Quantifying Knock-On Effects and Total Impact of Design Choices via Combined Sensitivity Analysis and Structural Equation Modeling Techniques

Vehicles are complex systems composed of interdependent subsystems, where a change in one component can propagate through others, causing knock-on effects and impacting the overall performance. This interconnected nature makes early stage design challenging due to limited knowledge of the consequences of design choices. Existing tools address different aspects of this gap in isolation and typically do not quantify cascading changes, that is, knock-on effects, or the total impact of an input on the output, thereby highlighting the need for an integrated approach. This study addresses these limitations by proposing a framework to quantify the magnitude and direction of knock-on effects and consequently calculate the total impact by integrating curve fitting, sensitivity analysis, and structural equation modeling. This framework derives representative functions, quantifies the influence of each interacting factor pair, and calculates the total impact. To demonstrate this framework, a rail traction system was used as a case study. The results indicate that while rated power had comparatively less impact on the output than frequency, it had six times as many paths and 1.86 times as many vertices as frequency, indicating higher knock-on effects. To validate the structural model, the total impact value was compared with the direct sensitivity coefficient for each input and output, yielding a maximum error of 3%. In addition, a comparison with the results of Global Sensitivity Analysis confirmed consistent input rankings and influence directions. This demonstrates the framework’s capability to quantify knock-on effects and total impact while preserving true input-output relationships.