Fluent Equivalent Circuit Model Applied to Steady-State Battery Module

Battery Module Thermal Design Challenges

One of the primary challenges in battery module thermal management is ensuring temperatures are below maximum operating limits. Higher temperatures can lead to reduced efficiency, accelerated aging, and potential safety hazards. Engineers must also balance thermal efficiency with the complexities, capabilities, and costs of forced convective cooling.

Understanding and predicting the thermal behavior of battery modules requires integrating the heat transfer processes within the battery and its surrounding environment for a comprehensive analysis of temperature distribution. Simulating modules is essential for enabling engineers to identify potential hotspots and optimize cooling strategies.

Simulating module thermal behavior can be enhanced via physical test data of battery cells. Generating this data can be costly and time consuming as HPPC testing involves multiple cycles, each requiring detailed measurements at different discharge and charge rates. This makes the process time-consuming and may take several hours or even days, depending on the battery’s capacity and testing conditions. Inputting proper values to a simulation model using the HPPC data is also a challenge.

Engineering Solution

Fluent software provides tools for simulating and analyzing thermal behavior in battery modules. With its Circuit Network - Equivalent Circuit Model capabilities, Fluent allows engineers to model complex thermal interactions and evaluate different cooling strategies. The software's ability to handle large-scale simulations makes it ideal for optimizing battery thermal management systems.

By using Fluent, engineers can conduct parametric studies to explore various design configurations and cooling techniques. This enables the identification of solutions that ensure uniform temperature distribution and efficient heat dissipation, ultimately improving battery performance and safety.

To address thermal management challenges, engineers can evaluate multiple inputs using Fluent software. These inputs can include different cell capacity, C-Rate, and HPPC data. Fluent's simulation capabilities allow for evaluation of these different inputs.

Method

Setting up battery module simulations with Fluent in this discussion involves several steps. These steps include thought map, product map, and Fluent case set up.

Thought Map: A thought map of the battery module is generated to organize and represent ideas, concepts, or information in a structured way. The thought map below shows the objective of the simulation study and questions asked to address the objective. Each question is followed by a theory, action, and prediction to address each question. Results would also be added to the bottom of each branch as they are generated.

Product Map: A product map of the battery module is generated to list and categorize product features. The product map indicates design factors that correspond to theories/actions in the thought map. The map below shows an example battery module.

Fluent Simulation: Fluent models are generated per the studies produced by the thought map. In this case a 8-factor, 2-level, fractional factorial DOE is employed which results in 16 unique Fluent models. Inputs pertaining to the battery are set up using the Battery Model. The simulations use Equivalent Circuit Model with active cells and passive tabs. The active cells release thermal energy, and the current is set between the two terminals. The image below shows the sequence of steps for populating inputs for the battery model.

The simulation calculations are executed to generate the results, focusing on temperature distribution and potential field. Treatments data are analyzed to answer the theory questions and confirm or contradict predictions.

Fluent Battery Simulation Results

HPPC Data Resolution: The complete HPPC data set used for the Equivalent Circuit Network consists of 13 SOC levels at 3 temperature levels for a maximum total number of 39 data files. The resolution of this data was varied by using testing 3 SOC levels (low, medium, and high) and by using the full 13 SOC levels. The resolution of the data was also varied by using only the middle temperature and by using the full 3 temperature levels. The resulting 4 HPPC data sets and their corresponding fitted resistance curves are shown below. As less data is used for fitting, the resulting

Graphical Analysis: The maximum cell temperature, in terms of rise over ambient, is graphically displayed for the key input factors as shown below. The impact of the Enable E-Chem Heat Source switch is most evident. If the switch is off then there is no, or very little heat rejection applied to the cells, resulting in no temperature rise. The C-rate has the next strongest influence. As the C-rate is increased the maximum cell rise over ambient temperature increases. The capacity and the initial SOC have mild impact on the maximum temperature. As the capacity increases the maximum temperature increases, and as the initial SOC increases the maximum temperature decreases.

Temperature Visualization: The cell temperature distribution is graphically displayed for the key input factors using temperature contour plots as shown below. The significance of the E-Chem switch and the C-rate is displayed by the contours. The first two columns have E-Chem heat source and Joule heating deactivated.

Impact of Joule Heating switch: The Joule heating switch primarily impacts the prediction of potential field, current magnitude, Joule energy and total energy.

Impact of E-Chem switch: The E-Chem source switch primarily impacts the temperatures of the module as well as the range of the cells network voltage.

Impact of Capacity: The capacity impacts module temperature, heat release, potential field, and network current.

Impact of C-Rate: The C-Rate primarily impacts the temperature of the module as well as the Joule and total heat source.

Impact of Initial State of Charge: The initial State of Charge primarily impacts the range of network voltage. It mildly impacts the module temperatures and Joule/total heat source.

Impact of Reference Capacity: The Reference Capacity primarily impacts the range in network voltage and the network electrical resistance.

Impact of HPPC SOC Resolution: The HPPC SOC Resolution primarily impacts the range in network voltage as well as the total heat source.

Impact of HPPC Temperature Resolution: The HPPC temperature resolution primarily impacted the range in module network voltage.

Setup Details: The following video steps through highlights of the set up.

Ansys Solution Benefits

ANSYS offers advanced capabilities for simulating battery modules which offer numerous benefits, including enhanced design optimization, improved safety, and cost savings. By accurately predicting module performance, manufacturers can design batteries that meet specific requirements more efficiently.

Applications of these simulations extend across various industries, such as electric vehicles, consumer electronics, and renewable energy storage solutions. They help in developing batteries with higher energy densities, longer lifespans, and better thermal management, which are critical for the advancement of these technologies.

Ansys Fluent enables the evaluation of multiple design/input factors such as capacity, C-rate, Joule heating, and initial state of charge. A thermal engineer can evaluate multiple design options to understand the thermal behavior as well as some of the electrical behavior of the cell. Beyond Fluent, ANSYS provides tools such as LS-Dyna, DesignXplorer, OptiSLang, and Twin Builder for further design parametrization and evaluation.

Ozen Engineering Expertise

Ozen Engineering Inc. leverages its extensive consulting expertise in CFD, FEA, optics, photonics, and electromagnetic simulations to achieve exceptional results across various engineering projects, addressing complex challenges like battery module thermal behavior for normal and abnormal operation.

We offer support, mentoring, and consulting services to enhance the performance and reliability of your battery system. Trust our proven track record to accelerate projects, optimize performance, and deliver high-quality, cost-effective results for both new and existing systems. For more information, please visit https://ozeninc.com.

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Tags:

Fluent, heat transfer, ANSYS fluent, Cooling, battery, battery modeling, Joule heating

Post by Brian Peschke
February 19, 2025