Entwicklungstendenzen im Bereich der Fahrzeugelektronik

Applications in the automobile sector, wired or unwired, are today often integrated into a network of sensors and actors as well as in service functions, visualization, and entertainment. The paper presents an innovative platform, which is applicable for automotive and automation applications. & IT systems for automobiles and for business applications took a very different development direction.

? In the automotive sector a lot of proprietary IT systems have been developed.

? The increasing requirements of automotive applications require platform concepts, which are based on open standards.

     

Evolving information systems: meeting the ever-changing environment

Abstract. To meet the demands of organizations and their ever-changing environment, information systems are required which are able to evolve to the same extent as organizations do. Such a system has to support changes in all time-and application-dependent aspects. In this paper, requirements and a conceptual framework for evolving information systems are presented. This framework includes an architecture for such systems and a revision of the traditional notion of update. Based on this evolutionary notion of update (recording, correction and forgetting) a state transition-oriented model on three levels of abstraction (event level, recording level, correction level) is introduced. Examples are provided to illustrate the conceptual framework for evolving information systems.     

RELAX: a language to address uncertainty in self-adaptive systems requirement

Self-adaptive systems have the capability to autonomously modify their behavior at run-time in response to changes in their environment. Self-adaptation is particularly necessary for applications that must run continuously, even under adverse conditions and changing requirements; sample domains include automotive systems, telecommunications, and environmental monitoring systems. While a few techniques have been developed to support the monitoring and analysis of requirements for adaptive systems, limited attention has been paid to the actual creation and specification of requirements of self-adaptive systems. As a result, self-adaptivity is often constructed in an ad-hoc manner. In order to support the rigorous specification of adaptive systems requirements, this paper introduces RELAX, a new requirements language for self-adaptive systems that explicitly addresses uncertainty inherent in adaptive systems. We present the formal semantics for RELAX in terms of fuzzy logic, thus enabling a rigorous treatment of requirements that include uncertainty. RELAX enables developers to identify uncertainty in the requirements, thereby facilitating the design of systems that are, by definition, more flexible and amenable to adaptation in a systematic fashion. We illustrate the use of RELAX on smart home applications, including an adaptive assisted living system.     

基于ZigBee的汽车空调控制系统

针对汽车空调系统的实时性要求,提出了一种基于ZigBee技术的汽车空调控制系统,给出了控制系统的网络结构、传感器节点和系统主节点电路,设计了控制系统的网络协议和传感器节点以及主控制节点的程序流程。为汽车空调控制提供了一种新的技术。     

Real-time collaboration in design engineering: an expensive fantasy or affordable reality?

The purpose of this paper is to discuss the main issues that are both driving and impeding the implementation and use of CSCW systems within the automotive industry. The paper begins by describing the current competitive pressures within the European Automotive industry and then moves on to highlight the main requirements for real-time collaborative systems, as expressed by various organizations along the automotive supply chain. Finally, the paper presents the results of a recent project in this area and some conclusions on the viability of CSCW technology in the current technical and commercial climate.     

Achieving cost-efficient fail-operational behavior based on inherent redundancy at the system level

To fulfill their safety requirements, modern embedded systems are increasingly often expected to deliver a guaranteed minimum level of functionality at all times. In practice, such fail-operational systems are often based on fault tolerance mechanisms that are inadequate for use in cost-driven environments such as the automotive domain. In this work, we consider safety-critical embedded systems with a certain degree of spare resources at the system level and propose a cost-efficient fault tolerance approach that protects a pair of execution units from severe hardware faults. The concept requires no replication of an execution unit. Instead, it employs a state-preserving proxy unit that communicates with low-level devices such as sensors or actuators and handles faults of one execution unit by dynamically migrating the safety-critical portion of its functionality to the redundant counterpart. Based on the application of this concept to an example scenario from the automotive domain, we analyze the resource overhead of the proxy unit and evaluate both the achieved fault handling time and the generated computational overhead experimentally.     

Real-time collaboration in design engineering: An expensive fantasy or affordable reality?

The purpose of this paper is to discuss the main issues that are both driving and impeding the implementation and use of CSCW systems within the automotive industry. The paper begins by describing the current competitive pressures within the European Automotive industry and then moves on to highlight the main requirements for real-time collaborative systems, as expressed by various organizations along the automotive supply chain. Finally, the paper presents the results of a recent project in this area and some conclusions on the viability of CSCW technology in the current technical and commercial climate.     

SMArDT modeling for automotive software testing

Efficient testing is a crucial prerequisite to engineer reliable automotive software successfully. However, manually deriving test cases from ambiguous textual requirements is costly and error-prone. Model-based software engineering captures requirements in structured, comprehensible, and formal models, which enables early consistency checking and verification. Moreover, these models serve as an indispensable basis for automated test case derivation. To facilitate automated test case derivation for automotive software engineering, we conducted a survey with testing experts of the BMW Group and conceived a method to extend the BMW Group's specification method for requirements, design, and test methodology by model-based test case derivation. Our method is realized for a variant of systems modeling language activity diagrams tailored toward testing automotive software and a model transformation to derive executable test cases. Hereby, we can address many of the surveyed practitioners' challenges and ultimately facilitate quality assurance for automotive software.     

Configuring use case models in product families

In many domains such as automotive and avionics, the size and complexity of software systems is quickly increasing. At the same time, many stakeholders tend to be involved in the development of such systems, which typically must also be configured for multiple customers with varying needs. Product Line Engineering (PLE) is therefore an inevitable practice for such systems. Furthermore, because in many areas requirements must be explicit and traceability to them is required by standards, use cases and domain models are common practice for requirements elicitation and analysis. In this paper, based on the above observations, we aim at supporting PLE in the context of use case-centric development. Therefore, we propose, apply, and assess a use case-driven configuration approach which interactively receives configuration decisions from the analysts to generate product-specific (PS) use case and domain models. Our approach provides the following: (1) a use case-centric product line modeling method (PUM), (2) automated, interactive configuration support based on PUM, and (3) an automatic generation of PS use case and domain models from Product Line (PL) models and configuration decisions. The approach is supported by a tool relying on Natural Language Processing (NLP) and integrated with an industrial requirements management tool, i.e., IBM DOORS. We successfully applied and evaluated our approach to an industrial case study in the automotive domain, thus showing evidence that the approach is practical and beneficial to capture variability at the appropriate level of granularity and to configure PS use case and domain models in industrial settings.     

Automotive behavioral requirements expressed in a specification pattern system: a case study at BOSCH

To allow an automatic formal analysis of requirements, the requirements have to be formalized first. However, logical formalisms are seldom accessible to stakeholders in the automotive context. Konrad and Cheng proposed a specification pattern system (SPS) represented in a restricted English grammar that can be automatically translated to logics, but looks like natural language. In this paper, we investigate whether this SPS can be applied to automotive requirements of BOSCH, in the sense that it is expressive enough to specify automotive behavioral requirements of BOSCH. We did a case study over 289 informal behavioral requirements taken from automotive BOSCH projects. We evaluated whether these requirements could be formulated in the SPS and whether the SPS has to be adapted to the automotive context. The case study strongly indicates that the SPS, extended with 3 further patterns, is suited to specify automotive behavioral requirements at BOSCH.     

Requirements engineering in automotive development: experiences and challenges

In the automotive industry, especially in the high-end market, the complexity of electronic components is increasing rapidly. Currently, about a third of all development costs in high-end models go to electric and electronic system development, and the cost continues to grow. At the same time, many slightly different variations on components are each developed in a series of prototyping phases on different schedules. Consequently, the complexity of specification activities surpasses what conventional text-processing systems can support in terms of management and tracing functionality. Using real world projects as a foundation, the authors describe problems and solutions for requirements engineering in the automotive domain.     

Case-based expert system using wavelet packet transform and kernel-based feature manipulation for engine ignition system diagnosis

Whenever there is any fault in an automotive engine ignition system or changes of an engine condition, an automotive mechanic can conventionally perform an analysis on the ignition pattern of the engine to examine symptoms, based on specific domain knowledge (domain features of an ignition pattern). In this paper, case-based reasoning (CBR) approach is presented to help solve human diagnosis problem using not only the domain features but also the extracted features of signals captured using a computer-linked automotive scope meter. CBR expert system has the advantage that it provides user with multiple possible diagnoses, instead of a single most probable diagnosis provided by traditional network-based classifiers such as multi-layer perceptions (MLP) and support vector machines (SVM). In addition, CBR overcomes the problem of incremental and decremental knowledge update as required by both MLP and SVM. Although CBR is effective, its application for high dimensional domains is inefficient because every instance in a case library must be compared during reasoning. To overcome this inefficiency, a combination of preprocessing methods, such as wavelet packet transforms (WPT), kernel principal component analysis (KPCA) and kernel K-means (KKM) is proposed. Considering the ignition signals captured by a scope meter are very similar, WPT is used for feature extraction so that the ignition signals can be compared with the extracted features. However, there exist many redundant points in the extracted features, which may degrade the diagnosis performance. Therefore, KPCA is employed to perform a dimension reduction. In addition, the number of cases in a case library can be controlled through clustering; KKM is adopted for this purpose. In this paper, several diagnosis methods are also used for comparison including MLP, SVM and CBR. Experimental results showed that CBR using WPT and KKM generated the highest accuracy and fitted better the requirements of the expert system.     

2DCMA: An Effective Maintenance Algorithm of Materialized Views in Peer Data Management Systems

Update management is very important for data integration systems. So update management in peer data management systems （PDMSs） is a hot research area. This paper researches on view maintenance in PDMSs. First, the definition of view is extended and the peer view, local view and global view are proposed according to the requirements of applications. There are two main factors to influence materialized views in PDMSs. One is that schema mappings between peers are changed, and the other is that peers update their data. Based on the requirements, this paper proposes an algorithm called 2DCMA, which includes two sub-algorithms： data and definition consistency maintenance algorithm% to effectively maintain views. For data consistency maintenance, Mork＇s rules are extended for governing the use of updategrams and boosters. The new rule system can be used to optimize the execution plan. And are extended for the data consistency maintenance algorithm is based on the new rule system. Furthermore, an ECA rule is adopted for definition consistency maintenance. Finally, extensive simulation experiments are conducted in SPDMS. The simulation results show that the 2DCMA algorithm has better performance than that of Mork＇s when maintaining data consistency. And the 2DCMA algorithm has better performance than that of centralized view maintenance algorithm when maintaining definition consistency.     

Constraint-based and SAT-based diagnosis of automotive configuration problems

We compare the concepts and computation of optimized diagnoses in the context of Boolean constraint based knowledge systems of automotive configuration, namely the preferred minimal diagnosis and the minimum weighted diagnosis. In order to restore the consistency of an over-constrained system w.r.t. a strict total order of the user requirements, the preferred minimal diagnosis tries to keep the most preferred user requirements and can be computed, for example, by the FASTDIAG algorithm. In contrast, partial weighted MinUNSAT solvers aim to find a set of unsatisfied clauses with the minimum sum of weights, such that the diagnosis is of minimum weight. It turns out that both concepts have similarities, i.e., both deliver an optimal minimal correction subset. We show use cases from automotive configuration where optimized diagnoses are desired. We point out theoretical commonalities and prove the reducibility of both concepts to each other, i.e., both problems are FP^NP-complete, which was an open question. In addition to exact algorithms we present greedy algorithms. We evaluate the performance of exact and greedy algorithms on problem instances based on real automotive configuration data from three different German car manufacturers, and we compare the time and quality tradeoff.     

Dealing with software process requirements complexity: an information access proposal based on semantic technologies

Organizations developing software for critical sectors like aerospace, automotive, and medical systems need to apply process requirements coming from different sources: industrial standards, customer-provided requirements, and procedures from internal quality management systems. In these situations, software teams need to deal with complex sets of process requirements that govern different aspects of their work. This paper describes the development of a collaborative, web-based solution to improve access to process requirements. The solution makes use of semantic technologies to handle the context of process requirement. Requirements are contextualized by linking them to activities, tasks, and work products. With this tool, software engineers have a single point of access to all the applicable process requirements, avoiding the risk of missing relevant information.     

Scalability planning for reconfigurable manufacturing systems

Scalability is a key characteristic of reconfigurable manufacturing systems, which allows system throughput capacity to be rapidly and cost-effectively adjusted to abrupt changes in market demand. This paper presents a scalability planning methodology for reconfigurable manufacturing systems that can incrementally scale the system capacity by reconfiguring an existing system. An optimization algorithm based on Genetic Algorithm is developed to determine the most economical way to reconfigure an existing system. Adding or removing machines to match the new throughput requirements and concurrently rebalancing the system for each configuration, accomplishes the system reconfiguration. The proposed approach is validated through a case study of a CNC-based automotive cylinder head machining system.     

Model-based diagnosis and fault tolerant control for ensuring torque functional safety of pedal-by-wire systems

This paper presents a model based approach for defining automotive functional safety requirements and provides a solution to ensure functional safety through model-based diagnosis and fault tolerant control. This model-based approach is consistent with ISO 26262 – functional safety standard. In particular, this paper presents the necessary steps for defining and implementing functional safety requirements, including item and function definition, Hazard Analysis and Risk Assessment, as well as the design of a model-based diagnostic and fault tolerant control (FTC) system that can lead to a systematic solution to automotive functional safety problems. The methodology proposed in this paper is applied to the problem of torque functional safety of pedal-by-wire systems.     

车用嵌入式开放系统的软构件研究*

研究适应于嵌入式领域的嵌入式构件是改进嵌入式软件开发方法的重要途径。首先阐述了嵌入式软构件的概念,对嵌入式软构件进行了深入总结分析,结合OSEK规范设计了车用OSEK嵌入式软构件,并提供了相应的开发支持工具。     

Design optimization for AUTOSAR models with preemption thresholds and mixed-criticality scheduling

Safety-critical embedded systems are often subject to multiple certification requirements from different certification authorities, giving rise to the concept of Mixed-Criticality Systems. Preemption Threshold Scheduling (PTS) is an effective technique for reducing stack memory usage by selectively disabling preemption between pairs of tasks. In this paper, we consider the AUTOSAR standard in automotive embedded software development, where each task consists of multiple runnables that are scheduled with static priority and preemption threshold. We address the problems of design synthesis from an AUTOSAR model to minimize stack usage for mixed-criticality systems with preemption threshold scheduling, and present algorithms for schedulability analysis and system stack usage minimization. Experimental results demonstrate that our approach can significantly reduce the system stack usage.