DocumentCode :
3476580
Title :
Towards advanced BMS algorithms development for (P)HEV and EV by use of a physics-based model of Li-ion battery systems
Author :
Prada, E. ; Di Domenico, Domenico ; Creff, Y. ; Sauvant-Moynot, V.
Author_Institution :
Rond-point de l´echangeur de Solaize, IFP Energies Nouvelles, Solaize, France
fYear :
2013
fDate :
17-20 Nov. 2013
Firstpage :
1
Lastpage :
12
Abstract :
Onboard Hybrid Electric Vehicles (HEV) and Battery Electric Vehicles (BEV), the Battery Management System (BMS) is of critical importance to ensure safe and reliable use of the electrical energy stored inside Li-ion batteries until the End-Of-Life (EOL) of the electrochemical system. At any time, the BMS must indicate the allowable current limits for charge and discharge (CMI: Charge Maximal Intensity and DMI: Discharge Maximal Intensity) that the battery systems can safely absorb/supply at different temperatures (T) and states-of-charge (SOC) for a given pulse duration (tpulse) according to the electric power absorbed by the vehicle operational usage. CMI and DMI laws are generally specified by the battery manufacturer based on experimental tests campaigns. In this paper, BMS specifications laws are investigated for Li(NixCoyAlz)O2/Graphite (NCA/C) Li-ion technology through a physics-based battery model which allows the analysis of different physical phenomena that impact the system performance according to operating conditions. The CMI and DMI are then compared to the battery manufacturer data. Finally, the DMI and CMI are implemented in a Battery Intensity Management Algorithm (BIMA) which is validated at the simulation level. This practical method can be generalized to other Li-ion chemistries, enabling efficient model-based design of conventional BMS laws with regard to cell limits in terms of (over)potentials, current, temperature, and aging mechanisms.
Keywords :
battery management systems; battery powered vehicles; hybrid electric vehicles; secondary cells; BMS algorithms; battery electric vehicles; battery intensity management algorithm; battery management system; battery systems; discharge maximal intensity; end of life; onboard hybrid electric vehicles; states of charge; Batteries; Computational modeling; Discharges (electric); Electrodes; Integrated circuit modeling; Mathematical model; System-on-chip; Battery management systems laws; Li-ion electrochemical and thermal modeling; Maximum charge and discharge current intensities;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electric Vehicle Symposium and Exhibition (EVS27), 2013 World
Conference_Location :
Barcelona
Type :
conf
DOI :
10.1109/EVS.2013.6914790
Filename :
6914790
Link To Document :
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