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Introduction The introduction of Ethernet and Gigabit Ethernet [2] as the main invehicle network infrastructure is the technical foundation for different new functionalities such as piloted driving, minimizing the CO2- footprint and others. The high data rate of such systems influences also the used microcontrollers due the fact that a big amount of data has to be transferred, encrypted, etc. Figure 1 Motivation - Vehicles will become connected to uncontrolled networks The usage of Ethernet as the in-vehicle-network enables the possibility that future road vehicles are going to be connected with other vehicles and information systems to improve system functionality. These previously closed automotive systems will be opened up for external access (see Figure 1). This can be Car2X connectivity or connection to personal devices. Allowing vehicle systems to communicate with other systems that are not within their physical boundaries impose a previously non-existing security problem.

The constant motivation for lower fuel consumption and emission levels has always been in the minds of most auto makers. Therefore, it is important to have precise control of the fuel being delivered into the engine. Gasoline Port fuel injection has been a matured system for many years and cars sold in emerging markets still favor such system due to its less system complexity and cost. This paper will explain injection control strategy of today during development, and especially the injector dead-time compensation strategy in detail and how further improvements could still be made. The injector current profile behavior will be discussed, and with the use of minimum hardware electronics, this paper will show the way for a new compensation strategy to be adopted.

In recent years, we see more and more ECUs integrating a huge number of application software components. This process mostly results from the increasing amount of so called in-house software in various fields like electric-drive, chassis and driver assistance systems. The software development for these systems is partially moved from the supplier to the car manufacturers. Another important trend is the introduction of new network architectures intending to meet the growing communication requirements. For such ECUs the software integration scenarios become more complicated, as more quality of service requirements with regards to timing, safety and security need to be considered [2]. Multi-core microcontrollers offer even more potential variants for integration scenarios. Understanding the interaction between the different software components, not only from a functional, but also from a timing view, is a key success factor for modern electronic systems [6,7,8,9].

End of Line tests are brief set of tests intended to evaluate ECU's in order to ensure correct functioning of its intended functionality. As these tests are executed on the production line, available time to perform these tests is limited. On one hand, faster production demands require these tests and its framework to be designed in a time optimized manner. On the other hand, increase in ECU functionality translates to an increase in test's functional coverage, requiring more time. Therefore the time taken to execute the tests reaches a critical point in overall ECU production. Availability of multicore microcontrollers with increase in clock speed can increase the performance of end of line tests, but design challenges e.g. synchronization do not guarantee a linear performance increase. Therefore, design of test execution framework is absolutely critical to increase performance of test execution.

The German funded project ARAMiS included work on several demonstrators one of which was a multicore approach on large scale software integration (LSSI) for the automotive domain. Here BMW and Audi intentionally implemented two different integration platforms to gain both experience and real life data on a Hypervisor based concept on one side as well as using only native AUTOSAR-based methods on the other side for later comparison. The idea was to obtain figures on the added overhead both for multicore as well as safety, based on practical work and close-to-production implementations. During implementation and evaluation on one hand there were a lot of valuable lessons learned about multicore in conjunction with safety. On the other hand valuable information was gathered to make it finally possible to set up a cost model for estimation of potential overhead generated by different integration approaches for safety related software functions.

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.

The powertrain module is being introduced to embedded System on Chips (SoCs) designed to increase available computational power. These high-performance SoCs have the potential to enhance the computational power along with providing on-board resources to support unexpected feature growth and on-demand customer requirements. This project will investigate the radial basis function (RBF) using the Gaussian process (GP) regression algorithm, the ETAS ASCMO tool, and the hardware accelerator Advanced Modeling Unit (AMU) being introduced by Infineon AURIX 2nd Generation. ETAS ASCMO is one of the solutions for data-driven modeling and model-based calibration. It enables users to accurately model, analyze, and optimize the behavior of complex systems with few measurements and advanced algorithms. Both steady state and transient system behaviors can be captured.

The current automotive electronic and electrical (EE) architecture has reached a scalability limit and in order to adapt to the new and upcoming requirements, novel automotive EE architectures are currently being investigated to support: a) an Ethernet backbone, b) consolidation of hardware capabilities leading to a centralized architecture from an existing distributed architecture, c) optimization of wiring to reduce cost, and d) adaptation of service-oriented software architectures. These requirements lead to the development of Zonal EE architectures as a possible solution that require appropriate adaptation of used security mechanisms and the corresponding utilized hardware trust anchors. 1 The current architecture approaches (ECU internal and in-vehicle networking) are being pushed to their limits, simultaneously, the current embedded security solutions also seem to reveal their limitations due to an increase in connectivity.

The trend towards even more sophisticated driver assistance systems and growing automation of driving sets new requirements for the robustness and availability of the involved automotive systems. In case of an error, today it is still sufficient that safety related systems just fail safe or silent to prevent safety related influence of the driving stability resulting in a functional deactivation. But the reliance on passive mechanical fallbacks in which the human driver taking over control, being inevitable in such a scenario, is expected to get more and more insufficient along with a rising degree of driving automation as the driver will be given longer reaction time. The advantage of highly or even fully automated driving is that the driver can focus on other tasks than controlling the car and monitoring it’s behavior and environment.

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.

Functional safe products conforming to the ISO 26262 standard are getting more important for automotive applications wherein electronic takes more and more response for safety relevant operations. Consequently safety mechanisms are needed and implemented in order to reach defined functional safety targets. To prove their effectiveness diagnostic coverage provides a measurable quantity. A straight forward safety mechanism for sensor systems can be established by redundant signal paths measuring the same physical quantity and subsequently performing an independent output difference-check that decides if the data can be transmitted or an error message shall be sent. This paper focuses on the diagnostic coverage figure calculation of such data correlation-checks for linear sensors which are also shown in ISO 26262 part5:2011 ANNEX D2.10.2.

For highly automated driving, commercial vehicles require an Electric/Electronic (E/E) architecture, which - in addition to sensor fusion - ensures safety-critical processes such as steering and braking at all times. Among other things, a redundant 24 V supply with corresponding disconnection is required. The battery switch is a key component. Commercial, construction, and agricultural vehicles (CAV) need to operate at the highest possible availability and the lowest possible cost of ownership. This is why automated and autonomous driving has the potential to revolutionize the CAV sector. Driverless machines can be operated around the clock and almost non-stop. Platooning allows automated, interconnected trucks to drive in a convoy and very close to each other. Platooning saves fuel.

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.