1. Design of an Intelligent Battery Management System
(BMS)
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Guide Name :- Prof. A. D. Dharmadhikari
Presented By:-Rupesh R. Dhule
Roll No:- IR111(RBT19ME225)
JSPMâS
RAJARSHI SHAHU COLLEGE OF ENGINEERING
TATHAWADE,PUNE-33.
(An Autonomous Institute Affiliated to Savitribai Phule Pune University, Pune)
2. content
âą Why BMS
âą Applications
âą Overall Topology
âą Model Description
âą Solar PV Array model
âą DC-DC Buck Boost Converter model
âą Battery RC model
âą Controller Algorithm Block
âą Results
âą Future Work-plan
âą References
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3. Need of Battery Management System
âą Heart of all types of energy storage technology.
âą Ensures optimum usage of the energy inside the battery powering
the portable/stationary system.
âą Risk of damage inflicted upon the battery is minimized.
âą Enhances system run-time reliability.
âą Increase overall system efficiency.
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4. Applications
âą Grid connected & off-grid
âą Utility grid
âą Off grid power storage and power transfer as required.
âą Storage in electric automobiles
âą Applications in astronomy:
âą Power supply and transfer in space stations and satellites.
âą Power to run remotely controlled automobiles and rover on other planets
surfaces.
âą Intermittent & renewable energy applications as backup [solar, wind,
etc.]
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5. BMS for solar PV system
âą BMS for solar PV systems are designed to enhance the battery storage life
time and to ensure power system reliability.
âą BMS is being extensively used in Grid connected and off-grid solar PV
applications (Stand-alone solar Pump, Electric vehicle, rural electrification
etc.)
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13. Lithium Ion Battery
ïą Lightest metal.
ïą Provides very high energy density in terms of weight (twice that of the
standard Ni- Cd batteries).
ïą It has a cycle life of 1200 â 2000 which is reasonably good for automotive
applications.
ïą Self-discharge is less than half compared to nickel-cadmium (Ni-Cd),
making lithium-ion well suited for modern fuel gauge applications.
ïą Does not need prolonged priming when itâs new.
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14. Electrical equivalent model of Battery
âą Equivalent circuit model of a battery
Thevenin battery model
E0 â Open-circuit Battery Voltage
R â Solution Resistance
C0 â Electrode Capacitance
R0 â Electrode Resistance
MATLAB model designed
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17. 3 stage Charge control Algorithm
Initialize battery
OCV , SOC
If
VOCV > VTrickle
If
VOCV > VBulk
NO YES
(C.C. Mode)
NO
YES
ICh = IBulk
(C.C. Mode)
ICh = ITrickle
If
ICh > IFloat
NO
YES
ICh = 0
(C.V. Mode)
VCh = VOCV
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19. Future Work-Plan
âą The performance of the proposed charge controller shall be improved
by proper choice of L-C filter.
âą Maximum power point tracking (MPPT) will be introduced in the PCU
model to improve the overall system efficiency.
âą The effect of temperature rise inside the battery stack shall be taken
care of in the proposed model later on.
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20. References
âą D. Sutanto, H.L. Chan, â A New Battery Model for use with Battery
Energy Storage Systems and Electric Vehicles Power Systemsâ, Power
Engineering Society Winter Meeting, January 2000.
âą John Chiasson, Baskar Variamohan, âEstimating the State of
Charge of a Batteryâ, Transactions on Control Systems Technology,
Vol. 13, NO. 3, May 2005.
âą Jun Xu and Binggang Cao, âBattery Management System for Electric
Drive Vehicles â Modeling, State Estimation and Balancingâ.
âą Barrie Lawson, âState of Charge (SOC) Determinationâ, Woodbank
Communications .
âą Dirk Uwe Sauer, Heinz Wenzl, âComparison of different approaches
for lifetime prediction of electrochemical systems-Using lead-acid
batteries as exampleâ, Journal of Power Sources, Vol. 176, NO. 2.
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