Capacity fade and aging models for electric batteries and optimal charging strategy for electric vehicles

• Published in: Energy (Oxford) 2013-10, Vol.60, p.35-43
• Main Authors: Fernández, I.J., Calvillo, C.F., Sánchez-Miralles, A., Boal, J.
• Format: Article
• Language: English
• Subjects: algorithms; Applied sciences; batteries; Battery degradation models; Capacity fade; Direct energy conversion and energy accumulation; Electric vehicles; Electrical engineering. Electrical power engineering; Electrical power engineering; Electrochemical conversion: primary and secondary batteries, fuel cells; energy efficiency; Energy management; Exact sciences and technology; linear models; Self-organizing maps; system optimization; temperature; vehicles (equipment); yields
• ISSN: 0360-5442
• DOI: 10.1016/j.energy.2013.07.068

Due to the increasing concern for energy efficient storage devices, extensive research is being done on the mechanisms which are involved in the battery degradation process. Optimality in electric vehicle energy management has been traditionally pursued from the perspective of efficient grid operation, but barely considering battery degradation in the process. The objective is to formulate a battery degradation model which will yield the degradation suffered by a battery as a function of its use, allowing both the comparison between different energy management strategies as well as including the model in linear optimization algorithms. Nearly three-hundred tests were carried out on Li-ion battery cells which were subjected to different depth-of discharges, currents and temperatures. Results are used to identify the variables which categorize best, using self-organizing maps, the degradation suffered by the cells. A model is proposed which yields the rate of degradation of the battery as a function of both temperature and depth-of-discharge. This model is then linearized and used in an electric vehicle energy management optimization problem, where the degradation suffered by the battery due to a controlled charge is minimized. Finally, the results are compared with other charging methods. •Battery degradation model as a function of depth-of-discharge and temperature.•Battery degradation model as sum of piece-wise linear functions.•Optimization algorithm which minimizes battery degradation.•Comparison with: uncontrolled charge and minimizing depth-of-discharge.•Substantial reduction of degradation with proposed model.