RT Journal Article
A1 João Pedro Trovão
AD R&D Unit, INESC Coimbra, Rua Sílvio Lima, Pólo II, 3030-290, Coimbra, Portugal
AD e-TESC Laboratory, Department of Electrical & Computer Engineering, University of Sherbrooke, Sherbrooke, QC , Canada, J1 K 2R1
A1 Mário António Silva
AD R&D Unit, INESC Coimbra, Rua Sílvio Lima, Pólo II, 3030-290, Coimbra, Portugal
A1 Maxime R. Dubois
AD e-TESC Laboratory, Department of Electrical & Computer Engineering, University of Sherbrooke, Sherbrooke, QC , Canada, J1 K 2R1

PB iet
T1 Coupled energy management algorithm for MESS in urban EV
JN IET Electrical Systems in Transportation
VO 7
IS 2
SP 125
OP 134
AB Multi-source energy storage systems (MESSs) have been gaining prominence in electric vehicles (EVs) research area. Energy- and power-flow control of on-board MESS and its integration are essential to the performance of urban EVs. Development of an energy management system (EMS) is an important issue with significant influence on the EV range and capabilities. In this study, an innovative coupled energy management algorithm is presented, applied to a fully decoupled MESS containing batteries and supercapacitors (SCs). The proposed energy management algorithm uses an original online filtering technique coupled to a fuzzy logic controller (FLC). The main advantages of the coupled approach and filtering are identified and discussed. The online filtering technique is placed inside the control loop, allowing the decoupling of the frequency of the battery power reference signal given by the FLC. The control loop as well as the EMS were previously simulated in MATLAB/Simulink™ for an urban EV. Furthermore, the coupled EMS has been validated through power-level reduced-scale hardware-in-the-loop (HIL) simulations. The experimental results show the effectiveness of the proposed coupled energy management algorithm. As a result of this development, the proposed EMS is effective in controlling the power-flows with battery lifetime improvement and optimisation in EV performance.
K1 Matlab-Simulink environment
K1 innovative coupled energy management algorithm
K1 EMS
K1 battery lifetime improvement
K1 control loop
K1 coupled energy management algorithm
K1 electric vehicles
K1 on-board MESS
K1 fuzzy logic controller
K1 supercapacitors
K1 frequency decoupling
K1 power-level reduced-scale hardware-in-the-loop simulation
K1 fully-decoupled MESS
K1 urban EV
K1 battery power reference signal
K1 energy management system
K1 power-flow control
K1 power-level reduced-scale HIL simulation
K1 energy flow control
K1 coupled energy management strategy
K1 online filtering technique
K1 multisource energy storage systems
K1 FLC
DO https://doi.org/10.1049/iet-est.2016.0001
UL https://digital-library.theiet.org/;jsessionid=60getgp8rsj4s.x-iet-live-01content/journals/10.1049/iet-est.2016.0001
LA English
SN 2042-9738
YR 2017
OL EN