the operating characteristics of a wide range air/fuel ratio (AFR) sensor in closed loop control. The AFR sensor used here has an output voltage with respect to AFR that is linear and can be characterized by a fourth order polynomial function. For this study the output signal of the AFR sensor was fed into a General Control Unit (GCU). The GCU converted this analog input signal into a square wave similar to a lambda sensor. The output from the GCU was fed into the Engine Control Unit (ECU) of the 3.8L, V6 test engine to control the engine A/F ratio. Emissions tests were conducted in closed loop mode under steady state and transient condition. Emissions of HC, CO and NOx using the AFR sensor will be shown. Results of these tests showed that the AFR sensor allowed for precise control of the AFR at the stoichiometric point (λ = 1.0).

Systems and network integration is a major challenge, and systematic analysis of the complex dynamic timing effects becomes key to building reliable systems. Very often, however, systematic analysis techniques are (considered) too restrictive with respect to established design practice. In this paper we present lessons learned from real-world case studies, in which OEMs have used the new SymTA/S scheduling analysis technology to evaluate different network choices with minimum effort. Thanks to its flexibility and supplier independence, SymTA/S can be applied in non-ideal situations, where other, more restricted technologies are inherently limited. Finally, we put the technology into relation with ongoing standardization activities.

Developers of safety-critical real-time systems have to ensure that their systems react within given time bounds. Ideally, the system is designed to provide sufficient computing power and network bandwidth, is cost efficient and provides the necessary safety level. To achieve this goal, three challenges have to be addressed. First, it must be possible to account for timing during early development stages in the architecture exploration phase. Second, during software development, timing behavior and the effects of software changes on timing must be observable. Third, there must be a technology for formally verifying the final timing behavior for industry-size applications. In this article we present a comprehensive methodology for dealing with timing which addresses all three issues based on state-of-the-art commercial tools.

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.

This paper proposes a new development method for highly reliable real-time embedded control systems using a CPU model-based hardware/software co-simulation. We take an approach that allows the full simulation of the virtual mechanical control system including CPU and object code level software. In this paper, Renesas SH-2A microcontroller model was developed on CoMET™ platform from VaST Systems Technology. A ETC (Electronic Throttle Control) system and engine control system were chosen to prove this concept. The ETB (Electronic Throttle Body) model on Saber® simulator from Synopsys® or engine model on MATLAB®/Simulink® simulator from MathWorks can be simulated with the SH-2A model. To help the system design, debug and evaluation, we developed an integrated behavior analyzer, which can display CPU behavior graphically during the simulation without affecting the simulation result, such as task level CPU load, interrupt statistics, software variable transition chart, and so on.

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.

To prevent the severe consequences of unsafe driving behaviors, it is crucial to monitor and analyze the state of the driver. Developing an effective driver state monitoring (DSM) systems is particularly challenging due to limited computation capabilities of embedded systems in automobiles and the need for finishing processing in real-time. However, most of the existing research work was conducted in a lab environment with expensive equipment while lacking in-car benchmarking and validation. In this paper, a DSM system that estimates driver's alertness and drowsiness level as well as performs emotion detection built with a cost-effective embedded system is presented. The proposed system consists of a mono camera that captures driver's facial image in real-time and a machine learning based detection algorithm that detects facial landmark points and use that information to infer driver's state.

The usage of Compressed Natural Gas (CNG) engines is increasing as requirements for cleaner emissions are required by state and federal agencies such as C.A.R.B. and E.P.A. Also, to further reduce emission levels, tighter air/fuel ratio control is required. There are many ways to control air/fuel ratio on a CNG engine. It can be performed in a feedforward method, a feedback method or a combination of both. CNG fuel can be introduced to the engine via single-point injection, multi-point injection or with an air/gas mixer. Mixer-type and single-point injection are good candidates for the application of a gas flow sensor for accurate air/fuel ratio measurement. Reduction of valve hysteresis can also be achieved. Fuel delivery and control systems cost can be kept low compared to using multi-point injection where high flow injectors are required for each cylinder. A gas flow sensor is placed in the CNG stream to monitor mass gas flow rate.

A new hydrogen flow sensor was designed and evaluated based on the concept of hot wire anemometry. This sensor is designed to measure the mass flow rate of hydrogen gas used in (but not limited to) proton exchange fuel cell, PEFC. The conceptual evaluation was initiated by deriving an electro-thermal model of the hot wire required for sensing hydrogen velocity. The modeling is done via a mechatronics software tool, Saber™. This model was validated using air as a medium. Simulated and experimental performance results and safety issues are presented and discussed in this paper. Fail safe methods and effectiveness have been investigated along with hydrogen ignition temperatures with varying hydrogen to air ratio.

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.

Demand for predictive powertrain control is rapidly increasing with the recent advancement of Advanced Driving Assistance Systems (ADAS) and Autonomous Driving (AD). The full or semi-autonomous functions could be leveraged to realize better user acceptance as well as powertrain efficiency of the connected vehicle utilizing the proposed Drive Horizon. The sensors of automated driving provide perception of surrounding driving environment which is required to safely navigate the vehicle in real-world driving scenarios. The proposed Drive Horizon provides real-time forecast of driving environment that a vehicle will encounter during its entire travel. This paper summarizes the vehicle’s future speed prediction technique which is an integral part of Drive Horizon for optimized energy control of the vehicle. The prediction model has been developed that integrates information from multiple sources including vehicle GPS, traffic information and map data.

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.

Today, gated networks with several buses are becoming standard in automotive E/E-systems but are evolving differently among the various vehicle manufactures, with different topologies, combinations of bus protocols, and speeds. Making the right architecture decisions requires systematic evaluation of the many alternatives during early design stages. However, there are many trade-offs in terms of performance, cost, extensibility, etc.. In this context, scheduling analysis is a powerful tool. It clarifies performance, end-to-end timing, and dynamic behavior. This enables evaluation of networking alternatives, foresight of bottlenecks, and provides guidance in the design process. In the paper, the application of scheduling analysis in automotive network exploration and optimization will be demonstrated. Specific emphasize will be put on end-to-end timing, migration from CAN to FlexRay, black-box integration and early-stage assumptions, extensibility, and trade-offs.

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.