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The increasing power and safety requirements of electrical systems present a challenge for future automotive electrical networks. However, the modeling of use-profiles and the overall power consumption of electrical systems proves to be difficult as the number of potential on/off combinations of the loads is tremendous. Furthermore, the operation of some loads is correlated or depends upon the operating conditions. Thus, simple worst-case calculations applied to this complexity often lead to an over-specification of components. The proposed approach is based on the probabilities of loads being in the on-state and their respective interdependencies with each other and with boundary conditions such as time of day. Applying basic statistics and a new iterative algorithm, it allows the calculation of the probability of consumed total power for a given set of boundary conditions and of, very importantly, its expected continuous period.

The topology of an EDS, defined by the routing paths and by the location of the distribution boxes and the inline connectors, has a strong impact on weight and required amount of material, especially of copper, as well as on the manufacturing- and assembly time. Although a good part of the routing and packaging is fixed due to technical reasons and carry-over situations, in general there are enough optional paths and locations to allow up to several thousand alternative topologies. For these reasons, an optimization is possible as well as important. For such an optimization, in this paper a method is presented to concurrently minimize predefined criteria, e.g. the required copper, length of the wires, and the overall length of the wire bundles. It is based on designated algorithms for the variation of the topology, the routing, and the calculation of the optimization criteria as mentioned above.

Both the electrical portion of the powertrain and the rising number of auxiliary systems will considerably increase the electrical power requirements in future vehicles. In addition, multiple voltage supply levels will enhance the complexity of the electrical distribution system (EDS), while strict cost, weight, packaging, and safety constraints must be upheld, posing serious design challenges in terms of robustness, reliability and energy efficiency. Currently, a self-contained integral test or evaluation of the EDS is normally not applied. For such a purpose, quantitative quality criteria are introduced here which allow a comparative assessment of an EDS by addressing the dynamic and static stability of the supply voltage, the reliability of the fusing system, and the ability to provide the required electrical power. The presented approach uses both precisely-defined test scenarios and a comprehensive EDS test bench.

Reliable estimation of pumping and friction losses in modern combustion engines allows better control strategies aiming at optimal fuel consumption and emissions. Sophisticated simulation tools enable detailed simulation of losses based as well on physical and thermodynamic laws as well as on design data. Models embedded in these tools however are not real-time capable and cannot be implemented into the programs of the electronic control units (ECU's). In this paper an approach is presented that estimates the pumping and friction losses of a combustion engine with variable valve train (VVT). Particularly the pumping losses strongly depend on the control of variable valve train by ECU. The model is based on a combination of a globally physical structure embedding data driven sub models based on test bed measurements. Losses are separated concerning different component groups (bearings, pistons, etc.).

The integration of safety-critical and major power-consuming electrical systems presents a challenge for the development of future vehicle power nets. Reliability and performance of the electrical network must be enhanced in order to guarantee the power supply to essential electrical consumers at a sufficient degree of power quality. This paper presents a test bench for automotive electrical networks based on a hardware-in-the-loop (HiL) platform. The test bench is used to assess the power and temperature behavior of the wiring harness and the connected power consumers. This characterisation facilitates the development of new tailored automotive electrical networks to meet the increased requirements while efficiently using the available resources.

The paper presents a simulation environment for the test of driver assistance systems. It covers software-in-the-loop and hardware-in-the-loop test capabilities. In the hardware-in-the-loop (HiL) configuration, real components such as electronic control units (ECUs) and actuators are embedded in the system. First, requirements for a virtual environment are defined. They build the basis for the entire simulation. Special emphasis is given to the interaction between the simulated vehicle under test and its traffic environment. A virtual environment was developed in which the simulated vehicle can drive on a road together with the surrounding traffic. The simulation environment is composed mainly of a traffic scenario generator and a simulation of sensor behavior allowing the recognition of the vehicle's surroundings. Appropriate critical traffic scenarios are generated depending on the tested driver assistance system.

The modern engine development process is characterized by shorter development cycles and a reduced number of prototypes. However, simultaneously exhaust after-treatment and emission testing is becoming increasingly more sophisticated. It is expected that predictive simulation tools that encompass the entire powertrain can potentially improve the efficiency of the calibration process. The testing of an ECU using a HiL system requires a real-time model. Additionally, if the initial parameters of the ECU are to be defined and tested, the model has to be more accurate than is typical for ECU functional testing. It is possible to enhance the generalization capability of the simulation, with neuronal network sub-models embedded into the architecture of a physical model, while still maintaining real-time execution. This paper emphasizes the experimental investigation and physical modeling of the port fuel injected SI engine.

The modern engine design process is characterized by shorter development cycles and a reduced number of prototypes. However, simultaneously exhaust after-treatment and emission testing is becoming increasingly more sophisticated. The introduction of predictive real-time simulation tools that represent the entire powertrain can likely contribute to improving the efficiency of the calibration process. Engine models, which are purely based on physical first principles, are usually not capable of real-time applications, especially if the simulation is focused on cold start and warm-up behavior. However, the initial data definition for the ECU using a Hardware-in-the-Loop (HiL)-Simulator requires a model with both real-time capability and sufficient accuracy. The use of artificial intelligence systems becomes necessary, e.g. neural networks. Methods, structures and the realization of a hybrid real-time model are presented in this paper, which combines physical and neural network models.

The optimum design of an electrical distribution system (EDS) is based on the profound understanding and measurement of its thermal behavior, because this determines wire diameter and insulation material, has a major impact on the fusing strategy, and enables minimizing technical risk. Current methods of calculation require an extensive database, whereas the temperature measurements at selected points with normal sensors allow neither the precise rating of the actual insulation temperature within a wire bundle, nor the determination of the thermal impact of load currents. The presented approach is based on both a new measurement method and on a related evaluation algorithm. A common automotive wire is applied as a sensing device using its resistance temperature coefficient as the measurement principle.

Both the integration of safety-critical electrical systems and the increasing power requirements in vehicles present a challenge for electrical distribution systems in terms of reliability, packaging, weight, and cost. In this regard, the wire protection device is a key element, as it determines the reliability of the short circuit detection, the immunity against false tripping, and the wire diameters. Currently, in most cases, thermal fuses are used, due to their low cost and robust design. However, the description of their tripping behavior based only on steady-state currents is insufficient for the increasingly complex current profiles in vehicles. Thus, to achieve an optimum dimensioning of a fuse-wire combination, a profound understanding of the thermal behavior of both components under dynamic load conditions is mandatory. However, the FEM tools used for the thermal design of fuses are relatively slow, require huge calculation resources, and must be well-parameterized.

The integration of safety-critical and major power-consuming electrical systems presents a challenge for the development of future automotive electrical networks. Both reliability and performance must be enhanced in order to guarantee the power supply to essential electrical consumers at a sufficient degree of power quality. Often, in order to cope with these requirements, merely an upgrade of the existing wiring harness design is used, resulting in additional complexity, weight, and cost [3]. A characterization of the wiring harness and its electrical consumers facilitates a systematic optimization approach aimed at designing new automotive power networks [1, 5]. Measurement and analysis methods to characterise the thermal behaviour of the wiring harness have been presented and discussed in a previous paper [4] This paper presents and compares two methods aimed at modeling the electrical behavior of consumers at various voltages and temperatures.

A main focus of development in modern SI engine technology is variable valve timing, which implies a high potential of improvement regarding fuel consumption and emissions. Variable opening, period and lift of inlet and outlet valves enable numerous possibilities to alter gas exchange and combustion. However, this additional variability generates special demands on the calibration process of specific engine control devices, particularly under cold start and warm-up conditions. This paper presents procedures, based on Hardware-in-the-Loop (HiL) simulation, to support the classical calibration task efficiently. An existing approach is extended, such that a virtual combustion engine is available including additional valve timing variability. Engine models based purely on physical first principles are often not capable of real time execution. However, the definition of initial parameters for the ECU requires a model with both real time capability and sufficient accuracy.

In the last two decades the abilities of neural networks as universal approximation tools of non linear functional relationships as well as identification tools for nonlinear dynamic systems have been recognized and used successfully in many applications areas like modelling, control and diagnosis of technical systems. At the same time an increasing interest in optimal design methods is observed. Design of experiment is used to cope with the growing amount of measurements needed for the calibration of engines due to the rising number of control variables to be considered and the need for more accuracy in the description of engine behaviour to derive the best control strategies. In this paper a strategy for the integration of the concept of D-optimality in the learning process of neural networks is proposed. This leads to an optimal selection of data to be presented to the training procedure of the neural network aiming to a generation of robust neural models using fewer training data.

Within the scope of the development of autonomous vehicles, the mandatory reliability requirements of the electrical power supply, and consequently of the electrical distribution system (EDS), are increased considerably. In addition, the overall rising number of electrical functions leads to significantly higher electrical power demands, while strict cost, weight and packaging constraints must be upheld. Current developments focus on adding redundancies, enhancing physical robustness, or dimensioning critical components. New approaches address predictive power management, better diagnostic capabilities, and, the subject of this paper, alternative topologies and architectures [1]. These are derivations of the conventional tree structure, as well as ring- or linear-bus-based zonal architectures, which feature in part distributed storage devices or semiconductor switches that rearrange the power paths in case of a fault [2,3].

Both the rising number of electrical systems and the electrical part of the powertrain are considerably increasing the electrical power requirements of vehicles. As a consequence, multiple voltage supply levels have been introduced. However, even if only the 12V/48V configuration is considered, as in this paper, the number of possible electrical distribution system (EDS) architectures is greatly enlarged. Additional degrees of freedom are the allocation of the loads to the voltage levels, the dimensioning of new components, and the control strategy. Hence, the optimization of such architectures must be based on simulation, which allows the evaluation of a multitude of variants and test scenarios within an acceptable time frame. While strict cost, weight, and quality constraints must be upheld, the stability of the voltage supply is a major focus because a significant part of future electrical systems is highly safety-critical.

The thermal behavior of wires within the electrical distribution system (EDS) has a strong impact on the conductor cross section, the type of insulation, the derating, and the fusing system, and therefore on weight, cost, and reliability. Consequently, significant efforts have been made to develop sound static and dynamic thermal models for single wires and wire bundles. However, these models are based on the simplifying assumption that the object is completely surrounded by air, where, with the exception of free convection, airflow can be neglected, and where no interaction with other objects is considered. The approach presented in this paper takes into account the actual environment and routing within a vehicle, where some objects such as metal sheets can be considered as heat sinks and other objects, e.g. a motor block, as heat sources.

Currently, circuit breakers and, in most cases, thermal fuses are used for wire protection due to their low cost and robust design. As an alternative, solid state switches are being considered within future electrical distribution systems (EDS) for several reasons, e.g. resetability, diagnosis, smaller tolerances, and reduced dependencies on ambient temperature or arcing. Particularely if combined with benefits on the system level, such an application can be advantageous. The new approach presented in this paper uses a thermal model of the wire instead of only an emulation of the thermal fuse behavior. This allows, based on the electrical current profile, the calculation of the wire temperature and thus a robust and precise protection of the wire. In addition, it minimizes the probability of faulty switching, which is of particular importance with regard to safety-critical electrical functions.