Fault detection of new and aged lithium-ion battery cells in electric vehicles

Abstract

In this paper, a novel model-based fault detection in the battery management system of an electric vehicle is proposed. Two adaptive observers are designed to detect state-of-charge faults and voltage sensor faults, considering the impact of battery aging. Battery aging primarily affects capacity and resistance, becoming more pronounced in the later stages of a battery lifespan. By incorporating aging effects into our fault diagnosis scheme, our proposed approach prevents false or missed alarms for the aged battery cells. The aging effect of battery, capacity fading and resistance growth, are considered unknown parameters. An adaptive observer is employed to design a fault detector, considering unknown parameters in the battery model. The adaptive observers are designed for two different scenarios: In the first scenario, it is presumed that aging effects remain constant over time due to their slow rate of change. Then, it is assumed that aging effects are time-varying. Therefore, the fault detection scheme can detect faults of new battery cells as well as aged cells. Some simulations have been conducted on a Lithium-ion battery cell and extended to battery pack, to demonstrate the performance of the proposed approach in more real-world scenarios. The results showed that the designed observers can detect faults correctly in a seven years old battery as well as a new one.

Keywords

• Adaptive observer
• Aging
• Electric vehicle
• Fault detection
• Lithium-ion battery
• State of charge