Fire Risk Assessment of Battery Ship Based on Bayesian Network

Recently, there has been a significant increase in interest in battery-powered vehicles to reduce emissions according to stringent regulations. Battery-powered ships pose a huge risk of fire. The consequences are dangerous. The main purpose of this paper is to determine the degree of risk of fire on a battery-powered ship and thereby improve the safety of battery-powered ships. Determining the causes of a fire on a battery ship is paramount. Even the smallest events can cause serious accidents. The study examined all the main causes of fire in a battery-powered vessel from the perspective of equipment failure, human factors, electrical faults and failure in a ship battery compartment, built the fire risk assessment model for battery ship based on Bayesian network. The prior probability and conditional probability tables of the model were generated using statistical data and expert judgment. A 500-ton pure electric cargo ship in Huzhou, China, was selected as an example for this assessment. The results show that the probability of a fire on a battery-powered ship is less than 5%. Moreover, measures have been proposed to reduce the occurrence of malfunctions leading to an explosion or fire.