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Robustness and reliability are key elements for product success in the automotive market. On this purpose, the Design Review Based on Failure Modes (DRBFM) is a product development methodology to guide on potential risks assessment related to new design proposals. This paper shows the DRBFM structure and mindset for new products, using function and behavior evaluation. Moreover, the methodology will be demonstrated for a real automotive case, considering a new component design for Fuel Supply Module (FSM). The FSM is responsible to deliver fuel to the engine and maintain the pressure in the fuel rail during the spark engine operation. To fit these main functions, the electrical fuel pump inside the module must be always working submerged even if the fuel tank is almost empty. This the reason for this product has the jet pump component that is responsible to actively drag fuel during this worst fuel tank volume condition.

The fuel heating system has completed a decade of operation in flex fuel vehicles to enable engine start in cold start conditions. Besides its proven-in-use benefits to reliable engine start, some recent studies have shown advantages of heating fuel also with respect to emission reduction, drivability enhancement and fuel economy. These benefits make this system a potential candidate to meet the increasingly demanding requirements of the new Brazilian emission legislation PROCONVE L7/L8. To allow system operation, not only to cold starts but whenever required, it is necessary to evaluate the system behavior under different use cases to determine the new system’s mission profile. Therefore, a multitude of tests is required to collect this data for analysis. However, performing such tests with the actual system can be very costly and time-consuming, due to the high variance of test parameters, such as engine sizes, fuel blends, emission driving cycles, ambient temperature, etc.

Some research shows that the transport system is one of the main responsible for the emission of pollutants in the atmosphere. The growing demand for automobiles contrasts directly with the scarcity of inputs, planet temperature increasing and air quality degradation in large cities. This counterpoint is explored and discussed a lot, demanding that studies would be conducted to find out sustainable solutions in the production to end-customers. Instead of use fossil resources, one of the options to reduce gas emissions is the use of vehicles powered by electricity. When converting part of the vehicle's kinetic energy into electrical one its reduces emissions in the production electricity - power plants - as well burning gases in transport. Technological advances allow us to use Electronic Stability Control to generate environmental and safety results in mobility for next years.

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.

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.

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 first generation of heated cold start systems for flex fuel vehicles in Brazil were launched in 2009 and have solved most of the issues around the former gasoline sub-tank concept. This new technological approach focused on concerns like the user experience by having the need to fulfill the sub-tank, on complains related to possible old gasoline left inside, in the complexity of the electro mechanic nozzles and other possible improvements. Some years later, the second generation expanded the initial cold start application to a mature drivability enhancement and further possibility of usage as a support for emission reduction. A leaner electronic control and heat sink concept also represented an alternative to the first generation, and an engineered plastic fuel rail replaced the first metallic concept, which was an option to the initial concerns about the combination of high temperatures and fuel.

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.

Many software functions currently available in the engine control units have been developed for several years (decades in some cases), reengineered or adapted due to new requirements, what may add to their inherent complexity an unnecessary complication. This paper deals with the study and implementation of a software reengineering strategy for the embedded domain, which is in transfer from research department to product development, here applied to improve maintainability of flex fuel functions. The strategy uses the SCODE “Essential Analysis”, an approach for the embedded system domain. The method allows to reduce the system complexity to the unavoidable inherent problem complexity, by decomposing the system into smaller sub problems based on its essential physics. A case study was carried out to redesign a function of fuel adaptation. The analysis was performed with the support of a tool, which covers all the phases of the method.

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.

When new vehicles are being developed and will later be made available to the market, one of the most important characteristics that may influence the buying decision is the comfort available to the driver and passenger inside the vehicle. This comfort is partially limited by NVH issues inside the car for example. With the new technologies development, vehicles have become noiseless and, that’s why some vibrations from fuel supply module that weren't identifiable then now might show themselves a huge impact of noise inside the vehicles. So it is important to analyze the NVH behavior of fuel supply modules. To perform this study in a short time and with low cost, CAE simulations were done focusing on geometry optimization of the pump holder that keeps the electric fuel pump inside the fuel tank.

Timing evaluation methods help to design a robust and extendible E/E architecture (electric/electronic). BMW has introduced the systematic application of such methods in the E/E design process within the last three years. Meanwhile, most of the architectural changes are now verified by a tool-based, automatic real-time analysis. This has increased the accuracy of the network planning and productivity of the BMW network department. In this paper, we give an overview of the actual status of timing evaluations in BMW's E/E architecture design. We discuss acceptance criteria, analysis metrics, and design rules, as far as these are related to timing. We look specifically at automation options, as these improve the productivity further. We will see that timing analysis has matured and should be mandatory for application in mass production E/E architecture development. At the same time, there is room for future improvements.

Today's automotive software integration is a static process. Hardware and software form a fixed package and thus hinder the integration of new electric and electronic features once the specification has been completed. Usually software components assigned to an ECU cannot be easily transferred to other devices after they have been deployed. The main reasons are high system configuration and integration complexity, although shifting functions from one to another ECU is a feature which is generally supported by AUTOSAR. The concept of a Virtual Functional Bus allows a strict separation between applications and infrastructure and avoids source code modifications. But still further tooling is needed to reconfigure the AUTOSAR Basic Software (BSW). Other challenges for AUTOSAR are mixed integrity, versioning and multi-core support. The upcoming BMW E/E-domain oriented architecture will require all these features to be scalable across all vehicle model ranges.

The potential to reduce the cost of embedded software by standardizing the application behavior for Automotive Body and Comfort domain functions is explored in this paper. AUTOSAR, with its layered architecture and a standard definition of the interfaces for Body and Comfort application functions, has simplified the exchangeability of software components. A further step is to standardize the application behavior, by developing standard specifications for common Body and Comfort functions. The corresponding software components can be freely exchanged between different OEM/Tier-1 users, even if developed independently by multiple suppliers. In practice, individual OEM users may need to maintain some distinction in the functionality. A method of categorizing the specifications as ‘common’ and ‘unique’, and to configure them for individual applications is proposed. This allows feature variability by means of relatively simple adapter functions.

Multicore-based ECUs are increasingly used in embedded automotive software systems to allow more demanding automotive applications at moderate cost and energy consumption. Using a high number of parallel processors together with a high number of executed software components results in a practically unmanageable number of deployment alternatives to choose from. However correct deployment is one important step for reaching timing goals and acceptable latency, both also a must to reach safety goals of safety-relevant automotive applications. In this paper we focus at reducing the complexity of deployment decisions during the phases of allocation and scheduling. We tackle this complexity of deployment decisions by a mixed constructive and analytic approach.

Nowadays, a continually growing system complexity due to the development of an increasing number of vehicle concepts in a steadily decreasing development time forces the engineering departments in the automotive industry to a deepened system understanding. The virtual design and validation of individual components from subsystems up to full vehicles becomes an even more significant role. As an answer to the challenge of reducing complete hardware prototypes, the virtual competence in NVH, among other methods, has been improved significantly in the last years. At first, the virtual design and validation of objectified phenomena in analogy to hardware tests via standardized test rigs, e.g. four poster test rig, have been conceived and validated with the so called MBS (Multi Body Systems).

The BMW Group has introduced electric cars to the market with the MINI E already in 2009. The next step will be the launch of the BMW ActiveE in 2011, followed by the revolutionary Mega City Vehicle in 2013. The presentation will explain the BMW Group strategy for implementing sustainable mobility. A focus will be emobility, the use of carbon fiber and the holistic sustainability approach of BMW Group?s project i. Reference will be made to the research results of the MINI E projects in the US and in Europe. Presenter Andreas Klugescheid, BMW AG