Fault detection and increased reliability of a 3.3 kW on-board battery charger for PHEVs

Reliability is an important performance index of a modern power electronics converter. The failure modes and effect analysis (FMEA) is one the mostly used techniques to evaluate or possibly improve the reliability of a power electronic system. This is one of the key challenges in electronics converters for vehicle industry. The project aim is to increase the reliability of a 3.3 kW on-board vehicle battery charger. However, the techniques can be utilized in other electronic converters like traction inverters and DC/DC converters. For a 3.3 kW vehicle battery charger an FMEA is provided to evaluate and quantify the reliability for important fault scenarios. In addition, the cause of failures and recommended actions are provided also. After the fault detection, appropriate changes in software are provided to be able to continue the charger operation but probably with a reduced functionality. For example reduced charging power to a predetermined level is necessary in many fault cases. In addition to the fault detection and changes in operation, some design changes in electronic hardware are suggested to increase the reliability. For example providing a bypass current flow path by adding an extra diode to the charger circuit is suggested. Computer simulations have been performed to verify the theoretical analysis, fault detection algorithms and provided solutions for increased reliability. Hardware development to verify the analytical and simulation results is in process. The project is performed within Electric Power Engineering Division in Chalmers University of Technology in January 2015 till June 2015 with a budget of 700 ksek by Saeid Haghbin as the main researcher and Torbjörn Thiringer as the scientific advisor. The project was in collaboration with ePower (Kongsberg Automotive) as one of the leading on-board charger producers. The idea was to use the project results to enhance the products performance. Around 70% of the project funding is allocated to the staffing and 30% is dedicated to the equipment purchasing including the software and hardware.