FlexRay is a hybrid communication protocol tailored to the requirements in the automotive domain, supporting both time-triggered and event-triggered communication with high data-rates. The time-triggered static segment is commonly used for in-vehicle communication while the event-triggered dynamic segment is used for diagnostics and configuration. This paper addresses the problem of synthesizing schedules for the static FlexRay segment for asynchronous scheduling, following the design approach of current automotive architectures. Previous approaches largely focused on FlexRay 2.1 while the few existing approaches for FlexRay 3.0 are nonoptimal in several aspects. As a remedy, our framework makes use of all new features of version 3.0 while supporting the still predominantly used FlexRay 2.1, making it backward compatible. The following approaches are proposed: 1) a single-stage integer linear programming (ILP) approach that determines an optimal solution but does not scale; 2) a multistage ILP for combining previously generated subsystem schedules to a global schedule. It clearly improves the scalability but is not optimal. The multistage approach allows to integrate and convert existing FlexRay 2.1 schedules into a FlexRay 3.0 schedule which is important for legacy reasons, i.e., to reduce testing and certification efforts; 3) a greedy heuristic which scales well and obtains high quality solutions in comparison with the optimal solution, but is unsuitable to integrate existing schedules; and 4) metaheuristic approaches based on genetic algorithms or simulated annealing to evaluate the benefits of the proposed approaches.

Car manufacturers provide a growing variety of models and configuration options for customers. In the highly competitive and cost-driven automotive industry, managing these variants and increasing the reuse of functionality in different variants has therefore become one of the key challenges. This paper addresses the problem of generating variant schedules for time-triggered electrical/electronic-architectures. We propose a multischedule synthesis approach that determines the common parts of multiple variants and generates a schedule that exploits this commonality. Hence, a multischedule defines individual variant schedules with an identical schedule for applications common to different variants. This makes these applications variant-independent, thus, reduces the testing and integration efforts as it only has to be done once. Multischedule synthesis involves several challenges, viz., identification of commonality between different variants, schedule synthesis for common parts, and the integration of uncommon parts. Consequently, the schedule synthesis approach presented here is very different from conventional approaches. Finally, to address the increased complexity, we also propose a divide-and-conquer approach to partition the problem, improving the scalability.

Embedded systems are developed within a cost-driven process, such that many purpose-build systems share a common embedded platform. For instance, a shared hardware device might be applied in various use cases with different software. Here, the bare hardware is considered as platform while the final hardware/software system is the product that implements a certain set of features. In this paper, we propose an efficient design space exploration methodology that optimizes a set of embedded platforms. For this purpose, we separate the exploration into two stages: (1) A set of candidate platforms is determined within an optimization framework that can cope with different system models, considering the optimization objectives and feature coverage. (2) The final set of target platforms is determined as subset of the candidates by minimizing the expected objectives like cost, area, etc. The experimental results give evidence that our modular approach is more flexible and scalable than state-of-the-art methodologies.

Automotive Electrical/Electronic (E/E)-architectures consist of various components which are generally developed independently. Due to the increasing size and complexity, component integration is highly challenging and already slight modifications to components or subsystems often require expensive re-testing and re-validation. As a remedy, we propose a framework for modular architectures based on a data-centric description and a fully time-triggered scheduling. This modular design approach is enabled by a novel methodology for schedule integration where local schedules are defined independently for subsystems before being integrated into a global schedule. This divide-and-conquer approach significantly reduces the integration complexity while the system becomes highly composable. Our experimental results give evidence of the efficiency and versatility of the proposed approach, using networks based on a time-triggered automotive Ethernet.

This paper presents a framework for schedule integration of time-triggered systems tailored to the automotive domain. In-vehicle networks might be very large and complex and hence obtaining a schedule for a fully synchronous system becomes a challenging task since all bus and processor constraints as well as end-to-end-timing constraints have to be taken concurrently into account. Existing optimization approaches apply the schedule optimization to the entire network, limiting their application due to scalability issues. In contrast, the presented framework obtains the schedule for the entire network, using a two-step approach where for each cluster a local schedule is obtained first and the local schedules are then merged to the global schedule. This approach is also in accordance with the design process in the automotive industry where different subsystems are developed independently to reduce the design complexity and are finally combined in the integration stage. In this paper, a generic framework for schedule integration of time-triggered systems is presented. Further, we show how this framework is implemented for a FlexRay network using an Integer Linear Programming (ILP) approach which might also be easily adapted to other protocols. A realistic case study and a scalability analysis give evidence of the applicability and efficiency of our approach.

This paper gives an overview of the system architecture and software design challenges for Electric Vehicles (EVs). First, we introduce the EV-specific components and their control, considering the battery, electric motor, and electric powertrain. Moreover, technologies that will help to advance safety and energy efficiency of EVs such as drive-by-wire and information systems are discussed. Regarding the system architecture, we present challenges in the domain of communication and computation platforms. A paradigm shift towards time-triggered in-vehicle communication systems becomes inevitable for the sake of determinism, making the introduction of new bus systems and protocols necessary. At the same time, novel computational devices promise high processing power at low cost which will make a reduction in the number of Electronic Control Units (ECUs) possible. As a result, the software design has to be performed in a holistic manner, considering the controlled component while transparently abstracting the underlying hardware architecture. For this purpose, we show how middleware and verification techniques can help to reduce the design and test complexity. At the same time, with the growing connectivity of EVs, security has to become a major design objective, considering possible threats and a security-aware design as discussed in this paper.

This paper is an introduction to security challenges for the design of automotive hardware/software architectures. State-of-the-art automotive architectures are highly heterogeneous and complex systems that rely on distributed functions based on electronics and software. As cars are getting more connected with their environment, the vulnerability to attacks is rapidly growing. Examples for such wireless communication are keyless entry systems, WiFi, or Bluetooth. Despite this increasing vulnerability, the design of automotive architectures is still mainly driven by safety and cost issues rather than security. In this paper, we present potential threats and vulnerabilities, and outline upcoming security challenges in automotive architectures. In particular, we discuss the challenges arising in electric vehicles, like the vulnerability to attacks involving tampering with the battery safety. Finally, we discuss future automotive architectures based on Ethernet/IP and how formal verification methods might be used to increase their security.

Electric vehicles are emerging as a solution to environmental changes and transportation challenges in growing mega-cities. Compared to combustion engine vehicles, electric vehicles bring along new challenges in the CPS design. This paper gives an overview of several of these challenges and presents initial and potential solutions for the design of the electric powertrain and E/E architectures for electric vehicles. The powertrain consists of multiple complex CPS such as the battery, the electric motor, and a distributed energy management system. These components require a complex monitoring and control in order to guarantee safety and maintain a high efficiency. For this purpose, novel E/E architectures become necessary that facilitate a predictable distributed computation and communication, requiring a paradigm shift towards fully time-triggered systems. These E/E architectures will also enable novel CPS such as innovative driver assistance systems, x-by-wire control to further increase the safety and energy-efficiency of electric vehicles, and a pervasive interaction of the vehicle and the grid. Instead of focusing on the specific applications, this paper describes the prerequisite architectural changes that are necessary to implement these novel functions.