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Virtual testing has grown to be an efficient tool in vehicle passive safety design. Most simulations currently are deterministic. Since the responses observed in real-life and standardized tests are greatly affected by scatter, a stochastic approach should be adopted in order to improve the predictability of the numerical responses with respect to the experimental data. In addition, an objective judgement of the performance of numerical models with respect to experimental data is necessary in order to improve the reliability of virtual testing. In the European VITES & ADVANCE project the software tool Adviser was developed in order to fulfil these two requirements. With Adviser, stochastic simulations can be performed and the quality of the numerical responses with respect to the experimental can be objectively rated using pre-defined and user-defined objective correlation criteria. The software Adviser was used to develop a stochastic HybridIII 50th% Madymo numerical model.

The key-enabler for tomorrow's X-by-wire systems is the mastery of today's advanced active chassis control systems that are highly safety critical, distributed and complex. The only feasible way is to compose future X-by- wire systems with established and field approved functional management, components and infrastructure technologies, which are addressed in this paper.

The dramatic increase in data and information exchange has lead to increased communication network complexity within the subsystems of the powertrain itself as well as in all other subsystems of the vehicle. It is essential to manage this complexity during the development process. Applying new processes and methods such as vehicle functions and systems orientation in a top-down structural approach creates a powerful support in development of innovative powertrains. Several technical integration examples of powertrain functions are illustrated for the purpose of demonstrating customer-related advantages. Vehicle functions and systems orientation also has significant impact on organisational structures and cooperation methods to achieve maximum synergies as well as efficient vehicle communication architectures.

The thermal operational safety (TOS) of a vehicle ensures that no component exceeds its critical temperature during vehicle operation. To enhance the current TOS validation process, a data-driven approach is proposed to predict maximum component temperatures of a new vehicle project by leveraging the historical thermal wind tunnel data from previous vehicle projects. The approach intends to support engineers with temperature predictions in the early phase and reduce the number of wind tunnel tests in the late phase of the TOS validation process. In the early phase, all measurements of the new vehicle project are predicted. In the late phase, a percentage of measurements with the test vehicle used for the model training and the remaining tests are predicted with the trained ML model. In a first step, data from all wind tunnel tests is extracted into a joint dataset together with metadata about the vehicle and the executed load case.

The international standard ISO 26262 for functional safety of road vehicles claims processes and requirements for the entire product lifecycle of automotive electric and electronic systems. The demanded activities and work products within the standard are highly interconnected. Additionally, references to exemplarily external quality management standards or commonly recognized industry sources are given. Therefore, the application of functional safety processes in distributed development is challenging regarding description, understanding, analysis and planning of processes. To overcome these inconveniences, we provide a meta model extension for model-based architecture description languages regarding process description, organizational structures and resource assignment. This is related to the established “Business Process Model and Notation” (BPMN) according to ISO/IEC 19510:2013.

The idea of keeping a vehicle safe and secure throughout its whole life cycle, as well as having the opportunity to add functionality after initial delivery, is the key motivation behind automotive software updates. Today, safety or security issues that appear after vehicle delivery need to be resolved by starting a recall campaign. These campaigns require the vehicle user to visit a car repair workshop to get an update. Over The Air (OTA) software updates, being location-independent, can pave the way for higher update frequencies and more efficiency regarding customer satisfaction, resource consumption as well as safety and security. In this paper we analyze requirements for OTA software updates phrased in various standards and regulations as well as in existing development and type approval processes. Prevailing challenges for OTA updates are extracted to identify necessary activities and artifacts within the procedure.

In a voluntary agreement, the German automobile industry has undertaken to recover 95 percent by weight of End–of–Life Vehicles in the year 2015. In addition, the European draft directive on „End–of–Life Vehicles” recycling calls for evidence that at least than 85 percent by weight of the materials are suitable for material recycling. It is therefore essential while new vehicles are being developed to be in a position to assess their suitability for dismantling and recycling. An automobile consists of a large number of individual components, each of which must be examined separately before a well–founded statement regarding the overall recycling level can be made. For this purpose the BMW Group has developed its own dismantling software which permits virtual dismantling analysis even during a vehicle's development phase and thus enables suitability for recycling to be determined at the earliest possible time.

The analysis of the acoustic behavior of flow fields has gained importance in recent years, especially in the automotive industry. The comfort of the driver is heavily influenced by the noise levels and characteristics, especially during long distance drives. Simulation tools can help to analyze the acoustic properties of a car at an early stage of the development process. This work focuses on the low-frequency sound effects, which can be a significant noise component under certain operating conditions. As a first step in the fluid-structure interaction workflow, the flow around a series-production vehicle is simulated, including passenger cabin and underhood flow. The complexity of this model poses extensive demands on the simulation software, concerning meshing, turbulence modeling and level of parallelism. We conducted a transient simulation of the compressible fluid flow, using a hybrid RANS/LES approach.

Various algorithms such as emergency brake or crash warning using V2X communication have been published recently. For such systems hard real-time constraints have to be satisfied. Therefore latency needs to be minimized to keep the message processing delay below a certain threshold. Existing V2X systems based on the IEEE 1609 and SAE J2735 standards implement most message processing in software. This means the latency of these systems strongly depends on the CPU load as well as the number of incoming messages per time. According to safety constraints all messages of nearby vehicles have to be processed, whereby no prediction of the message importance can be given without analyzing the message content. Regarding the aforementioned requirements we propose a novel architecture that optimizes latency to satisfy the hard real-time constraints for V2X messages.

Thermal management has always played a significant role in reducing emissions and improving the fuel efficiency of the internal combustion engines (ICEs). With a momentous influence on the thermal behavior of the engines, the cooling system has a considerable impact on ICE performance. In this scenario, a method based on artificial neural network (ANN) of the cooling system was proposed in this work. Specific modeling methods were adopted for the various operating conditions and flow circuits of the cooling system. To describe these varied dynamic characteristics, four ANN sub-models were established to simulate the system at different temperature stages. As a closed-loop system, the temperature of the cooling system can be regarded as a result of all the experienced operating points. Therefore, integral parameters describing the trajectory of the system were selected as the input of the ANNs.

The start of combustion in a spark-ignited engine is highly dependent upon the conditions between the two spark plug electrodes at ignition. In addition to the air-to-fuel ratio in this gap, the gas flow is seen as most critical. In a combustion engine with a standard spark plug that protrudes into the combustion chamber, this gas flow is mainly dependent upon the tumble, swirl, or squish that is developed by the cylinder head and the piston movement. However, the air movement in the pre-chamber depends on the orientation of the orifices towards the main combustion chamber (MCC). This implies a less complex manipulation of local velocity in the electrode gap. This paper focuses on the effect of different pre-chamber designs on spark deflection by the inflowing gas. Therefore, a test rig was developed using the spark plug thread in the cylinder head of a motored engine.

The Deep Orange program is a concept vehicle development program focused on providing hands-on experience in design, engineering, prototyping and production planning as part of students’ two-year MS graduate education. Throughout this project, the team was challenged to create innovative concepts during the ideation phase as part of building the running vehicle. This paper describes the usability studies performed on two of the vehicle concepts that require driver interaction. One concept is a human machine interface (HMI) that uses a holographic companion that can act as a concierge for all functions of the vehicle. After creating a prototype using existing technologies and developing a user interface controlled by hand gestures, a usability study was completed with older adults. The results suggest the input method was not intuitive. Participants demonstrated better performance with tasks using discrete hand motions in comparison to those that required continuous motions.

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.

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.

Reductions of hardware costs as well as implementations of new innovative functions are the main drivers of today's automotive electronics. Indeed more and more resources are spent on adapting existing solutions to different environments. At the same time, due to the increasing number of networked components, a level of complexity has been reached which is difficult to handle using traditional development processes. The automotive industry addresses this problem through a paradigm shift from a hardware-, component-driven to a requirement- and function-driven development process, and a stringent standardization of infrastructure elements. One central standardization initiative is the AUTomotive Open System ARchitecture (AUTOSAR). AUTOSAR was founded in 2003 by major OEMs and Tier1 suppliers and now includes a large number of automotive, electronics, semiconductor, hard- and software companies.

The BMW Group is the first car manufacturer introducing FlexRay in series projects. Start of production is September 2006, where a pilot application is implemented in the chassis domain of the new BMW X5. In 2008 FlexRay will form a substantial part of the overall electronics architecture in form of a FlexRay network connecting multiple ECUs implementing chassis, powertrain, and driver assistance applications.

Service-oriented architectures (SOAs) are well-established solutions in the IT industry. Their use in the automotive domain is still on the way. Up to now, the automotive domain has taken advantage of service-oriented architectures only in the area of infotainment and not for systems with hard real-time requirements. However, applying SOA to such systems has just started but is missing suitable design and verification methodologies. In this context, we target to include the notion of model-based design to address fail-operational systems. As a result, a model-based approach for the development of fail-operational systems based on dynamic reconfiguration using a service-oriented architecture is illustrated. For the evaluation, we consider an example function of an automatically controlled braking system and analyze the reconfiguration time when the function fails.

Classical decentralized architectures based on large networks of microprocessor-based Electronic Control Units (ECU), namely those used in self-driving cars and other highly-automated applications used in the automotive industry, are becoming more and more complex. These new, high computational power demand applications are constrained by limits on energy consumption, weight, and size of the embedded components. The adoption of new embedded centralized electrical/electronic (E/E) architectures based on dynamically reconfigurable hardware represents a new possibility to tackle these challenges. However, they also raise concerns and questions about their safety. Hence, an appropriate evaluation must be performed to guarantee that safety requirements resulting from an Automotive Safety Integrity Level (ASIL) according to the standard ISO 26262 are met. In this paper, a methodology for the evaluation of dynamically reconfigurable systems based on centralized architectures is presented.