Modeling Collaboration Is a Win-Win Situation for Vehicle Research
One of the primary advantages of large multidisciplinary research organizations such as the U.S. Department of Energy's (DOE's) national laboratories is the opportunity for synergistic collaborations between research groups that meet the goals of the project and simultaneously benefit science on many fronts. A recent example of such a collaboration involved researchers in Argonne National Laboratory's Center for Transportation Research (CTR) and their colleagues in the Chemical Engineering (CMT) and Nuclear Engineering (NE) divisions.
Argonne's Fuel Cell Program staff was tasked by its DOE sponsor, the Hydrogen, Fuel Cells and Infrastructure Technology Program, to establish the energy storage requirements for three vehicle platforms (compact car, midsize car, and sport utility vehicle) that employed projected 'midterm' (2005–2007) fuel cell technologies. The Fuel Cell Program researchers, part of the CMT division, worked with researchers in CTR to develop baseline models for these conventional platforms using Argonne's Powertrain System Analysis Toolkit© (PSAT) software, a versatile powertrain modeling software that realistically simulates vehicle fuel economy, emissions, and performance. Development of PSAT was funded by DOE's d Vehicle Technologies Office.
According to CTR's Aymeric Rousseau, "The plan was to use suitably sized fuel-cell-based powertrains for each platform, as indicated by PSAT, to compare fuel storage requirements, assuming that the fuel cells would be powered by compressed hydrogen. That meant, for example, modeling a 90-kW fuel cell that would offer the same performance (acceleration, maximum speed, etc.) as a compact car's 86-kW internal combustion engine."
Researchers in Argonne's NE division developed models for the pressurized, direct hydrogen, polymer electrolyte fuel cell systems needed for the different vehicle platforms. The fuel cell systems were designed by using NE's General Computational Toolkit (GCtool). The team quickly found that the comprehensive models in GCtool ran slowly in PSAT's vehicle environment. The models did not work optimally with PSAT because the two programs were written in different languages and there was no means of translating from one language to another. "What we had to do was to develop an alternative set of dynamic models for fuel cell system components and write a translator for the GCtool 'driver' to produce a dynamic link library for the fuel cell system that would interface with PSAT's language," says NE's Rajesh Ahluwalia.
The resulting modified GCtool software, called GCtool-ENG, worked like a charm — allowing the researchers to study the potential for gains in fuel economy with hydrogen fuel cell vehicles and determine the energy storage requirements for the three vehicle platforms. The study showed that the fuel economy of midterm hydrogen fuel cell vehicles can be 2.5–2.7 times the fuel economy of the current conventional gasoline internal combustion engine vehicles on the same platform. The study also showed that the vehicles need 4.3–6.5 kg of onboard recoverable hydrogen to achieve a 320-mile driving range between refuelings. The researchers used these data to estimate the fuel tank weight and volume requirements if hydrogen was stored at 5,000–10,000 psi.
|Conventional||Fuel Cell||Conventional||Fuel Cell||Conventional||Fuel Cell|
|Fuel economy (mpg)||28||74||23||62||20||50|
|Tank pressure (psi)||5,000||10,000||5,000||10,000||5,000||10,000|
|Hydrogen stored (kg)||--||4.3||--||5.1||--||6.4|
|Tank volume (l)||205||150||240||165||295||200|
|Tank weight (kg)||60||75||75||80||80||95|
Argonne's multidisciplinary study revealed that the fuel economy of mid-term hydrogen fuel cell technology can be 2.5–2.7 times the fuel economy of present-day conventional vehicles on the same platform. Hybridization can further improve the fuel economy.
In a separate study involving the modeling tools, the researchers also investigated combining a Saft lithium-ion HP6 battery and the simulated fuel cell system in various hybridization schemes. It turns out, for example, that higher hybridization (more battery power) leads to increased regenerative braking energy but decreased fuel cell system cycle efficiency. The researchers also found that the increase in efficiency afforded by more regenerative braking does not always overcome the decrease in efficiency caused by downsizing the fuel cell and operating it outside its peak efficiency region. In other words, unless the design of the hybridization scheme is optimized, an overall decrease in fuel economy can result. According to Rousseau, "Argonne's work using GCtool-ENG and PSAT demonstrated that the best fuel economy is a compromise between hybridization degree, energy storage technology, driving cycle, and control strategies."
CTR researchers are by no means the only beneficiaries of the collaboration that led to the development of GCtool-ENG. Both CMT and NE researchers now have a new tool that they intend to fully exploit in the years to come. "We created one dynamic link library for one particular type of fuel cell system, so now we are going to look at different systems," says Ahluwalia. In the near term, the researchers intend to use GCtool-ENG in investigating ambient pressure fuel cell systems and various hydrogen storage methods.