Position Statement for BMS workshop at the 2011 PHM Society Conference Montreal, Quebec
Nick Williard, Wei He, Michael Osterman, Michael Pecht Objective: To demonstrate a novel method of estimating state of health within the framework of the coulomb counting technique
Center for Advanced Life Cycle Engineering University of Maryland College Park, MD 20742 http://www.calce.umd.edu
Center for Advanced Life Cycle Engineering 1 University of Maryland Copyright © 2011 CALCE

• The Center for Advanced Life Cycle Engineering (CALCE) formally started in 1984, as a NSF Center of Excellence in systems reliability. • One of the world’s most advanced and comprehensive testing and failure analysis laboratories • Funded at .$6M by over 150 of the world’s leading companies • Supported by over 120 faculty, visiting scientists and research assistants • Received NSF innovation award in 2009 Center for Advanced Life Cycle Engineering 2 University of Maryland Copyright © 2011 CALCE

Decline in Capacity vs. Cycle Number
1.2
0.8
• State of Health (SOH) refers to the general decline in battery performance with usage or aging. 0.4
0 0 200 400 600 800 1000 • SOH can be characterized by capacity fade, power fade, or increase in internal resistance.
Cycle Number
When using capacity as the metric for degradation, we could define SOH as : 100% • Monitoring SOH is critical for performing condition based maintenance and for mitigating failure. Where the SOH at cycle
c
is equal to the capacity Q at cycle
c
over the capacity at the beginning of life, expressed as a percentage • In an electric vehicle, a SOH indicator would be analogous to a “check engine” light, which informs the user that maintenance or battery replacement is required when some degradation threshold is crossed. Center for Advanced Life Cycle Engineering 3 University of Maryland Copyright © 2011 CALCE

Electrochemical Impedance Spectroscopy (EIS) Internal DC Resistance
R
 ( (
V I
2 2  
V I
1 ) 1 ) Internal DC resistance can be measured by applying 2 current pulses at I capacity 1 and I 2 and then measuring the voltage change at each pulse. This feature has been shown to have a linear relationship to Parameters from EIS are fit to an equivalent circuit model. Estimations can be improved though filtering methods such as particle filter and Kalman filter.
Coulomb Counting
Coulomb counting refers to the continuous monitoring of current that inters and leaves the battery. By integrating current with time, the capacity can be calculated. Whenever the battery is fully discharged to it’s cut off voltage the maximum capacity can be calculated and compared with the maximum capacity at the beginning of life then: 100% Center for Advanced Life Cycle Engineering 4 University of Maryland Copyright © 2011 CALCE

If a particular discharge is cut-off midway though it’s operation the, observed capacity will be lower due to the decreased about of time spent in operation. This decrease in capacity is not due too degradation mechanisms but rather the time spent in operation 4.2
4 3.8
Discharge was cut off at 3.4V
Capacity = 1.06Ah 3.6
3.4
3.2
 
-0.5
-0.52
-0.54
-0.56
-0.58
-0.6
4.15
4.1
4.05
4 3.95
3.9
3.85
0 0.5
1 1.5
2 0
Current Voltage Time (hours)
0.2
Discharge was cut off at 3.9V
Capacity = 0.24Ah 0.4
Time (hours)
-0.5
-0.52
-0.54
-0.56
-0.58
0.6
-0.6
Center for Advanced Life Cycle Engineering 5 University of Maryland Copyright © 2011 CALCE

• • •
The plot below shows the measured capacity of a battery that under went shallow charging for 900 cycles. The charge profile was then changed to cycle from a completely charged state to a completely discharged state. It can be seen that little degradation occurred during the shallow charging cycles. Cycled between 2.7 and 4.2V
1 0.8
0.6
0.4
0.2
0 0 Cycled between 2.7 and 3.7V
400
Cycles
800 1200 Center for Advanced Life Cycle Engineering 6 University of Maryland Copyright © 2011 CALCE

Assumptions
• Discharging under a constant condition will produce a smooth continuous trend in capacity fade • Different conditions lead to different rates in capacity fade • When all other conditions are constant, changes in capacity can be attributed solely to degradation Rate of degradation = when all discharge conditions are held constant
dc
Observed capacity measurements Equivalent Capacity Idealized trends in capacity fade Increasing cut-off Voltage Center for Advanced Life Cycle Engineering Cycles 7 University of Maryland Copyright © 2011 CALCE

discharge
• • • • When a capacity is recorded that does not reach the end cut-off voltage it can not be used to infer SOH. In this case it must be compared to a previous capacity value that was calculated at a similar cut-off voltage. When comparing capacities from similar cut-off voltages, the effective loss of capacity can be attributed to declining SOH rather than depth of discharge. When two discharges are recorded that have similar cut-off voltages the equivalent capacity can be calculated by: Where: c is the cycle number, Q similar similar cut-off voltages, and c similar are the capacity values that were recorded at are the cycle numbers associated with the similar capacity values .
Center for Advanced Life Cycle Engineering 8 University of Maryland Copyright © 2011 CALCE

• • • A battery underwent charge/discharge cycling at a constant discharge current Every cycle the battery was charged to it’s fully charged state Every 15 cycles the discharge cut-off voltage was randomly changed Cut-off Voltage • • The change in cut-off voltage resulted in variations in the observed capacity for each cycle This test simulates the situation where a user decides to re-charge their battery before it has reached a completely discharged state Center for Advanced Life Cycle Engineering 9 University of Maryland Copyright © 2011 CALCE

10 5 0 -5 -10 0 200 400 600 800
# of cycles between recalibration
• • • The red points show the observed capacity for each cycle The blue points show the equivalent capacity for each cycle (estimation of Q max ) The green points are cycles that were fully discharged indicating the true value of Q max • The percent error between the equivalent capacity and the next observed Q max 10% error of the maximum capacity is shown with respect to the number of cycles between recalibration. The model was able to run for over 600 cycles with less than a Center for Advanced Life Cycle Engineering 10 University of Maryland Copyright © 2011 CALCE

• By calculating an equivalent capacity, the maximum capacity can be estimated for partial discharges allowing for SOH to be updated for every cycle by: 100% • Frequent SOH estimations using equivalent capacity can improve maintenance strategies and mitigate failure.
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