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Carnegie Mellon Robotics Institute

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Abstract

The successful introduction of electric vehicles continues to be stiﬂed by the high cost and limited perfor-mance life of battery technology. We assert that a disruptive improvement in systems-level cost-of-performance is possible by employing a rate-heterogeneous energy storage system, combining low-rate batteries and high-rate supercapacitors, that is mated to a predictive control system that optimizes power management by exploiting topographic information, trafﬁc history, and speciﬁc driver performance. Such predictive power management, optimizing energy storage throughout episodes of vehicle acceleration and regenerative braking, has the potential to signiﬁcantly decrease the total energy duty on the vehicle’s batteries.

Notes

Text Reference

Alexander Styler, Gregg Podnar, Paul S. Dille, Matthew Duescher, Christopher Bartley, and Illah Nourbakhsh, "Active Management of a Heterogeneous Energy Store for Electric Vehicles," June, 2011.

BibTeX Reference

@inproceedings{Styler_2011_7025,
   author = "Alexander Styler and Gregg Podnar and Paul S Dille and Matthew Duescher and Christopher Bartley and Illah Nourbakhsh",
   title = "Active Management of a Heterogeneous Energy Store for Electric Vehicles",
   booktitle = "",
   month = "June",
   year = "2011",
   number= "CMU-RI-TR-",
}

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