Project 2
a.The max heat generation of the battery:
Theory:
Heat Generation:
As we need propulsion power to run a vehicle which is for an EV – possible by using the needed heavy voltage battery packs?
Heat is generated when the battery pack is being Used and during charging as well.
Therefore, it is necessary to evaluate the battery heat generation to maintain the level of heat within safe limits for safety and durability, better performance.
Operating temperature of lithium-ion battery is an important factor influencing the performance of
Electric vehicles. During charging and discharging process, battery temperature varies due to internal heat generation, calling for analysis of battery heat generation rate. The generated heat consists of Joule heat and reaction heat, and both are affected by various factors, including temperature, battery aging effect, state of charge (SOC), and operation current.
In this article, a series of experiments based on a power-type lithium manganese oxide/graphite battery was implemented under different conditions. The parameters for Joule heat and reaction heat are determined as well as the total heat generation rate is detailed and analyzed considering the influence of temperature, aging, SOC, and current. In order to validate the accuracy of heat generation rate, a lumped battery heat transfer model is applied to calculate the temperature variation, and the estimated temperature variation shows good correspondence with experimental results under different currents and aging conditions. Due to its simplicity, the temperature variation estimation method is suitable for real time applications.
What factors affect the generated heat in a battery?
The generated heat consists of Joule heat and reaction heat, and both are affected by various
factors, including temperature, battery aging effect, state of charge (SOC), and operation
current.
Controlling the heat buildup in EVs:
Battery thermal management is a huge challenge in electric vehicles. In addition to increasing the risk of fire, high temperatures can have a direct influence on range. By efficiently controlling EV
Temperature levels, battery range can be maximized.
Just like internal-combustion engine vehicles, when an electric power train works harder, it gets
Hotter. Therefore, EVs require effective, efficient and durable cooling systems. Heat management can have a major impact on not only the components within a vehicle, but also its overall performance.
Importance of Thermal Management for EVs?
TMS is generally used for batteries operating under a high discharge rate, and especially for a large-
Scale battery pack that requires a long life cycle (>10 years) and is pricy to replace.
The factors that are traditionally considered in the TMS trade-off analysis include energy efficiency,
Capital costs, ease of operation, maintenance requirements, and reliability. Cold plate and
thermoelectric devices are not recommended for use in commercial systems, owing to their high
thermal resistance and low coefficient of performance, respectively.
Battery Thermal Runaway in Electric Vehicles:
Thermal runaway begins when the heat generated within a battery exceeds the amount of heat that is dissipated to its surroundings.
What causes the battery to overheat which leads to thermal runaway?
1. Ambient Temperature
2. Age of the Battery
3. Float Charging Voltage
4. Overcharging
Approaches to Minimize Thermal Runaway
The reduction of the Thermal Runway hazard can be fulfilled on three levels-
1. First: improve the intrinsic safety of anti-TR properties by material modification;
2. Second: set passive defense against the practical abuse conditions and develop an early warning
Algorithm before TR;
3. Third: postpone or inhibit the secondary hazard, such as Thermal Runway propagation, to win
Sufficient time for the passenger to escape from the EV after the accident
Formula:
Heat Generation = Joule Heat + Entropic Heat
Joule Heat = i^2 X r X t
Where, t = time (sec/hr)
i = battery current (A)
r = resistance (mohm)
Joule heating, also known as ohmic heating, is used to directly heat water with electric current.
Joule heating is sometimes also referred to as ohmic heating or electrical resistance heating. It refers
to the method of heating electrolyte-filled water by exposing it directly to electrical current.
The entropic coefficient of a lithium-ion battery cell is used to calculate the reversible heat of a
Battery during operation, which is a no negligible part of the battery thermal modeling.
SOC % (State Of Charge) of a Battery pack:
The SOC is the measurement of the amount of charge remaining on a battery. It represents the ratio of the current capacity of the battery to its nominal capacity after a period of use or long-term
shelving, which also indicates the maximum amount of power that can be stored in the battery. The
SOC is calculated as a percentage: when it’s at 0, it means the battery is completely discharged.
When the SOC is at 100, it means the battery is completely full.
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Absolute Charge State
There is also what’s called an absolute charge state, which is a reference value calculated from the
fixed capacity value when the cell is manufactured. The absolute SOC of a new fully charged battery is
100% while an aged battery, even if fully charged, cannot reach 100% in different charge and dis-
charge situations.
Influencing Factors
Most SOC estimations require precise data measurements, whether it is the chemistry of the cell (type
of electrolyte), its operating conditions, or the variables of the cell (voltage, current), etc., thus being
suitable only in the laboratory and not in real applications. The SOC of a battery is a combination of
voltage, charge/discharge current and internal resistance parameters to estimate its size. These
parameters are also affected by a variety of uncertainties such as battery aging, temperature changes
and usage status.
Accurate SOC estimations reflect important information, such as battery performance, remaining
battery life, etc., which ultimately leads to efficient management and utilization of battery power and
energy. In addition, SOC estimation can be used to regulate battery life degradation, explosions or
fires due to battery over-discharge and overcharge, as well as aging and permanent damage to the
battery cell structure. Therefore, the SOC indicator on a BMS is vital for user convenience, as well as
the efficiency, safety and life of the battery.
Calculations:
1. To find the maximum heat generation of the battery.
| me | Time Step | Battery Current | TIME t 60 seconds =1 minute | Time | Time Step | Battery Current | CURRENT | ||||||||||
| 00:00.4 | 0.1 | -0.9632 | 4 | 00:00.4 | 0.1 | -0.9632 | |||||||||||
| 00:00.5 | 0.2 | -0.952 | 5 | 00:00.5 | 0.2 | -0.952 | |||||||||||
| 00:00.6 | 0.3 | -0.9072 | 6 | 00:00.6 | 0.3 | -0.9072 | |||||||||||
| 00:00.7 | 0.4 | -0.9632 | 7 | 00:00.7 | 0.4 | -0.9632 | |||||||||||
| 00:00.8 | 0.5 | -1.0304 | 8 | 00:00.8 | 0.5 | -1.0304 | |||||||||||
| 00:00.9 | 0.6 | -0.9632 | 9 | 00:00.9 | 0.6 | -0.9632 | |||||||||||
| 00:01.0 | 0.7 | -1.0304 | 60 | 00:01.0 | 0.7 | -1.0304 | I MAX | ||||||||||
| 00:01.1 | 0.8 | -1.008 | 61 | 00:01.1 | 0.8 | -1.008 | |||||||||||
| 00:01.2 | 0.9 | -0.9856 | 62 | 00:01.2 | 0.9 | -0.9856 | |||||||||||
| 00:01.3 | 1 | -0.9632 | 63 | 00:01.3 | 1 | -0.9632 | |||||||||||
| 00:01.4 | 1.1 | -0.9184 | 64 | 00:01.4 | 1.1 | -0.9184 | Given ; | ||||||||||
| 00:01.5 | 1.2 | -0.9296 | 65 | 00:01.5 | 1.2 | -0.9296 | Battery resistance = 0.5 mohm | ||||||||||
| 00:01.6 | 1.3 | -0.9296 | 66 | 00:01.6 | 1.3 | -0.9296 | Entropic factor = 2 | ||||||||||
| 00:01.7 | 1.4 | -0.9296 | 67 | 00:01.7 | 1.4 | -0.9296 | delta time = 0.1 | ||||||||||
| 00:01.8 | 1.5 | -0.9184 | 68 | 00:01.8 | 1.5 | -0.9184 | Currrent = -0.896.....(from the drive cycle ) | -1.0304 | |||||||||
| 00:01.9 | 1.6 | -0.9408 | 69 | 00:01.9 | 1.6 | -0.9408 | |||||||||||
| 00:02.0 | 1.7 | -0.896 | 120 | 00:02.0 | 1.7 | -0.896 | Formula: | ||||||||||
| 00:02.1 | 1.8 | -0.9072 | 121 | 00:02.1 | 1.8 | -0.9072 | Maximum Heat Generated = Joule Heat + Entropic Heat | ||||||||||
| 00:02.2 | 1.9 | -0.9072 | 122 | 00:02.2 | 1.9 | -0.9072 | Now, Joule heat = i^2 X r X t | ||||||||||
| 00:02.3 | 2 | -0.9408 | 123 | 00:02.3 | 2 | -0.9408 | (-1.0304^2*0.5*129 | ||||||||||
| 00:02.4 | 2.1 | -0.9296 | 124 | 00:02.4 | 2.1 | -0.9296 | Joule heat = | 68.48121 | |||||||||
| 00:02.5 | 2.2 | -0.9296 | 125 | 00:02.5 | 2.2 | -0.9296 | Therefore, | ||||||||||
| 00:02.6 | 2.3 | -0.9968 | 126 | 00:02.6 | 2.3 | -0.9968 | Maximum Heat Generated = 68.48121mJ + 2 mJ | 70.48121 | mj | ||||||||
| 00:02.7 | 2.4 | -0.9968 | 127 | 00:02.7 | 2.4 | -0.9968 | Maximum Heat Generated = 70.48121 mJ | ||||||||||
| 00:02.8 | 2.5 | -0.9408 | 128 | 00:02.8 | 2.5 | -0.9408 | |||||||||||
| 00:02.9 | 2.6 | -0.9408 | t MAX | 129 | |||||||||||||
b) The SOC of the battery at 2 *104second of the battery operation
Now coming to State of charge of the battery which is so important in which state of charge is given by
but if we are having the current state of charge we have to use the Coulomb count method
The Coulomb Count Method is given by
were
Cnis battery nominal capacity
Z(t) is state of charge
i(t) is instantaneous current
t is time
niis Coulomb efficiency
by this we can calculate the state of charge of the battery
Now let us design the battery model in Simulink to calculate the SoC% and current in the battery
Simulation Diagram:
SOC �lculation for 208 seconds
The generic battery with 7.2V, 5.4Ah is connected to a Controlled current source with the current reference from the signal builder block in which the signal builder block is loaded with the currents with respect to time values from the given table. The simulation run time is set to 208 seconds.
We can observe that the SOC% is discharging and charging in the above output by its simulink model connectivity .The positive symbol of the battery is connected controller current source negative and negative of the battery is connected to the positive of controlled current source and the controlled current source is connected to the signal builder to check the battery operation for 208 seconds
As we can see the both charging and discharging the SOC has been decreased only 1% of the battery as we can observed and also my drive cycle has been shown for the 208seconds as required.
Data input & signal conversion
output:
Conclusion
A Battery model is designed in the Simulink with the given currents data and given specifications, Calculated SoC% for 208seconds of simulation run time, and also Calculated Maximum heat generated in the battery.
We can observe that the SOC% is discharging and charging in the above output by its simulink model connectivity .The positive symbol of the battery is connected controller current source negative and negative of the battery is connected to the positive of controlled current source and the controlled current source is connected to the signal builder to check the battery operation for 208 seconds
As we can see the both charging and discharging the SOC has been decreased only 1% of the battery as we can observed and also my drive cycle has been shown for the 208seconds as required.
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