The transition toward Software-Defined Vehicles is reshaping the automotive industry, with vehicle functionalities increasingly determined by software rather than hardware. This paradigm, enabled by Hardware Abstraction Layers, improves software portability and upgradability; however, it also introduces challenges in timing analysis for safety-critical functions that demand an estimation of their reaction times. Existing timing analysis techniques, including those designed for frameworks like ROS 2, often neglect uncertainties in execution times, fail to attribute delays to specific software components, and provide limited insights into the causes of timing variability — hindering system optimisation. This paper presents a novel timing analysis framework for SDVs that overcomes these limitations by leveraging a minimal yet sufficient set of timing information exposed by the HAL. The framework accounts for uncertainty in both hardware and software, models logical timing requirements of components, and estimates reaction time and its variability while explaining their root causes. We demonstrate the applicability and benefits of our approach through a running example, showing how it enables more transparent and informed system design.