ChargeCar is a new project at the CREATE Lab at the Carnegie Mellon University Robotics Institute. This project is funded thanks to the generosity of Donna Auguste (CMU alumna), David Hayes, The Heinz Endowments and Bombardier Inc.
We are grateful for the conversations and collaborations we have had with numerous electric vehicle groups, including:
We have written two papers to provide you with more information about ChargeCar's analysis of the potential for change in the urban electric car ecology:
Learn more about the methods, motivations and mechanisms underlying the ChargeCar project.
Look under the hood of our physics model to see how we calculate your commute statistics.
Every Commute is Unique: |
Use Real Data:
We need solutions |
Engineer the Whole System: Many researchers and car companies are conducting outstanding research on specific components of electric cars, such as motors and batteries. We are doing complementary work by optimizing the entire power management system rather than concentrating on the individual component designs. This allows us to address the question: Can we use today's batteries, computers and supercapacitors to create far less costly intelligent electric vehicles? |
Include Everyone: ChargeCar is as much a social challenge as an engineering challenge. We want to involve you: collecting and sharing your commute data to contribute to accurate real-world commuting models to develop better intelligent control algorithms. |
Reuse: In addition to lowering the costs for commercially-developed electric vehicles, we are dedicated to practical conversion of existing cars, extending their usability. One of our goals is a conversion and customization process that empowers local mechanics and garages to be community-supported centers for an affordable urban electric vehicle revolution. |
Open the Hood: The combination supercapacitor-battery architecture has the potential for large gains in efficiency and large drops in overall cost of ownership. But to realize this potential we need whole new algorithms for using all the available data, from topography to driver behavior, to manage power intelligently. We pledge to openly share our algorithms and models so that everyone can collaborate continually on better solutions. |