Identifying Degradation Indicators for Electric Vehicle Battery Based on Field Testing Data
- Resource Type
- Conference
- Authors
- Wong, Kei Long; Chou, Ka Seng; Aguiari, Davide; Tse, Rita; Tang, Su-Kit; Pau, Giovanni
- Source
- 2022 IEEE Electrical Power and Energy Conference (EPEC) Electrical Power and Energy Conference (EPEC), 2022 IEEE. :206-211 Dec, 2022
- Subject
- Components, Circuits, Devices and Systems
Computing and Processing
Power, Energy and Industry Applications
Signal Processing and Analysis
Correlation coefficient
Degradation
Correlation
Estimation
Electric vehicles
Discharges (electric)
Batteries
electric vehicle
lithium-ion battery
battery degradation
state of health
correlation analysis
field testing data
- Language
State of health estimation of battery is crucial to ensure the safety and durability of electric vehicles. This paper presents six methods to extract the battery health indicator from electric vehicle field testing data. The methods for extracting health indicators from the discharge cycle show the ability to cope with the variable driving condition. In total, 157 health indicators are extracted from the collected data. Pearson correlation coefficient and Spearman's rank correlation coefficient are used to measure the correlation between the health indicators and the state of health. The results suggest that health indicators extracted by the presented methods have high correlations to the battery state of health.