Project 2 Thermal modeling of battery pack
PROJECT 02
THERMAL MODELLING OF BATTERY PACK
AIM: For a 10-cell series lithium-ion battery model, simulate the thermal effects and compare life cycle performance at various temperatures, charge & discharge rates using MATLAB.
ABSTRACT
Lithium-ion batteries play a pivotal role in modern energy storage, powering a diverse range of applications from portable electronics to electric vehicles. This project is a comprehensive investigation conducted using MATLAB to model the thermal dynamics and evaluate the life cycle performance of a 10-cell series lithium-ion battery under varying temperature conditions and charging/discharging rates.
The project features a robust battery model that combines electrical and thermal components to accurately replicate the intricate behavior of a 10-cell series battery pack. The thermal model encompasses the heat generated during charging and discharging processes, the heat transfer within the battery pack, and the influence of surrounding temperature variations. A set of representative charge and discharge profiles are employed to simulate real-world operational scenarios.
INTRODUCTION
The Significance of Thermal Modeling for Battery Packs:
Thermal modeling for battery packs is a fundamental aspect of battery system design and management for several compelling reasons:
Ø Safety Assurance: Batteries can generate substantial heat during operation, and if not effectively managed, this can lead to hazardous conditions like thermal runaway. Thermal modeling helps anticipate and mitigate temperature-related safety concerns, ensuring the well-being of both users and the equipment.
Ø Optimizing Performance: Temperature has a profound impact on a battery's performance. Modeling enables us to identify optimal operational conditions that maximize energy efficiency and power output, thus ensuring that the battery performs at its best.
Ø Prolonging Battery Life: Elevated temperatures can expedite battery degradation, potentially shortening its useful life. Through thermal modeling, it's possible to forecast how various operating conditions will affect battery longevity and implement strategies to extend its life.
Ø Efficient Cooling Solutions: By simulating the temperature distribution within a battery pack, thermal modeling assists in designing effective cooling solutions, including heat sinks, liquid cooling systems, and fans. This aids in maintaining safe and efficient operating temperatures.
Ø Adaptation to Environmental Conditions: Batteries are deployed in a wide range of environments, from extreme cold to scorching heat. Thermal modeling enables the development of batteries that can reliably perform across diverse temperature ranges, making them suitable for a broader spectrum of applications.
Ø Accurate State-of-Charge (SoC) Estimation: Temperature variations can impact the accuracy of SoC estimation. Thermal modeling provides insights to correct SoC estimates based on temperature fluctuations, which is vital for precise battery management.
Ø Energy Storage Systems: In applications such as electric vehicles and renewable energy storage, a profound understanding of thermal behavior is critical for efficient energy utilization and the preservation of costly battery packs.
Ø Optimized Charging and Discharging Strategies: Thermal modeling facilitates the design of charging and discharging protocols that prevent overheating, promote cell balancing, and maintain uniform temperature distribution, ensuring safe and efficient operation.
Ø Cost Reduction: Insight into thermal behavior enables the design of cost-effective cooling and thermal management solutions, reducing the need for overly complex or expensive systems.
Ø Material and Design Selection: Thermal modeling guides the choice of materials and designs for battery packs, enhancing thermal conductivity and dissipation, thereby contributing to improved performance and extended service life.
Ø Quality Assurance: In the manufacturing process, thermal modeling serves as a valuable tool for quality control, ensuring that batteries consistently operate within safe temperature thresholds.
Incorporating these optimization techniques into the design and operation of a battery pack is essential for extending its longevity and ensuring its reliability in a wide range of applications. These strategies not only enhance the performance of the battery but also contribute to cost savings and environmental sustainability.
THEORY
Required Simulink models to build the circuit:
1.
Battery (Table Based): The Battery block represents a battery model. A table-based battery model often uses data to simulate the behavior of a real battery under different conditions, such as state of charge, voltage, and current.
2.
Temperature Source: The Temperature Source block generates temperature data. It could represent the temperature of the environment or a specific component within the system.
3.
Controlled Current Source: The Controlled Current Source block generates a controlled current signal. This can simulate various current inputs or sources in your system.
4. Current Sensor: The Current Sensor block measures the current flowing through a component or circuit and provides that information for further analysis or control.
5. Temperature Sensor: The Temperature Sensor block measures the temperature at a specific point in the system and provides this data for monitoring or control purposes.
6.
Voltage Sensor: The Voltage Sensor block measures the voltage across a component or circuit and provides this information for analysis or control.
7.
Thermal Reference: The Thermal Reference block typically serves as a reference temperature point in your simulation, often used for comparison with other temperature values.
8. Convective Heat Transfer: The Convective Heat Transfer block models heat transfer between a component and its surroundings through convection, which is a common mode of heat dissipation in many systems.
9. Signal Builder: The Signal Builder block allows you to create complex input signals, making it useful for testing and validating your system under different operating conditions.
10.
Electrical Reference: The Electrical Reference block is often used to set a reference point for electrical potential (voltage) within the circuit.
11. Integrator Block: The Integrator block performs mathematical integration, which is useful for tasks like calculating the cumulative effect of a signal over time, such as calculating state of charge in a battery.
12. Solver Configuration: The Solver Configuration block lets you set the solver settings for your simulation. This can include choosing a numerical integration method and specifying tolerances.
13. Goto Block and From Block: Goto and from blocks are used for creating signal connections between unusual parts of your Simulink model. They help organize and simplify the model by providing a clear path for data flow.
14.
Scope: The Scope block is a visualization tool that allows you to monitor and plot signals during simulation, helping you understand the behavior of the system.
These Simulink blocks are crucial for building a comprehensive model of a system, particularly when you need to simulate and analyze the behavior of electrical and thermal components in real-world applications. They enable you to create complex simulations, monitor system performance, and optimize designs.
SIMULINK MODEL
WORKING OF SIMULINK MODEL
Here I am briefly explaining about how the Simulink model is being built and the working principle of each block in the model based on lithium-ion cell configuration.
Battery Configuration: Firstly, setting up the table-based battery model and installing it, which allows you to monitor and control its behavior. The thermal port and SOC port are activated for temperature modeling, while other parameters remain at default values. This battery model doesn't use specific data sheets but relies on default MATLAB data.
Series Connection of Battery Cells: Ten identical battery cells are connected in series, multiplying the total pack voltage by a factor of ten. However, the capacity of each cell remains constant but voltage increases, resulting in a series configuration with consistent capacity throughout the pack.
Voltage Sensing: To monitor the pack's voltage, a voltage sensor is connected across the first and last cell terminals. A Goto block connected to a PS to Simulink Converter is used to extract the voltage signal. A From block then connects this signal to a Scope for visualization.
Current Measurement: To measure the current drawn from the battery, a controlled current source is connected to the battery model. A current sensor captures the current value, and a PS to Simulink Converter connected to a Goto block allows you to access the current data. A From block delivers this information to the Scope for observation.
State of Charge (SOC) Estimation: SOC is estimated by integrating the battery's current over time. The integrated current is divided by the total pack capacity (27 Ah or 27 * 3600) to yield an amperes-second value. This value is then subtracted from one to calculate the SOC. A Goto block retrieves the SOC output, and a from block sends this data to the Scope for monitoring.
Input Signal Generation: A Signal Builder block is used to generate the input current signal. In my case, I’m using the UDDS drive cycle data, which provides the current profile over time, representing a real-world scenario.
Temperature Modeling: Temperature modeling is incorporated via the thermal port. The Temperature Source block simulates the external temperature, and it's connected through a Convective Heat Transfer block to enhance the area of contact. A Temperature Sensor captures the temperature of the battery pack, with one port linked to a Thermal Reference.
Temperature Sensing: A Temperature Sensor captures the temperature within the battery pack. Data from the temperature sensor is transmitted through a Goto block via a PS to Simulink Converter and is then delivered to a from block, which directs the information to a Scope for temperature visualization.
Electrical Reference and Solver Configuration: An Electrical Reference provides a ground reference in the electrical part of the model. A Solver Configuration block is used to configure solver settings for the simulation.
Simulation Run: The simulation is executed for a specific time duration, in this case, 1369 seconds, aligning with the input current profile. Beyond this time, the system doesn't experience any load current, causing the outputs to stabilize.
The complete analyzed working principle of the Simulink model for a thermal modeling of 10 series battery pack is explained.
SIMULATION RESULTS
Ø AT 20 degrees Celsius (Normal temperature)
Here, I just used all the default parameters from the Simulink blocks as it is maintaining normal temperature.
There is a temperature rise in the battery pack as time progresses but when it comes to state of charge it has slight decrement in the battery charge/discharge percentage which is from 1 to 0.8, current profile is fluctuating as the vehicle stops and accelerates frequently with traffic dynamics in urban areas.
Ø AT 75 degrees Celsius (higher temperature)
I updated the values of convective area to 1m^2 from 1e^-1 initially and the temperature raised to 75 degrees Celsius.
Though there is increment in the temperature, the state of charge hasn’t changed much, voltage and current dynamics also have not changed due to the constant load in the output.
Ø
AT -50 degrees Celsius (Low temperature)
Finally, I decreased the temperature input to minus 50 degrees Celsius and increased the area of convective heat transfer, as we can see there is not much change in the current and voltage, there is a fluctuation in voltage and current profile which tells us about traffic dynamics of the vehicle in urban area, but temperature is being decreased rapidly from 300 to 210 degrees Celsius approximately.
CONCLUSION
In summary, this project highlights the crucial role of thermal modeling of 10 series battery packs in enhancing the safety, performance optimization, and adaptability of lithium-ion battery packs. The Simulink model developed as part of this study offers valuable insights into battery behavior across varying temperature conditions, serving as a foundation for the refinement of battery design and management approaches.
REFERENCES
https://www.laserax.com/blog/ev-battery-cooling
https://www.mathworks.com/help/sps/ug/lithium-pack-cooling.html