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Risk Analysis Project
Electric Vehicle
Objectives
● To find the risk value of initiating events
● Understanding how Risk is analyzed for particular event
● Identify the hazards and Study the level of risks
Familiarization and Information Building
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General Layout of battery in Electric vehicle
Identifying Critical Barriers
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Past Major Failures
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Battery material
Battery Enclosure structure
Battery management systems
Battery are known to overheat and explode
Extreme weather isn’t conducive to EV’s
Documentation
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For quality performance risk assessment.
Initiating Events
1. Over pressurization of battery due to Tire Pressure
Measuring Sensor.
2. Battery failure( catching fire) due to overheating.
3. Over pressurization due to battery cell pack.
4. Airbag deployment malfunctioning due to “Piezo-electric
sensor” failure
Initiating Event 1
Over pressurization of battery due to Tire Pressure Measuring
Sensor
Probability of failure of basic event
● R(t)= e-t/71686
At 61500 km running condition, reliability of
component shock absorber is 91.45%
● Probability of failure is 8.55%
Risk value of Top event
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Risk value of Top event = 0.0307 = 3.07%
Probability of failure of basic event:
1.
Voltage sensor failure = 0.0023
2.
Firmware bus = 0.0051
3.
Broken connector = 0.009
4.
Battery Thermal Instability = 0.018
5.
Tire Pressure sensor failure = 0.056
6.
Shock absorber = 0.0855
7.
Device operation faulty = 0.0032
Uncertainty Risk Analysis
Identifying the sources of risk and quantifying the risk
probabilities
Reliability at Lower bound (62612.70) = 0.8890
Reliability of Upper bound(71067.97) = 0.9156
Initiating Event 2
Battery failure( catching fire) due to overheating
Fault Tree
Performance Risk Assessment
Performance Risk Assessment
Since the data is cyclic in nature Durability Endurance model is used
We have, R(t)= e-λt
Where, λ is 1/MTTF,
MTTF: mean time to failure
MTTF(s) = 433.45
AF= 10
MTTF(n) = 4334.5
Therefore,
t/4334.5
R(t)= e-
Performance Risk Assessment
•For 400th cycle of charging and discharging of the
battery, reliability is 91.18%
•Probability of failure is 8.82%
Risk value for top event
Probability of failure
Thermal management system fails: 0.089
e
Motor fail : 0.091
Battery pack fails: 0.29 (from calculations)
Battery failure: 0.088
Faulty charger: 0.009
Battery exposed to high temperature : 0.008
Collison: 0.004
Internal Damage and impurities: 0.006
Internal pressure build up: 0.087
External factor cause damage: 0.004
Probability for top event = 0.089 * 0.29
= 0.0258
= 2.58%
Uncertainty Risk Analysis
Confidence level for mean at 90 percent confidence is
389.58 and 477.31
Uncertainty Risk Analysis
Lower bound is 389.58
Upper bound is 477.31
Relibility at lower bound is= 0.914041
Reliability at Upper bound is =0.895726
Range for reliability is
0.895-0.914
Initiating Event 3
Battery Explosion due to overpressurization in the cell pack
Fault Tree
Initiating Event: Overpressure in cell pack
Performance Risk Assessment
Failure Cycle for Tested Samples
To find reliability R(t)= e-λt
Where, λ =
mean time to failure
MTTF(s) = 109 hrs
Initial test temp is 25 ॰C and gradually increased to
80॰C AF= 120
So Mean time to failure for initial test temp.
MTTF * AF = 109 * 128 = 13,952 hrs
Probability of failure of the event
● Running the testing for 150 hrs reliability is 0.9893
● Probability of failure is = 1- R(t) = 0.0107
Risk Value of Top Event
Risk value of Top Event : 0.0819 = 8.19%
Probability of failure for basic event:
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MOSFET : 0.006
OptoCoupler : 0.008
Relay = 0.0015
Faulty charger: 0.025
high temperature : 0.0063
Collision Damage: 0.004
Master Chip Failure: 0.015
Battery Puncture due to accident: 0.0055
Low Material Quality: 0.004
Poor sealing : 0.0001
Uncertainty Analysis
Quantifying Risk Value
Confidence level at 95% with lower bound of 34.5347
and upper bound of 153.049
Reliability for lower bound – 0.99
Reliability for upper bound – 0.9865
Initiating Event 4
Airbag deployment malfunctioning due to “Piezo-electric sensor” failure
Fault Tree
Performance risk Assessment
Performance Risk Assessment
As the data presented is cyclic in nature Durability Endurance model is used
Performance Risk Assessment
R(t)= 0.91943 = 91.94%
Probability of failure = 1 – R(t) = 1 – 0.9194
Probability of failure = 8.06%
Risk evaluation for top event
Now, we can calculate the probability of failure of top event from if we have probability for all the basic events. The probability of all the
basic events are mentioned below,
Risk evaluation for top event
Solving for the top event, by adding the probabilities connected by OR gate and
multiplying the one connected by AND gates, we get the following probability for
the top event
Probability of Airbag failure = 0.021 = 2.1%
Uncertainty risk analysis
589.25 + 228.88 and 589.25 – 228.88
Lower bound = 360.37
Upper bound = 818.13
Reliability at lower bound is= 0.940823
Reliability at Upper bound is =0.871099
The reliability range is between [0.8710, 0.9408]
Event Tree – For battery Initiating event
Event Tree for Airbag System
Rank of Initiating Event
1. Airbag deployment malfunctioning due to “Piezo-electric
sensor” failure(2.1%)
2. Battery failure( catching fire) due to overheating of the battery
(2.4%)
3. Over pressurization of battery due to Tire Pressure Measuring
Sensor (3.07%)
4. Battery Explosion due over pressurization in battery cell pack
(8.19%)
Consequence
If the battery catches fire because of the failure of the battery it have dreadful
consequences, EV fire are extremely difficult to put out as it doesn’t need
oxygen to continue as it has oxidising agents. The fire could spread and
damage any infrastructure present in the vicinity. It requires 1000s of litre of
water to put out and many hours.
CONCLUSION- Battery Initiating Event
The resilience of Li-ion batteries in an explosion scenario has to be further studied.
Investigations should pay particular attention to the kinds and levels of fire that
might be predicted to put a lot of strain on the built-in safety measures of electric
vehicles and their batteries.
Based on the results of this first investigation, it should be taken into account to
have available specialised firefighting gear as well as thermal imaging equipment
to check for hotspots and BMS malfunctions remotely around important vehicle
components.
Conclusion
For Airbag Deployment system
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Keeping in mind the Airbag feature is well developed but still there are many cases which suggests
that Airbags malfunction rather then not opening. The fatality cases for airbag malfunctioning are
more than the cases of airbag does not open during the crash.
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It suggests that there is still some area of improvement in the field to detect the crash properly so as
to prevent the airbags from malfunctioning. This study was focused on the deployment part of the
airbags that is dependent upon the working of “Piezo-electric” sensors and other several similar
sensors, for that part the airbags are working with very high reliability and can be trusted upon
regardless of the nature of collision.
References
https://www.portescap.com/en/newsroom/2021/12/reliability-estimation-of-coreless-brush-dc-motors
https://elsmar.com/elsmarqualityforum/threads/weibull-analysis-of-life-time-test-of-8-electric-motors-until-failure.63715/
https://www.sciencedirect.com/science/article/pii/S2589004222004424#!
https://www.cnbc.com/2022/01/29/electric-vehicle-fires-are-rare-but-hard-to-fight-heres-why.html
https://www.sciencedirect.com/science/article/pii/S0378775316317864
https://www.researchgate.net/publication/320580566_A_late_and_failure_of_airbag_deployment_case_study_for_drivers_of_passenger_cars_in_rear-end_collisions
https://www.researchgate.net/publication/41231680_Safety_Analysis_of_an_Airbag_System_using_Probabilistic_FMEA_and_Probabilistic_Counter_Examples
http://ijarcs.info/index.php/Ijarcs/article/viewFile/2150/2138
https://www.proquest.com/openview/ccb542667704bcfde3360f11c07b152d/1?pq-origsite=gscholar&cbl=1606379
https://pricetheory.uchicago.edu/levitt/Papers/LevittPorter2001.pdf
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