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Secanell M.,University of Alberta | Wishart J.,ECOtality North America | Dobson P.,University of Alberta
Journal of Power Sources | Year: 2011

The design of fuel cells is a challenging endeavour due to the multitude of physical phenomena that need to be simultaneously optimized in order to achieve proper fuel cell operation. Fuel cell design is a multi-objective, multi-variable problem. In order to design fuel cells by computational design, a mathematical formulation of the design problem needs to be developed. The problem can then be solved using numerical optimization algorithms and a computational fuel cell model. In the past decade, the fuel cell community has gained momentum in the area of numerical design. In this article, research aimed at using numerical optimization to design fuel cells and fuel cell systems is reviewed. The review discusses the strengths, limitations, advantages, and disadvantages of optimization formulations and numerical optimization algorithms, and insight obtained from previous studies. © 2010 Elsevier B.V. All rights reserved.


Carlson R.B.,Idaho National Laboratory | Lohse-Busch H.,Argonne National Laboratory | Diez J.,ECOtality North America | Gibbs J.,U.S. Department of Energy
SAE International Journal of Alternative Powertrains | Year: 2013

The U.S. Department of Energy's Office of Energy Efficiency & Renewable Energy initiated a study that conducted coastdown testing and chassis dynamometer testing of three vehicles, each at multiple test weights, in an effort to determine the impact of a vehicle's mass on road load force and energy consumption. The testing and analysis also investigated the sensitivity of the vehicle's powertrain architecture (i.e., conventional internal combustion powertrain, hybrid electric, or all-electric) on the magnitude of the impact of vehicle mass. The three vehicles used in testing are a 2012 Ford Fusion V6, a 2012 Ford Fusion Hybrid, and a 2011 Nissan Leaf. Testing included coastdown testing on a test track to determine the drag forces and road load at each test weight for each vehicle. Many quality measures were used to ensure only mass variations impact the road load measurements. Chassis dynamometer testing was conducted over standard drive cycles on each vehicle at multiple test weights to determine the fuel consumption or electrical energy consumption impact caused by change in vehicle mass. The road load measurements obtained from the coastdown testing were used to configure the chassis dynamometer. Chassis dynamometer testing also incorporated many quality controls to ensure accurate results. The results of the testing and analysis showed that for a given vehicle, the road load shows a slightly non-linear trend of decreasing road load with decreasing mass. This trend appears to be consistent across vehicle powertrain architectures (i.e., conventional powertrain, hybrid electric, or all-electric). Chassis dynamometer testing of fuel consumption or electrical energy consumption showed for the Highway Fuel Economy Test drive cycle there was little impact due to change in mass for all three vehicles. For the Urban Dynamometer Drive Schedule and US06 drive cycle, there was a 2.4 to 4.1% change in energy consumption for a 10% change in mass. Additionally, the less efficient the vehicle's powertrain, the larger the energy consumption benefits were for mass reduction. Copyright © 2013 SAE International.


Schey S.,ECOtality North America | Scoffield D.,Idaho National Laboratory | Smart J.,Idaho National Laboratory
World Electric Vehicle Journal | Year: 2012

ECOtality was awarded a grant from the U.S. Department of Energy to lead a large-scale electric vehicle charging infrastructure demonstration, called The EV Project. ECOtality has partnered with Nissan North America, General Motors, the Idaho National Laboratory, and others to deploy and collect data from over 5,000 Nissan LEAFs™ and Chevrolet Volts and over 10,000 charging systems in 18 regions across the United States. This paper summarizes usage of residential charging units in The EV Project, based on data collected through the end of 2011. This information is provided to help analysts assess the impact on the electric grid of early adopter charging of grid-connected electric drive vehicles. A method of data aggregation was developed to summarize charging unit usage by the means of two metrics: charging availability and charging demand. Charging availability is plotted to show the percentage of charging units connected to a vehicle over time. Charging demand is plotted to show charging demand on the electric gird over time. Charging availability for residential charging units is similar in each EV Project region. It is low during the day, steadily increases in evening, and remains high at night. Charging demand, however, varies by region. Two EV Project regions were examined to identify regional differences. In Nashville, where EV Project participants do not have time-of-use electricity rates, demand increases each evening as charging availability increases, starting at about 16:00. Demand peaks in the 20:00 hour on weekdays. In San Francisco, where the majority of EV Project participants have the option of choosing a time-of-use rate plan from their electric utility, demand spikes at 00:00. This coincides with the beginning of the off-peak electricity rate period. Demand peaks at 01:00. © 2012 WEVA.


Smart J.,Idaho National Laboratory | Schey S.,ECOtality North America
SAE International Journal of Alternative Powertrains | Year: 2012

In 2010, a large-scale plug-in electric vehicle (PEV) infrastructure demonstration was launched to deploy an unprecedented number of PEVs and charging infrastructure. This demonstration, called The EV Project, is funded by the U.S. Department of Energy and led by ECOtality North America. ECOtality has partnered with Nissan North America and General Motors to deploy up to 8,300 Nissan LEAF™ battery electric vehicles and Chevrolet Volt extended-range electric vehicles, along with approximately 14,000 AC Level 2 and DC fast-charging units in 18 metropolitan areas across the United States. ECOtality and the Idaho National Laboratory partnered to collect and analyze electronic data from EV Project vehicles and charging units. An early analysis of data from Nissan LEAFs enrolled in The EV Project was performed. The data set analyzed came from 2,903 privately owned vehicles, which logged over 10 million driving miles in 2011. On average, Nissan LEAF drivers drove 6.9 miles per trip and 30.3 miles per day. Median values were 4.0 and 26.8 miles, respectively. In environments without many public charging locations, LEAF drivers averaged 28.8 miles between consecutive charging events, with a median of 27.1miles. The average and median number of times vehicles were charged per day driven were 1.05 and 0.99 charging events per day, respectively. Analysis of charging location determined that 82% of charging events were conducted at the project participants' homes using their residential electric vehicle supply equipment. 18% of charging events were performed elsewhere. Despite the relatively low numbers of publicly available charging units, over 70% of vehicles were charged away from home. Most of those vehicles charged at many distinct locations, such as shopping centers, health clubs, restaurants, and business offices. Some of the most frequently and infrequently charged vehicles were charged exclusively at home or in public, but most supplemented home charging with away-from-home charging. Copyright © 2012 SAE International.


Lidicker J.,University of California at Berkeley | Sathaye N.,ECOtality North America | Madanat S.,University of California at Berkeley | Horvath A.,University of California at Berkeley
Journal of Infrastructure Systems | Year: 2013

In recent decades, pavement management optimization has been designed with the objective of minimizing user and agency costs. However, recent analyses indicate that pavement management decisions also have significant impacts on life-cycle greenhouse gas (GHG) emissions. This study expands beyond minimization of life-cycle costs to also include GHG emissions. Previous work on the single-facility, continuous-state, continuous-time optimal pavement resurfacing problem is extended to solve the multicriteria optimization problem with the two objectives of minimizing costs and GHG emissions. Results indicate that there is a trade-off between costs and emissions when developing a pavement resurfacing policy, providing a range of GHG emissions reduction cost-effectiveness options. Case studies for an arterial and a major highway are presented to highlight the contrast between policy decisions for various pavement and vehicle technologies. © 2013 American Society of Civil Engineers.


Smart J.,Idaho National Laboratory | Powell W.,Idaho National Laboratory | Schey S.,ECOtality North America
SAE Technical Papers | Year: 2013

ECOtality North America, OnStar, and the Idaho National Laboratory have partnered to collect and analyze electronic data from Chevrolet Volts enrolled in The EV Project, which is a large-scale plug-in electric vehicle infrastructure demonstration being conducted in 21 metropolitan areas across the United States. This paper presents results of an early analysis of these data. The data set analyzed came from 923 privately owned vehicles, which logged over 4.7 million driving miles from October 2011 to October 2012. These data are used to identify the potential of electric vehicle (EV) mode driving, based on driver and charging behavior. Driving and charging behavior is quantified with metrics such as daily vehicle miles traveled, number of charging events performed per day, and distance driven between consecutive charging events. Drivers averaged 40.7 miles per day, with a median of 31.6 miles per day. Vehicles were charged 1.46 times per vehicle day driven on average, with a median of 1 charging event per day driven. This results in an average of 27.9 miles between consecutive charging events and a median distance of 19.8 miles between charging events. Underlying distributions for these metrics also are examined to find a wide variation in driving and charging behavior across vehicles and vehicle days. Overall, 81% of the vehicles averaged 40 miles or less between consecutive charging events. Assuming a fixed EV mode range of 35 miles, vehicles in this study had the potential to drive 73% of their miles in EV mode. These results show that Chevrolet Volt drivers participating in The EV Project found frequent opportunities to charge their vehicles, such that a high percentage of their driving was performed in EV mode. Also, drivers took advantage of their vehicle's extended range mode to meet their driving needs beyond the all-electric range of their vehicle.


Wishart J.,ECOtality North America | Carlson R.B.,Idaho National Laboratory | Chambon P.,Oak Ridge National Laboratory | Gray T.,ECOtality North America
SAE Technical Papers | Year: 2013

As energy storage system (ESS) technology advances, vehicle testing in both laboratory and on-road settings is needed to characterize the performance of state-of-the-art technology and also identify areas for future improvement. The Idaho National Laboratory (INL), through its support of the U.S. Department of Energy's (DOE) Advanced Vehicle Testing Activity (AVTA), is collaborating with ECOtality North America and Oak Ridge National Laboratory (ORNL) to conduct on-road testing of advanced ESSs for the Electric Drive Advanced Battery (EDAB) project. The project objective is to test a variety of advanced ESSs that are close to commercialization in a controlled environment that simulates usage within the intended application with the variability of on-road driving to quantify the ESS capabilities, limitations, and performance fade over cycling of the ESS. To accommodate on-road testing of a wide range of ESS size, mass, and intended applications, the EDAB testbed was constructed on a mid-sized pickup truck chassis. This truck was converted into a Series Plug-In Hybrid Electric Vehicle (PHEV) which enables vehicle operation consistent with any electrified vehicle. Sophisticated software algorithms were prepared and integrated into the testbed to emulate the physical characteristics and ESS demands of the intended application during on-road operation. This emulation is vital for proper ESS operation since the testbed is larger and heavier than the vehicle for which the ESS is typically designed. On-road testing is conducted over a range of ambient temperatures and driving route types ranging from stop-and-go city driving to constant-speed highway driving. Battery laboratory cycling with standard test procedures has been conducted throughout all phases of testing to corroborate the on-road data and accurately measure the ESS degradation. The first ESS to be tested is the Type I EV Pack manufactured by EnerDel, Inc. The ESS has a Li-ion chemistry, with a mixed-oxide cathode and amorphous hard carbon anode and a rated capacity of 70 Ah (at a C/3 rate). Due to the sealed enclosure, there is no internal thermal management system (TMS). The intended application for this ESS is for a small EV. This paper will report on current results of energy consumption, city vs. highway proportions, battery throughput, and laboratory testing results. The results illustrate the performance of the unit under test and the degradation throughout. The end-of-test criteria are 100,000 miles, three years of operation, or a 23% decrease in battery capacity, whichever occurs first. Copyright © 2013 SAE International.


Wishart J.,ECOtality North America | Shirk M.,Idaho National Laboratory | Gray T.,ECOtality North America | Fengler N.,ECOtality North America
SAE Technical Papers | Year: 2012

Vehicles equipped with idle-stop (IS) systems are capable of engine shut-down when the vehicle is stopped, and rapid engine re-start for the vehicle launch. This capability reduces fuel consumption and emissions during periods where the engine is not being utilized to provide propulsion or to power accessories. IS sytems are a low-cost and fast-growing technology in the industry-wide pursuit of increased vehicle efficiency, possibly becoming standard features in European vehicles in the near future. In contrast, there are currently only three non-hybrid vehicle models for sale in North America with IS systems, and these are distinctly low-volume models. As part of the United States Department of Energy's Advanced Vehicle Testing Activity (AVTA), ECOtality North America has tested the real-world effect of IS systems on fuel consumption in three vehicle models imported from Europe. These vehicles were chosen to represent three types of systems: (1) spark ignition (SI) with 12 V Belt Alternator Starter (BAS); (2) compression ignition (CI) with 12 V BAS; and (3) direct-injection SI (DISI) with 12 V BAS/combustion restart The vehicles have undergone both dynamometer and on-road testing, and the test results show somewhat conflicting data. The laboratory data and the portion of the on-road data in which the driving is conducted on a prescribed route with trained drivers produced significant fuel economy improvement. However, the fleet data do not corroborate the improvement even though the data show significant engine-off time. It is possible that the effects of the verying driving styles and routes in the fleet testing overshadowed the fuel economy improvements. More testing with the same driver over routes that are similar for the IS system enabled and disabled modes is recommended. There is anecdotal evidence that current Environmental Protection Agency (EPA) fuel economy test procedures do not capture the fuel economy gains that IS systems produce in real-world driving. The program test results provide information on the veracity of these claims and can help guide automotive manufacturers debating whether to include this system in future models. Copyright © 2012 SAE International.

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