A Lifecycle-Centric Hardware-in-the-Loop Validation Framework for Continuous Verification of Software-Defined Automotive Chassis and Powertrain Systems
Keywords:
Hardware-in-the-Loop, Software-Defined Vehicles, Lifecycle Validation, Digital Twin, Continuous Verification, Functional Safety, Automotive Embedded SystemsAbstract
The transition to software-defined vehicle (SDV) architectures has fundamentally altered the validation challenge for automotive chassis and powertrain embedded control systems. In traditional development cycles, validation is a pre-deployment activity: software is verified against a fixed functional specification before release, and the system is assumed stable thereafter. Software-defined vehicles dissolve this assumption entirely. Over-the-air (OTA) software updates, continuous calibration adjustments, and feature extensions delivered post-deployment create a time-varying system model in which the behavioral correctness of chassis and powertrain controllers must be re-established after every change. Existing Hardware-in-the-Loop (HIL) validation practices, designed around pre-deployment milestone verification, are structurally inadequate for this continuous, lifecycle-spanning verification demand. This paper proposes a lifecycle-centric HIL validation framework that extends HIL-based verification across development, deployment, and post-deployment phases through three integrated mechanisms: automated validation pipelines that execute HIL regression suites within 24 hours of each software update, digital twin feedback loops that continuously enrich the HIL scenario library from field-collected operational data, and embedded functional safety validation that evaluates diagnostic coverage and fault detection latency against ISO 26262 requirements after each update cycle. The framework is evaluated across 180 software update regression cycles spanning six months of simulated post-deployment operation on a dSPACE SCALEXIO platform. Key results include: a first-pass HIL success rate of 73.1%, a mean validation turnaround time of 19.4 hours, a diagnostic coverage of 91.3%, a fault detection latency of 44 ms, and a regression escape rate of 0.8%. These results demonstrate that lifecycle-centric HIL validation provides the continuous assurance capability that software-defined automotive architectures require.
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References
F. Pan et al., "Toward software-defined vehicles: From model-based engineering to virtualization-based deployment," IEEE Access, vol. 12, pp. 192127–192145, 2024. [Online]. Available: https://ieeexplore.ieee.org/document/10778534/
M. Abboush, C. Knieke, and A. Rausch, "Advancing real-time validation of automotive software systems via continuous integration and intelligent failure analysis," Scientific Reports, vol. 15, 2025. [Online]. Available: https://www.nature.com/articles/s41598-025-21416-5
F. Mihalič, M. Truntič, and A. Hren, "Hardware-in-the-loop simulations: A historical overview of engineering challenges," Electronics, vol. 11, no. 15, p. 2462, 2022. [Online]. Available: https://www.mdpi.com/2079-9292/11/15/2462
M. R. Kabir, B. B. Y. Ravi, and S. Ray, "Digital twin technologies for vehicular prototyping: A survey," IEEE Open Journal of Intelligent Transportation Systems, 2025. [Online]. Available: https://ieeexplore.ieee.org/document/10969983/
V. Skrickij et al., "Review of integrated chassis control techniques for automated ground vehicles," Sensors, vol. 24, no. 2, p. 600, 2024. [Online]. Available: https://www.mdpi.com/1424-8220/24/2/600
M. Abboush, C. Knieke, and A. Rausch, "A virtual testing framework for real-time validation of automotive software systems based on hardware in the loop and fault injection," Sensors, vol. 24, no. 12, p. 3733, 2024. [Online]. Available: https://www.mdpi.com/1424-8220/24/12/3733
J. Sini, M. Violante, and F. Tronci, "A novel ISO 26262-compliant test bench to assess the diagnostic coverage of software hardening techniques against digital components' random hardware failures," Electronics, vol. 11, no. 6, p. 901, 2022. [Online]. Available: https://www.mdpi.com/2079-9292/11/6/901
M. Abboush, D. Bamal, C. Knieke, and A. Rausch, "Hardware-in-the-loop-based real-time fault injection framework for dynamic behavior analysis of automotive software systems," Sensors, vol. 22, no. 4, p. 1360, 2022. [Online]. Available: https://www.mdpi.com/1424-8220/22/4/1360
M. Abboush, C. Knieke, and A. Rausch, "Automating fault test cases generation and execution for automotive safety validation via NLP and HIL simulation," Sensors, vol. 24, no. 10, p. 3145, 2024. [Online]. Available: https://www.mdpi.com/1424-8220/24/10/3145
B. Deng et al., "A survey on integration of network communication into vehicle real-time motion control," IEEE Communications Surveys & Tutorials, vol. 25, no. 4, pp. 2755–2790, 2023. [Online]. Available: https://ieeexplore.ieee.org/document/10184107/
M. Abboush, C. Knieke, and A. Rausch, "Intelligent fault detection and classification based on hybrid deep learning methods for hardware-in-the-loop test of automotive software systems," Sensors, vol. 22, no. 11, p. 4066, 2022. [Online]. Available: https://www.mdpi.com/1424-8220/22/11/4066
M. Abboush, C. Knieke, and A. Rausch, "Representative real-time dataset generation based on automated fault injection and HIL simulation for ML-assisted validation of automotive software systems," Electronics, vol. 13, no. 2, p. 437, 2024. [Online]. Available: https://www.mdpi.com/2079-9292/13/2/437
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