Assessing the risk of transporting battery electric vehicles through water transportation modes by integrating system theory and Bayesian network approach

The growing use of Battery Electric Vehicles (BEVs) has increased the need for their transportation via sea routes. This study conducts a comprehensive safety assessment of BEV transport on ferries using the System Theoretic Process Analysis (STPA) to identify Unsafe Control Actions (UCAs) and potential loss scenarios. A Bayesian Network (BN) model is developed to evaluate the causal relationships between contributing factors, while fuzzy set theory is applied to quantify failure and conditional probabilities based on expert input. Four key subsystems influence the safety of BEV transports, including marine crew, fire safety, port-related activities, and EV's batteries. The analysis highlights component failures, process model flaws, and inadequate system feedback as key contributors to UCAs. Sensitivity analysis reveals that lack of knowledge is the most influential factor leading to human, asset, and environmental losses. Furthermore, management factors, specifically, lack of procedures and rules, were found to be significant causal contributors to potential losses and accidents. These findings provide crucial insights to support the development of safety standards and regulations for the maritime transportation of BEVs.