Lithium-ion battery aging dataset based on electric vehicle real-driving profiles

Gabriele Pozzato; Anirudh Allam; Simona Onori

doi:10.1016/j.dib.2022.107995

Lithium-ion battery aging dataset based on electric vehicle real-driving profiles

Data Brief. 2022 Feb 25:41:107995. doi: 10.1016/j.dib.2022.107995. eCollection 2022 Apr.

Authors

Gabriele Pozzato¹, Anirudh Allam¹, Simona Onori¹

Affiliation

¹ Energy Resources Engineering, Stanford University, Stanford, CA 94305, USA.

Abstract

This paper describes the experimental dataset of lithium-ion battery cells subjected to a typical electric vehicle discharge profile and periodically characterized through diagnostic tests. Data were collected at the Stanford Energy Control Laboratory, at Stanford University. The INR21700-M50T battery cells with graphite/silicon anode and Nickel-Manganese-Cobalt cathode were tested over a period of 23 months according to the Urban Dynamometer Driving Schedule (UDDS) discharge driving profile and the Constant Current (CC)-Constant Voltage (CV) charging protocol designed at different charging rates - ranging from C/4 to 3C. Ten (10) cells are tested in a temperature-controlled environment (23 $^{\circ}$ C). A periodic assessment of battery degradation during life testing is accomplished via Reference Performance Tests (RPTs) comprising of capacity, Hybrid Pulse Power Characterization (HPPC), and Electrochemical Impedance Spectroscopy (EIS) tests. The dataset allows for the characterization of battery aging under real-driving scenarios, enabling the development of models and management strategies in electric vehicle applications.

Keywords: Aging campaign; Battery aging; EV driving-based data; Lithium-ion battery; NMC 2170; Reference performance tests.