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Model-based development of automotive embedded systems
KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Embedded Control Systems. KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.ORCID iD: 0000-0002-4300-885X
KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Embedded Control Systems. KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.ORCID iD: 0000-0001-7048-0108
KTH.
KTH.
2017 (English)In: Automotive Embedded Systems Handbook, CRC Press , 2017, p. 10-52Chapter in book (Other academic)
Abstract [en]

Vehicles are being transformed into autonomous machines that assist drivers when accidents are about to occur, inform about traffic conditions, diagnose and upgrade themselves as required, while providing comfort and entertainment functionalities. The evolution of embedded systems technology has provided an important enabler for such new functionalities and improved qualities. In this context it can be noted that an estimated 70% of the innovations over the last 20 years are related to information and communication technologies [3]. Cars are becoming computers on wheels. The impact of introducing embedded system technology into vehicles has had, and is having, a radical effect on vehicle development, production, and maintenance. Automotive embedded systems have over the past decades evolved from single stand-alone computer systems, simple enough to be designed and maintained with a minimum of engineering, to distributed computer systems including several networks, and large numbers of sensors, electrical motors, and points of interactions with humans. These distributed systems are tightly integrated into the vehicle. They provide flexible information transfer and computational capabilities, allowing coordination among actuators, sensors, and human-machine interfaces (HMIs), removal of mechanical parts, and also completely new mechanical designs. Automotive embedded systems is an interesting area where the mechanical and control systems worlds meet with the general IT world represented by entertainment/telematics functionalities and increasing connections to the vehicle external infrastructure and IT systems. The opportunities are thus enormous, but the new technology also requires new competencies, methodologies, processes, and tools that can handle the flip side of the coin; the resulting increase and change in product and development complexity. Competition, customer demands, legislation, and new technologies are driving the introduction of new functionalities in the automotive industry. Many new functions in vehicles span traditional domains and organizations. An example of this is active safety systems that assist the driver by receiving environmental information, interpreting the driver intentions, controlling the vehicle dynamics, and, in case an accident is about to occur, informing an emergency center. The increasing system complexity and related increase in costs for the embedded systems development and maintenance create strong needs for systematic and cost-effective development approaches. Current methods of automotive embedded system development lead to [2,50,70] • Long turnaround time, since the complete behavior can only be tested in the integration phase. • Lack of continuity between requirements deinition, system design, and distributed system implementation; typically involving different people and with little formalized communication. • Suboptimal solutions. The organizational structures still mirror the mechanical architecture, and because of a current lack of a systems-level engineering approach for embedded systems design. © 2009 by Taylor & Francis Group, LLC.

Place, publisher, year, edition, pages
CRC Press , 2017. p. 10-52
National Category
Mechanical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-236849DOI: 10.1201/9780849380273Scopus ID: 2-s2.0-85052675806ISBN: 9780849380273 (print)ISBN: 084938026X (print)ISBN: 9780849380266 (print)OAI: oai:DiVA.org:kth-236849DiVA, id: diva2:1273211
Note

QC 20181220

Available from: 2018-12-20 Created: 2018-12-20 Last updated: 2018-12-20Bibliographically approved

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Törngren, MartinChen, DeJiu

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