Thermal System Diagnostics Development For Electric Trucks

Abstract

Abstract This thesis explores the development of a system-level diagnostic approach for the thermal management system of an electric truck, using the Global Simulation Platform (GSP). The study begins by collecting information about commonly occurring faults in electric trucks, with a focus on those related to the thermal system. From this list, selected faults are injected into GSP to evaluate the thermal behaviour of the electric vehicle system under fault conditions. These identified faults are used to assess the impact of fault scenarios on the thermal system, with fault injection employed to evaluate the severity. From this analysis, one specific fault is selected for detailed investigation. A logic based diagnostic system is developed to detect this fault, using insights derived from the simulation based fault behaviour. The diagnostic system is implemented and tested both on a test bench and in an electric vehicle to verify its function and logic. This thesis demonstrates how simulation driven analysis can be used to inform the design of practical diagnostic systems and presents a structured method for building logic based tools for fault detection in an electric vehicle thermal systems.