NDLI: Electric vehicle battery model identification and state of charge estimation in real world driving cycles

Content Provider	IEEE Xplore Digital Library
Author	Fotouhi, A. Propp, K. Auger, D.J.
Copyright Year	2015
Description	Author affiliation: Sch. of Aerosp., Cranfield Univ., Cranfield, UK (Fotouhi, A.; Propp, K.; Auger, D.J.)
Abstract	This paper describes a study demonstrating a new method of state-of-charge (SoC) estimation for batteries in real-world electric vehicle applications. This method combines realtime model identification with an adaptive neuro-fuzzy inference system (ANFIS). In the study, investigations were carried down on a small-scale battery pack. An equivalent circuit network model of the pack was developed and validated using pulse-discharge experiments. The pack was then subjected to demands representing realistic WLTP and UDDS driving cycles obtained from a model of a representative electric vehicle, scaled match the size of the battery pack. A fast system identification technique was then used to estimate battery parameter values. One of these, open circuit voltage, was selected as suitable for SoC estimation, and this was used as the input to an ANFIS system which estimated the SoC. The results were verified by comparison to a theoretical Coulomb-counting method, and the new method was judged to be effective. The case study used a small 7.2 V NiMH battery pack, but the method described is applicable to packs of any size or chemistry.
Starting Page	243
Ending Page	248
File Size	535852
Page Count	6
File Format	PDF
e-ISBN	9781467394819
DOI	10.1109/CEEC.2015.7332732
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-09-24
Publisher Place	UK
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	NiMH Battery Driving cycle Computational modeling Estimation Model identification Predictive models Electric vehicle Batteries Vehicles State of charge estimation Simulation ANFIS Mathematical model Integrated circuit modeling
Content Type	Text
Resource Type	Article

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