Project 8:
Battery Technologies for Mass Deployment of Electric Vehicles

Objective

Assess current and emerging battery technologies and the requirements for their commercialization; align with DOE targets for future EV batteries. Focus will be placed on battery technologies, charging cycles, lifetimes, safety, codes and standards, and economics.

Brief Description

Battery technologies are advancing at a rapid pace, with several potential markets for adoption. One market that is expected to experience a significant increase is the electric vehicle market. As these batteries are adopted into electric vehicles, it will be required to understand how the battery is cycled during vehicle utilization. This project investigates the impact of electric vehicle applications on battery performance, with an emphasis on both current and future applications (e.g. vehicle-to-grid). Additionally, this project investigates the usage profile of electric vehicles, and the required infrastructure to support current and future electric vehicle ranges.

Research Results

The initial project results evaluated the performance of commercially available Li-ion batteries by conducting a search of the existing literature and evaluation of the data from over 100 peer-reviewed papers. This material was compiled into a database of battery performance degradation as a function of electrode chemistry, temperature and state of charge (SOC) and is accessible using a MATLAB code compiled by the University of Hawaii.

Work done on setting up of the database regarding degradation rates for lithium-ion batteries as a function of electrode chemistry, temperature and state of charge (SOC) has been completed. Currently, the degradation rates are being analyzed for calendar aging studies, following which cycling aging studies will be examined. The output will be peer-reviewed papers to be published in research journals.

Another project accomplishment was an analysis of national driving trends and battery size to determine where and when electric vehicles will likely recharge. The analysis was also able to determine how many miles the average consumer has driven as a function of both time and place, and to correlate these parameters to the expected SOC of an electric vehicle battery. The results were published in the Journal of Power Sources.

The analysis was also able to determine how many miles the average consumer has driven as a function of both time and place, and to correlate that to the expected SOC of an electric vehicle. By incorporating driver recharging preferences (as provided by Idaho National Laboratory), the likelihood of vehicle recharging as a function of both time and place was determined. Based on this model, it was estimated that only 12% of 80-mile range electric vehicles are likely to recharge at work, while 53% will recharge at home (or one charge every 2-days). This value is likely under-estimating the frequency of at-home charging, since many EV owners are likely to plug their vehicles in at home whether or not there is a strong need to recharge. Due to the ability of this approach to model charging station usage as a function of location and time, this analysis could assist in grid-forecasting for EVs.

The third project on creation of a battery laboratory for work on characterization of Lithium-Ion polymer batteries by electrochemical impedance spectroscopy at Tuskegee University. In this effort a battery laboratory will be set up which is complete with impedance analyzer, potentiostat, power supply and infra-red camera. This setup will enable students and faculty to investigate battery performance changes as well as the temperature effects of battery charging/discharging cycles. Specifically, electrode performance can be characterized by charge transport, ohmic resistance and mass transport, all of which are accessible by using the impedance spectroscopy setup. The infra-red camera will be used to determine how heat is evolved during battery usage, so as to design better coolant systems. It is also noted that Electrical impedance spectroscopy (EIS) is an indispensable tool to study the performance of batteries. EIS works on simple principle, in which a sinusoidal voltage or current is applied to the battery and its impedance is measured for a wide range of frequencies. The results are plotted and analyzed. Based on the measured value of cell impedance in the form of real and imaginary components on can measure (a) Electronic/ionic conduction in the electrode and electrolytes, (b) Interfacial charging either at the surface films or the double-layer, (c) charge transfer processes and the mass transfer effects.

At the end of an electric vehicle’s useful life, the battery still has approximately 80% of its capacity remaining, and this could be used in a “second life” application. One such application is to support a building’s electrical load through peak shaving, where significant savings can be accrued through a reduction in demand charges. This project has developed a Matlab model that simulates a stationary battery’s state of charge when used to reduce peak demand, and estimates the potential return on investment for a given reduction in demand charges. This model is currently designed to use a stationary battery, but will be expanded to include batteries in vehicles (i.e. vehicle-to-building).

Impacts/Benefits

Understanding how batteries degrade as a function of temperature, voltage and cycles could assist in identifying chemistries for particular applications. For example, one chemistry may be able to tolerate high temperatures better, suggesting better operation in hot climates. Similarly, one chemistry may be able to tolerate cold-cycling better than others, indicating better operation in cold climates.

By modeling where and when EVs are likely to recharge, it may be possible to forecast where grid operators should make changes to the grid in order to accommodate EVs. The grid as a whole is able to tolerate the energy and power required by EVs for several more years before needing to expand capacity. However, there will likely be localized effects at the substation level where high penetration of EVs could stress transformers. The model of EV recharging as a function of time and place could be used to predict the load on local substations as a function of EV adoption rates. By tracking EV purchases, the grid operators may be able to pro-actively increase the service to a particular area with high EV penetration.

Creation of a battery laboratory for work on characterization of Lithium-Ion polymer batteries by electrochemical impedance spectroscopy at Tuskegee University is being set up in order to enable students and faculty to investigate battery performance changes as well as the temperature effects of battery charging/discharging cycles.

By modeling a building's use of batteries for demand charge reduction, the demand cycle on the battery can be simulated, which will be able to define potential degradation rates. This is particularly important in life-cycle assessment studies.

Reports

Brooker, P., Qin, N., "Identification of potential locations of electric vehicle supply equipment" Journal of Power Sources, Volume 299, Pages 76-84, 2015.

Click, D. "PV and Batteries: From a Past of Remote Power to a Future of Saving the Grid," The Electrochemical Society Interface, Vol 24, No 1, Spring 2015, pp49-51.

Brooker, P., Qin, N., Debarry, M. (2018). Battery Technologies for Mass Deployment of Electric Vehicles (FSEC Rep No. FSEC-CR-2079-18). Florida Solar Energy Center: Cocoa, FL.