NDLI: Reinforcement learning based power management for hybrid electric vehicles

Content Provider	IEEE Xplore Digital Library
Author	Xue Lin Yanzhi Wang Bogdan, P. Naehyuck Chang Pedram, M.
Copyright Year	2014
Description	Author affiliation: Korea Adv. Inst. of Sci. & Technol., Daejeon, South Korea (Naehyuck Chang) \|\| Univ. of Southern California, Los Angeles, CA, USA (Xue Lin; Yanzhi Wang; Bogdan, P.; Pedram, M.)
Abstract	Compared to conventional internal combustion engine (ICE) propelled vehicles, hybrid electric vehicles (HEVs) can achieve both higher fuel economy and lower pollution emissions. The HEV consists of a hybrid propulsion system containing one ICE and one or more electric motors (EMs). The use of both ICE and EM increases the complexity of HEV power management, and therefore requires advanced power management policies to achieve higher performance and lower fuel consumption. Towards this end, our work aims at minimizing the HEV fuel consumption over any driving cycle (without prior knowledge of the cycle) by using a reinforcement learning technique. This is in clear contrast to prior work, which requires deterministic or stochastic knowledge of the driving cycles. In addition, the proposed reinforcement learning technique enables us to (partially) avoid reliance on complex HEV modeling while coping with driver specific behaviors. To our knowledge, this is the first work that applies the reinforcement learning technique to the HEV power management problem. Simulation results over real-world and testing driving cycles demonstrate the proposed HEV power management policy can improve fuel economy by 42%.
Starting Page	33
Ending Page	38
File Size	1338775
Page Count	6
File Format	PDF
ISBN	9781479962785
DOI	10.1109/ICCAD.2014.7001326
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-11-02
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hybrid electric vehicles Ice Batteries Learning (artificial intelligence) Fuels Gears reinforcement learning Hybrid electric vehicle (HEV) power management
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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