Applying Specialized System Analysis for Brake by Wire in Software Defined Vehicles: The Development of a System Analysis Tool (SAT)

In the rapidly advancing field of automotive engineering, the emergence of Software-Defined Vehicles (SDVs) has introduced complex design and functionality challenges, particularly with respect to braking systems. A main concept of SDV electrical architecture is centralizing vehicle controls and decoupling this control software from sensing and actuation mechanisms. This paradigm shift, specifically when applied to Brake by Wire (BbW) systems, leads to the decentralization of brake actuation, and requires precise coordination among numerous electronic components for effective braking command execution. The absence of mechanical backup in BbW systems necessitates additional fail-safe redundancies, further complicating the system. A comprehensive model that elucidates these component interdependencies is essential for enhancing engineers' optimization of system design. This paper introduces a custom-built System Analysis Tool (SAT), complemented by a specialized methodology, tailored specifically for modeling and analyzing the BbW system. The methodology and logic behind operation of the SAT is explained and its application is shown via select illustrative examples. The SAT is instrumental in assessing independent component failures, their interdependencies, and the cumulative impact of various multiple failure scenarios, thereby significantly enhancing the safety and reliability of the BbW system. It primarily functions as an analytical tool, evaluating the effects of component malfunctions on system functionality and performance. This enables engineers to rapidly adapt and refine designs, optimizing both cost and complexity. Moreover, the SAT quantifies the relationship between individual component failure rates, expressed in Failures In Time (FIT), and their ensuing impact on system performance degradation. This approach supports a data-driven, customer-centric strategy which balances system reliability, complexity, and cost-effectiveness.