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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.

Software complexity of vehicles is constantly growing especially with additional autonomous driving features being introduced. This increases the risk for bugs in the system, when the car is delivered. According to a car manufacturer, more than 90% of availability problems corresponding to Electronic Control Unit (ECU) functionality are either caused by software bugs or they can be resolved by applying software updates to overcome hardware issues. The main concern are sporadic errors which are not caught during the development phase since their trigger condition is too unlikely to occur or is not covered by the tests. For such systems, there is a need of safe and secure infield diagnosis. In this paper we present a tool software architecture with remote access, which facilitates standard read/write access, an efficient channel interface for communication and file I/O, and continuous trace.

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.

The C166 family, based on a 16-bit core; it is nowadays an enormous success in automotive, in particular in PowerTrain. This component is the right answer for the automotive real time applications of today. It is with both, automotive customer requirements and a long automotive experience in semi-conductors that this new generation 32-bit family is borne. The objective of this document is to provide and comment on automotive requirements in terms of the new micro-controller, to show the benefits for the applications and explain how the AUDO architecture fulfils these requirements.

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.

Rising oil prices and increasing strict emission legislation force vehicle manufacturers to reduce fuel consumption of future vehicles. In order to meet this target, the process of converting fuel into useable energy and the use of this energy by the different energy-consuming vehicle's subsystems have to be examined. Vehicles' subsystems consist of energy-supplying, energy-consuming, and in some cases energy-storing components. Due to the high complexity of these systems and their interaction, optimization of their energy efficiency is a challenging task. By introducing individual operational strategies for each subsystem, it is possible to increase the energy efficiency for a specific function. To further improve the vehicle's overall energy efficiency, holistic control strategies are introduced that distribute the energy between the subsystems intelligently.

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.

This paper presents a reliability study of a directly cooled IGBT module after a test drive of 85,000 Km in a fuel cell electric vehicle, as well as of an indirectly cooled IGBT module after a test drive of 200,000km in a hybrid car on public roads. At the end of the test drive, the inverter units were disassembled and analyzed with regard to the lifetime consumption. First, electrical measurements were carried out and the results were compared with the ones obtained directly after module production (End of Line test). After that, ultrasonic microscopy was performed in order to investigate any delamination in the solder layers. As a third step, an optical inspection was performed to monitor damages in the housing, formation of cracks or degradation of wire bonds. The results show none of the depicted failure modes could be found on the tested power modules after the field test. Obviously, no significant life time consumption could be observed.

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 driving comfort influences the customer purchase decision; hence it is an important aspect for the vehicle development. To better quantify the comfort level and reduce the experiment costs in the development process, the subjective comfort assessment by test drivers is nowadays more and more replaced by the objective comfort evaluation. Hereby the vibration comfort is described by scalar objective characteristic parameters that correlate with the subjective assessments. The correlation analysis requires the assessments and measurements at different vehicle vibration. To determine the objective parameters regarding the powertrain excitations, most experiments in the previous studies were carried out in several test vehicles with different powertrain units.

The technology in the automotive industry is evolving rapidly in recent times. Thus, with the development of new technologies, the challenges are also ever-increasing from an Electromagnetic Interference and Susceptibility (EMI/EMC) perspective. A lot of the latest technologies in Adaptive Driver Assistance Systems (ADAS), which include Rear Drive Assist, Blind Spot Detection (BSD), Lane Change Assist (LCA) to name a few, and other features like Anti-Braking System (ABS), Emergency Brake Assist (EBD) etc. rely heavily on different types of sensors and their detection circuitry. In addition, a lot of other internal functions in the Engine Control Unit (ECU) also depend on such sensors’ functionalities. Thus, it becomes imperative to study the potential impact of higher field emissions on the immunity behaviour of the sensors.

The increasing legal requirements for safety, emission reduction, fuel economy and onboard diagnosis systems push the market for more innovative solutions with rapidly increasing complexity. Hence, the embedded systems that will have to control the automobiles have been developed at such an extent that they are now equivalent in scale and complexity to the most sophisticated avionics systems. This paper will demonstrate the key elements to provide a powerful, scalable and configurable solution that offers a migration pass to evolution and even revolution of automotive Sensors and Sensor interfaces. The document will explore different architectures and partitioning. Sensor technologies such as magnetic field sensors based on the hall effect as well as bulk and surface silicon micro machined sensors will be mapped to automotive applications by examples. Functions such as self-test, self-calibration and self-repair will be developed.

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.

Classic vehicle production had limitations in bringing the driving commands to the actuators for vehicle motion (engine, steering and braking). Steering columns, hydraulic tubes or steel cables needed to be placed between the driver and actuator. Change began with the introduction of e-gas systems. Mechanical cables were replaced by thin, electric signal wires. The technical solutions and legal standardizations for addressing the steering and braking systems, were not defined at this time. Today, OEMs are starting E/E-Architecture transformations for manifold reasons and now have the chance to remove the long hydraulic tubes for braking and the solid metal columns used for steering. X-by-wire is the way forward and allows for higher Autonomous Driving (AD) levels for automated driving vehicles. This offers new opportunities to design the vehicle in-cabin space. This paper will start with the introduction of x-by-wire technologies.

As the demand for enhanced comfort, safety and differentiation with new features continues to grow and as electronics and software enable most of these, the number of electronic units or components within automobiles will continue to increase. This will increase the overall system complexity, specifically with respect to the number of controller actuators such as e-motors. However, hard constraints on cost and on physical boundaries such as maximum power dissipation per unit and pin-count per unit/connector require new solutions to alternative system partitioning. Vehicle manufacturers, as well as system and semiconductor suppliers are striving for increased scalability and modularity to allow for most cost optimal high volume configurations while featuring platform reuse and feature differentiation. This paper presents new semiconductor based approaches with respect to technologies, technology mapping and assembly technologies.

In the case of a side impact the decision to deploy an airbag has to be taken much faster as it would be required for a front impact. Furthermore, there is a significant spread of the measurable acceleration depending on which pillars of the cars side are hit. Measuring the pressure inside the door as a direct result of an impact, the deformation of the door becomes observable. Based on pressure measurements side impacts can be detected much faster and more reliable. Therefore side airbag pressure sensors are established as add-on or replacement for side airbag acceleration sensors. This paper will present a Side Airbag Chip Set comprising of a side airbag pressure sensor and a satellite receiver. The system architecture and the partitioning between a single chip solution for the side airbag pressure sensor module plus the compatible satellite receiver will be described.

Driven by the growing internet and remote connectivity of automobiles, combined with the emerging trend to automated driving, the importance of security for automotive systems is massively increasing. Although cyber security is a common part of daily routines in the traditional IT domain, necessary security mechanisms are not yet widely applied in the vehicles. At first glance, this may not appear to be a problem as there are lots of solutions from other domains, which potentially could be re-used. But substantial differences compared to an automotive environment have to be taken into account, drastically reducing the possibilities for simple reuse. Our contribution is to address automotive electronics engineers who are confronted with security requirements. Therefore, it will firstly provide some basic knowledge about IT security and subsequently present a selection of automotive specific security use cases.

The development of highly automated driving functions (AD) recently rises the demand for so called Fail-Operational systems for native driving functions like steering and braking of vehicles. Fail-Operational systems shall guarantee the availability of driving functions even in presence of failures. This can also mean a degradation of system performance or limiting a system’s remaining operating period. In either case, the goal is independency from a human driver as a permanently situation-aware safety fallback solution to provide a certain level of autonomy. In parallel, the connectivity of modern vehicles is increasing rapidly and especially in vehicles with highly automated functions, there is a high demand for connected functions, Infotainment (web conference, Internet, Shopping) and Entertainment (Streaming, Gaming) to entertain the passengers, who should no longer occupied with driving tasks.

The newly released Distributed System Interface 3 (DSI3) Bus Standard specification defines three modulation levels form which 16 valid symbols are coded. This complex structure is best decoded with symbol pattern recognition. This paper proposes a simplification of the correlation score calculation that sharply reduces the required number of operations. Additionally, the paper describes how the pattern recognition is achieved using correlation scores and a decoding algorithm. The performance of this method is demonstrated by mean of simulations with different load models between the master and the sensors and varying noise injection on the channel. We prove than the pattern recognition can decode symbols without any error for up to 24dBm.