Ensuring the safety and functionality of sophisticated vehicle technologies has grown more difficult as the automotive industry quickly shifts to intelligent, electric, and connected mobility. Software-defined architectures, electric powertrains, and advanced driver assistance systems (ADAS) all require strong quality assurance (QA) frameworks that can handle the multi domain nature of contemporary vehicle platforms. In order to thoroughly assess the functionality and dependability of next generation automotive systems, this paper proposes an integrated QA methodology that blends conventional testing procedures with model-based validation, digital twin environments, and real-time system monitoring.
The suggested framework, which includes hardware-in-the-loop (HIL), software-in-the-loop (SIL), and over-the-air (OTA) testing techniques, concentrates on end-to-end traceability from specifications to validation.
Simulating intricate situations for ADAS, electric vehicle battery temperature management, and dynamic system updates in connected platforms are prioritized. This study also outlines the main obstacles to integrating QA methods with changing regulatory environments and draws attention to discrepancies between operational performance in real-world scenarios and compliance benchmarks. Early fault detection, lifecycle validation, and continuous improvement are made possible by the QA process's transition from reactive to proactive through the integration of digital twins and predictive analytics. A strategic roadmap for QA specialists and test engineers to adjust to changing industry demands is presented in the paper's conclusion. In addition to promoting safety and dependability, the suggested framework speeds up time to market, lowers development costs, and increases consumer confidence in cutting-edge automotive technologies.