Embedded Systems in Automotive Applications
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77 139 Ft
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Product details:
- Publisher Elsevier Science
- Date of Publication 1 March 2026
- ISBN 9780443338618
- Binding Paperback
- No. of pages425 pages
- Size 229x152 mm
- Weight 450 g
- Language English 700
Categories
Long description:
With its well-thought-out overview of the topic, Embedded Systems in Automotive Applications serves diverse audience across both in academia and industry. The volume discusses the AUTOSAR architecture and standards, highlighting their role in enabling the integration of emerging technologies such as blockchain-based security within the Internet of Vehicles. It further addresses embedded software design, implementation, and validation techniques that are fundamental to developing reliable and safety-critical automotive systems. In addition, it examines electric vehicle technologies, with particular focus on advanced battery management strategies and real-time power and health monitoring. Autonomous driving is explored through LiDAR-SLAM techniques and FPGA-based hardware architectures designed to support robust vehicle navigation. The book also emphasizes vehicle connectivity and telematics applications, encompassing innovations in smart mobility and intelligent transport. Together, these themes provide readers with a rigorous and well-rounded understanding of the challenges, methodologies, and opportunities shaping next-generation automotive embedded systems.
MoreTable of Contents:
Part I. Introduction
1. Overview of Embedded Systems in Automotive Applications
Part II. AUTOSAR Architecture and Standards
2. AUTOSAR in Automotive Embedded Systems: Classic vs. Adaptive Platforms and Their Role in IoV Development with Integrated Blockchain Security
3. Multi-threading Integration in Automotive Computing: AUTOSAR-Compliant Survey
4. A Concise Survey on ADAS: Advances in Vehicle and Pedestrian Detection with a focus on the AUTOSAR Automotive Standard
Part III. Embedded Software Implementation and Validation
5. Efficient Parallel Implementation Strategies on Multicore Digital Signal Processors
6. Google Test/ Google Mock to Verify Critical Embedded Software
7. MIL and PIL Tests for SOC Estimation Algorithms of Electric Vehicles Lithium-ion Batteries and its Implementation on ARM Embedded Processor
Part IV. Battery Management Systems and Monitoring
8. Battery Management Systems: Integration and Optimization in Automotive Applications
9. Battery Real-time Power Monitoring and Control in Automotive Embedded Systems
Part V. Autonomous Driving Technologies
10. A Comprehensive Review of LiDAR-SLAM for Hardware Implementation for Autonomous Vehicles
11. Efficient FPGA-Based Hardware Architecture for High-Performance EKF-SLAM in Autonomous Vehicle Navigation
12. Advancing Autonomous Vehicle Technology with 3D LiDAR and SqueezeSeg-ROS Integration
Part VI. Connectivity and Telematics
13. 3G Universal Plugin for Car Remote Starters and Alarm Systems and Car Key Fobs
