Breakthrough Flow Battery Cell Stack: Transformative Electrochemical Flow Storage System (TEFSS)

DOE OSTI · 1046610

Breakthrough Flow Battery Cell Stack: Transformative Electrochemical Flow Storage System (TEFSS)

View original source ↗Read source document ↗Export metadata ↓

Abstract

GRIDS Project: UTRC is developing a flow battery with a unique design that provides significantly more power than today's flow battery systems. A flow battery is a cross between a traditional battery and a fuel cell. Flow batteries store their energy in external tanks instead of inside the cell itself. Flow batteries have traditionally been expensive because the battery cell stack, where the chemical reaction takes place, is costly. In this project, UTRC is developing a new stack design that achieves 10 times higher power than today’s flow batteries. This high power output means the size of the cell stack can be smaller, reducing the amount of expensive materials that are needed. UTRC’s flow battery will reduce the cost of storing electricity for the electric grid, making widespread use feasible.

Explore related subjects

ARPA-E Grid-Scale Rampable Intermittent Dispatchable Storage GRIDS Stationary Energy Storage

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

2010-09-09. Breakthrough Flow Battery Cell Stack: Transformative Electrochemical Flow Storage System (TEFSS). https://www.osti.gov/biblio/1046610

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related reports

DOE OSTI2020

Leveraging Real-World Driving Data for Design and Impact Evaluation of Energy Efficient Control Strategies

Modeling and simulation are crucial in the development of advanced energy efficient control strategies. Utilizing real-world driving data as the underlying basis for control design and simulation lends veracity to projected real-world energy savings. Standardized drive cycles are limited in their utility for evaluating advanced driving strategies that utilize connectivity and on-vehicle sensing, primarily because they are typically intended for evaluating emissions and fuel economy under controlled conditions. Real-world driving data, because of its scale, is a useful representation of various road types, driving styles, and driving environments. The scale of real-world data also presents challenges in effectively using it in simulations. A fast and efficient simulation methodology is necessary to handle the large number of simulations performed for design analysis and impact evaluation of control strategies. In this study, two methods are presented of leveraging real-world data in both design optimization of energy efficient control strategies and in evaluating the real-world impact of those control strategies upon large-scale deployment. Through these methodologies, strategies with highest impact on energy savings were selected to be implemented as control algorithms. The developed algorithms were incorporated into a vehicle dynamics and powertrain control architecture implemented on a Cadillac CT6 demonstration vehicle. The control algorithms were then exercised on real-world driving scenarios to determine their impact on collective energy savings. The methodology utilizes the large-scale driving data sets maintained by the National Renewable Energy Laboratory to extract real-world driving scenarios and efficient simulation software tools. The insights obtained through this research help in guiding technology selection for energy efficient driving controls.

ARPA-E↗

DOE OSTI2020

Corroborative Evaluation of the Real-World Energy Saving Potentials of InfoRich Eco-Autonomous Driving (iREAD) System

There has been an increasing interest in exploring the potential to reduce energy consumption of future connected and automated vehicles. People have extensively studied various eco-driving implementations that leverage preview information provided by on-board sensors and connectivity, as well as the control authority enabled by automation. Quantitative real-world evaluation of eco-driving benefits is a challenging task. The standard regulatory driving cycles used for measuring exhaust emissions and fuel economy are not truly representative of real-world driving, nor for capturing how connectivity and automation might influence driving trajectories. To adequately consider real-world driving behavior and potential “off-cycle” impacts, this paper presents four collaborative evaluation methods: large-scale simulation, in-depth simulation, vehicle-in-the-loop testing, and vehicle road testing. These four approaches, spanning simulation and testing aspects, evaluate real-world fuel economy benefits with different ranges and resolutions. The large-scale simulations leverage an extensive real-world driving database to assess overall eco-driving benefits across a range of road network and driving scenarios. The real-world driving data are further leveraged to generate representative driving routes for deeper evaluation. Based on the representative routes, in-depth simulation relying on high-fidelity models investigates how different traffic scenarios can impact the eco-driving performance. The vehicle-in-the-loop setup reinforces the in-depth simulations by conducting tests with an actual vehicle operated on a chassis dynamometer; the measured energy savings were indeed found to agree with the in-depth simulation savings estimates. Finally, limited but representative road testing with the fully integrated vehicle will be conducted to demonstrate the eco-driving capability and conclude the overall evaluation regimen.

ARPA-E↗

DOE OSTI2012

Distributed Power Flow Control: Distributed Power Flow Control using Smart Wires for Energy Routing

GENI Project: Smart Wire Grid is developing a solution for controlling power flow within the electric grid to better manage unused and overall transmission capacity. The 300,000 miles of high-voltage transmission line in the U.S. today are congested and inefficient, with only around 50% of all transmission capacity utilized at any given time. Increased consumer demand should be met in part with more efficient and an economical power flow. Smart Wire Grid’s devices clamp onto existing transmission lines and control the flow of power within—much like how internet routers help allocate bandwidth throughout the web. Smart wires could support greater use of renewable energy by providing more consistent control over how that energy is routed within the grid on a real-time basis. This would lessen the concerns surrounding the grid’s inability to effectively store intermittent energy from renewables for later use.

ARPA-E↗