Proceedings of the 2nd International Conference on Advances in Computer Science and Engineering (CSE 2013)

Energy Aware Battery Powered Electric Vehicles:A Predictive Model Driven Approach

Authors
Dennis Babu, Anirudh Kumar, Joydeb Roychowdhury
Corresponding Author
Dennis Babu
Available Online July 2013.
DOI
https://doi.org/10.2991/cse.2013.49How to use a DOI?
Keywords
battery management system; FPGA; gradient descent algorithm; Extended Kalman Filter; EffBMS
Abstract
Active energy management for power optimization is essential for successful commercialization of battery powered electric vehicles. In this paper we propose and implement an energy aware electric vehicle using an efficient battery management system, EffBMS which estimates the remaining charge of the Li-ion battery online, learns the rate of change of SOC and accordingly modulates the velocity and acceleration of the vehicle for optimal energy usage. An Extended Kalman Filter (EKF) was used to estimate the remaining charge of the Li-ion battery pack. An online dual time frame gradient descent algorithm with higher time frame for updating dataset and lower time frame for parameter tuning learns the SOC curve and employs a set point controller for energy management in motion. The entire model was developed in a SPARTAN 6 LX-45 reconfigurable FPGA board and is tested in a laboratory model of differentially driven single geared electric car. Case study of an upward slope hill motion is performed and results shows 10-12% energy savings.
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Proceedings
2nd International Conference on Advances in Computer Science and Engineering (CSE 2013)
Part of series
Advances in Intelligent Systems Research
Publication Date
July 2013
ISBN
978-90786-77-70-3
ISSN
1951-6851
DOI
https://doi.org/10.2991/cse.2013.49How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Dennis Babu
AU  - Anirudh Kumar
AU  - Joydeb Roychowdhury
PY  - 2013/07
DA  - 2013/07
TI  - Energy Aware Battery Powered Electric Vehicles:A Predictive Model Driven Approach
BT  - 2nd International Conference on Advances in Computer Science and Engineering (CSE 2013)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/cse.2013.49
DO  - https://doi.org/10.2991/cse.2013.49
ID  - Babu2013/07
ER  -