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Battery Energy Storage System (BESS) Design using Ansys Fluent

The Challenge

Fueled by an increasing desire for renewable energies and battery storage capabilities, many Utilities are considering significantly increasing their investments in battery energy storage systems (BESS), which store energy from solar arrays or the electric grid, and then provide that energy to a residence or business. This increase in energy storage could address another concern facing Utilities: a demand for a reliable and uninterrupted power source. More stored energy would alleviate the problem of an oversupply when the sun is shining and a shortage when it is not. Several complex factors go into the cost/benefit analysis of any major business decision. In the case of battery energy storage systems, the

potential costs of on-site modifications caused by incomplete or incorrect initial designs as well as the risks—time, money, reputation—associated with system outages could prevent decision-makers from participating in the expected record industry growth.

The Solution

Reduce Risks by Implementing Simulation Early in the Design Process

Rand Simulation has the expertise to provide simulation-based guidance early in the design cycle, ensuring that designs work correctly the first time. Our team has 200+ combined years in the engineering simulation and design industry, and we have completed more than 4,000 CFD, FEA, and electromagnetics analysis projects. Our proven, collaborative approach means we will work with you from brainstorming through successful analysis, making sure the results meet your expectations. And our deep knowledge of the Utility industry means that we will work efficiently because we speak your language, understand your challenges, and are aware of regulations you must follow. Our experts can help you dramatically reduce the chance of costly rework on built structures by testing a battery energy storage system design early in the process, or when the system goes down, identifying possible performance issues, and adjusting the design to address those issues. Our analysis capabilities include:

• Evaluating HVAC performance
• Quantifying temperature uniformity in batteries
• Ensuring temperature is within the range set by warranty
• Resolving aging discrepancies between batteries
• Solving end of life capacity problems

Design Examples

BESS designs balance a wide variety of constraints like external environmental conditions, target capacity & discharge rate, etc. with the need to keep the batteries within a thermal operating window. Failing to do so results in end-of-life capacity issues due to fast aging batteries and may void the battery module warranty. In this section, we will discuss two BESS designs each with their own set of engineering challenges.

Figure 1 shows a typical in-building energy storage using batteries with fan for fast charge/discharge. Cool air is blown directly on top of the rack, and the idea is to have the battery fans pull the cool air down into the cold aisle – the space between the racks – and into the batteries. Seems simple right? Think again! If not balanced properly, hotter ambient air can be drawn in by the low-pressure cold aisle which results in hotter battery modules locally.

Figure 1: In-building designs typically have more space available for the cooling ducts. In this case, the ducts blow cool air right on top of the racks. Battery fans will then suck in the cool air down the cold aisle.

Figure 2 shows a radically different approach to BESS. This design is enclosed within a container for transportability & flexibility. This shifts the focus on optimizing the limited space available to provide maximum capacity without sacrificing temperature uniformity. The fan-less battery modules put added strain onto the HVAC system which must push the cool air through the battery modules without assistance from module fans. It also puts some design constraints on the ducting as even a small imbalance in the airflow delivery can spell doom on the thermal uniformity. Even rack design becomes critical with every gap leaking cool air out of the cold aisle. In figure 2, the duct is not properly calibrated with a cool air deficit in the 1^st and 2^nd duct openings, which translates into higher battery module temperatures locally.

Figure 2: Analysis of Rand SIM’s compact enclosure design concept. The duct delivers cool air into the center cold aisle. No battery fans in this design, battery modules are cooled by air flowing through small gaps between the battery modules.

All in all, an experienced aerodynamicist as well as Ansys Fluent are found to be key advantages to overcome the many challenges of BESS thermal design.

Creating Solids from a Deformed Mesh in Ansys SpaceClaim

Quite often, engineers need to set up a model not by using ideal or undeformed geometry but by using a geometry that has been deformed as the result of structural loading. Checking for clearance or fit within a larger top-level assembly, using the deformed shape for additional simulation or physics, or using the deformed components in a production model could be a reason why a user would seek to create solid geometry from their deformed mesh. With some of the Python scripts available in Ansys SpaceClaim, this process is quite easy.

To start, open SpaceClaim and import the following objects (making sure that they all share the same coordinate system and origin):

1. The original model geometry (solids)
2. The undeformed mesh, exported from Ansys Mechanical
3. The deformed mesh, exported from Ansys Mechanical

 

 

From the File menu, create a new Script:

 

 

Copy and Paste in the code below (This SpaceClaim 2021R1) (Copying the comment lines beginning with “#”is optional)

# Python Script, API Version = V20 Beta

from SpaceClaim.Api.V20.Scripting.Internal import CustomMethods

m0=GetRootPart().Components[0].Content.Meshes[0]

m1=GetRootPart().Components[1].Content.Meshes[0]

b=GetRootPart().Bodies[0]

CustomMethods.WarpBodyByMeshNew(b,m0,m1,False,0.00001)

# m0 uses the Original Model in STL (Exported from Mechanical)

# m1 uses the Deformed Model in STL (Exported from Mechanical)

# b uses the Original Model geometry in imported or native to Space Claim

# 0.00001 is the tolerance in meters

Select Version V20 Beta

 

Next, we need to use the select tool to verify the entity ID numbers for m0, m1, and b. Change the select tool from the Script Editor to use the “Index” method:

Then, turn off recording, select the facet body of the original geometry (it should be inside of a component in the tree), then select the Select Tool from the Script Editor to define that selection. Repeat this process for the deformed mesh and the original body geometry. Verify that the IDs for those entities match the corresponding assignments for m0, m1, and b.

If it is helpful, you can simply Copy and Paste the portion of each line starting with “GetRootPart()…” to the definitions for m0, m1, and b. Once all three objects have been defined, comment out the selections by placing a # at the beginning of each line.

Finally, to create your deformed solid, select Run from the Script Editor.

Running the script creates a 4^th entity called “Warp0” seen in the below Structure tree, which is the deformed geometry in solid form.

Now you are ready to use your deformed components in any number of new applications!

CFD for Electronics Cooling?

It goes without saying that electronics and high temperatures don’t generally mix well; overheating electronics shut down, malfunction, or completely fail. This becomes a significant issue when electronics generate heat as they are being used. If this heat is not removed it can build up, causing failures. 

Historically, hand calculations have produced conservative junction temperature estimates for individual components and boards.  These hand calculations become less effective when estimating heat transfer from one board component to another and throughout system-level assemblies.  Analysis programs can fill this gap, providing design validation for many electronic systems.  Some analysis programs, like Ansys Icepak, help engineers prevent a wide range of electrical, magnetic, and thermal issues in electronics software and are ideal for electronics cooling on component and board-level analysis.  Programs like Icepak are a subset of a larger category of analysis programs that simulate fluid flow and heat transfer.  General Computational Fluid Dynamics (CFD) software, like Ansys Fluent, has wide use for many applications and may have a better choice for electronics cooling than the more specific programs.  This can be overlooked for electronics cooling but there are two areas where CFD’s capabilities make it a good choice. 

As assembly size increases it becomes more difficult to maintain all the small details which make specific electronics software more valuable.  Examples of systems that CFD can be used to simulate range from system-level electrical components and power or control enclosures all the way up to large battery storage facilities and server rooms.  In these cases, some conservative assumptions in a CFD analysis can produce a good quality analysis with both reasonable time investment and complexity.

Many electronics assemblies are air-cooled, either by natural convection or by adding fans to create forced convection.  A general CFD program is a good choice anytime the velocity, air path, or cooling capability of airflow is complex or less defined.  A general CFD program has added the capability to identify the amount of airflow produced by either a fan or natural convection, show flow direction, and even size fans to produce the correct amount of flow through the resistance created by the assembly. 

Analysis software is a valuable tool for electronics design and validation, providing insight into temperature profiles, fan specifications, and room or enclosure design among many others.  Contact Rand Simulation to discuss any electronics cooling projects; let us help you find the right software to solve your problem. 

Optimizing Home Heating with CFD Analysis

As cold weather approaches, many fireplaces and wood-burning stoves are pressed into service.  The idea of sitting next to a fire is comforting, though comfort has not always been the prime reason for fireplaces and stoves.  For thousands of years, open fireplaces with chimneys warmed and fed, everyone from kings to paupers with most of the fire’s heat going up the chimney instead of into the room. 

Reducing flow into the chimney, as well as a poorly designed or blocked chimney, could allow smoke into the room, making an unpleasant indoor environment. It wasn’t until the late 17th century that significant advancements started improving ventilation and efficiency of fireplaces. The 18th century brought several more advancements. Baffling, which were added by Benjamin Franklin and some of his contemporaries, kept hot exhaust gasses in contact with cooler room air, improving heat transfer. Work to improve wood-burning heaters continues, especially in modern pellet-type heaters.

These problems of home heating may seem old, but they are not simple.  Understanding the impact of a wood-burning heater, even excluding the chemical changes due to combustion, involves three invisible factors: air movement, heat transfer, and radiation.  Hand calculations can identify general trends, but they require costly assumptions to work in a 3-dimensional space.  Use of analysis tools makes these three invisible factors visible.      

The results of analysis not only produce answers, they also produce questions.  What would happen if that chimney were larger?  Should it be closer to the front of the fireplace? Should the fire grate keep the fire up higher?  What would happen if the back of the fireplace was more reflective?  Further analysis can quickly answer these questions, resulting in a better final product.

Finally, the analysis process reduces time to market.  Wood-fired heating products have been in continuous improvement for hundreds of years; but movement from concept to market today won’t wait for extended physical testing cycles.  Visualizing design factors and accelerating product improvement cycles will put better products in customer hands faster. 

Off-Label Usage of CFD Leads to Awesome Lazy River Designs

My son takes a daily medication prescribed by a doctor who thought outside the box.  This medication is exceptionally helpful for him, but his issue is not the intended use for this medication.  We frequently have to explain to doctors and pharmacists why he takes it and how it has benefitted him.  This idea of “off-label” use is also applicable to CFD analysis. 

CFD started as a way to solve unsolvable problems and its use continues to grow, though few of us need to solve hypersonic flow over a re-entry vehicle.  Just about any three-dimensional flow or heat transfer application becomes very difficult to calculate without making, sometimes detrimental, assumptions.  Applications of large areas, like building ventilation and industrial manifolds, are frequently reduced to volumetric calculations, (e.g. air changes per hour) which do nothing to identify flow uniformity issues and regions of low flow.  Enter CFD. 

One such application, which initially seems an unlikely candidate for CFD, is the humble lazy river.  Most of us have had an opportunity to float around one of these narrow, winding pools propelled by flowing water.  Historically, river paths have been simple, the jets well defined and flow rate targets low.  As with all things, if a little is good, more must be better.  Why float around a river at 0.5 feet per second when you can be zipped around bends at 2 feet per second?  Why have only one path when the same river can have multiple paths, which increases the amount of time occupants want to stay in the river?  These increased requirements have led to a breakdown in how these new “adventure rivers” are designed.  Without attention to details, such as: the river path, nozzle location and direction, and entrance and exit regions, the design of the pool can have problems not seen in lower-velocity, single path rivers. 

Figure 1:  Surface Velocity of a River

In addition to accurately predicting the surface and bulk velocity of the river, CFD analysis shows how the river profile is driving flow, if propulsion nozzles are well located and directed, and many other areas.  Tight turns in the river can create slow and recirculating flows, trapping occupants and reducing their enjoyment of the river.  A CFD analysis will identify these regions and show how small path changes or nozzle re-location can improve flow.  Figure 2 shows the tight bend from the lower left corner of the river. 

Figure 2: Surface Velocity Map and Velocity Iso-Surface Showing Flow from Propulsion Nozzles

This is a region where flow must change direction quickly.  Without proper propulsion nozzle placement a large region of recirculating flow can restrict river flow and decrease surface velocity throughout the river. 

Figure 3: Surface Velocity through a Zero-Depth Entrance and Exit Region

Flow in and around entrance and exit regions, especially large, zero-depth regions can make entrance and exit either easy or challenging for pool occupants.  The entrance region in Figure 3 shows the river flow splitting and a large channel of higher-velocity water flowing into the shallow area with a recirculating region between them.  This could make both ingress and egress more difficult and possibly dangerous.   An inconvenienced occupant could find their tube swept into the river without them, whereas a parent could see a young child swept in.  A small change to the upstream wall angle and radius could keep more high velocity flow in the river and out of the entrance area. 

CFD is a powerful and flexible tool, able to predict safe re-entry of astronauts and keep vacationing tourists from being caught in recirculating traps.  If you have an application where hand calculation fails to show the full picture, contact Rand Simulation to discuss how an out of the box, or off label, approach to CFD can help.

When Does it Make Sense to Bring Simulation In-house?

When deciding whether to bring simulation in-house or to hire a consulting partner to solve your simulation problems, there is rarely an easy answer. This article provides clarity into the benefits of bringing simulation software capability in-house vs. hiring a consulting firm to do the work for you.

To start, the decision between in-house vs. hiring out, is not binary. Often, the most economical and best engineering option is to utilize a blend of the two. An example of this would be to hire out your first project for consulting and use this simulation as a template for your continued use of the software going forward. Through this project, your engineers will learn how to convert a real-world problem into a simulation that provides insight into your design and allows them to continue solving future problems in-house. Here, we cover three options and highlight when each approach is appropriate. The options include: doing the work in-house, hiring an outside consultant, and a blend of both.

When should you hire outside consultants?

If you have a project and you do not have the resources to purchase simulation software and/or the time to hire and train your own simulation engineer, this is the option for you. A consultant like Rand Simulation works with your engineering team to determine what the best and most economical route is for your specific problem. Throughout the simulation process, we hold meetings with your engineering team ensuring there is collaboration throughout the project timeline, making sure the simulation gives you the results you need to make the necessary verifications or changes to move forward on your project deadlines.

When should you blend the hiring of consultants and bringing software in-house?

If you have an individual on the team who has used simulation in the past or is familiar with how simulation works and wants to begin to incorporate it into their design processes, this is the option for you. By hiring out the first project it can provide experience for your engineer on how to take a real-world process and convert it into a simulation that will provide valuable insight into your design. When you hire a consulting partner like Rand Simulation to consult on your first project, we become an extension of your team. In doing so, we bring your engineer into the simulation process, explaining why we made decisions on geometry changes, mesh sizes, boundary conditions, and simulation methods to help give them insight and establish their intuition on how to perform these practices themselves. As a result, your first project is finished quickly using our simulation experts while your engineer learns from experts how to perform quality simulations that can be easily utilized for design decisions. This will help you avoid the garbage in, garbage out issue by giving your engineers an understanding of what it takes to generate useful data using simulation.

When should you bring simulation software in-house?

The best time to bring simulation software in-house is when you have a simulation engineer on the team or you have an engineer who is familiar with simulation and is willing to go through training to learn how to use the software. When you have a simulation engineer already on the team, bringing simulation in-house is easy as they are familiar with the software and require minimal training. When you do not have a dedicated simulation engineer, an engineer on the team is going to require training. This engineer has two courses of action for training. It can be done through personalized training sessions or by utilizing predefined training documents available when you buy an Ansys Learning Hub (ALH) license. The personalized training sessions offer your engineers tailored learning sessions to help them with the design problems they need to solve. It allows them to apply techniques to transform real world problems into solvable simulations in a feasible timeframe. It also allows your engineers to get up to speed with how to use simulation software and teaches them best practices to produce reliable results to use in design processes.

If they decide they want to utilize the Ansys Learning Hub, they will not have the tailored training sessions and custom material, but they will have access to hundreds of online documents and tutorials over a wide range of problems. These documents can help teach your engineers the basics of how to run the tool and the types of scenarios in which simulation can be used; they will just need to take the last step in applying it to the problems you need solved.

If you do not have a dedicated simulation engineer or an engineer willing to go through the training that they need, it is highly recommended that you do not bring simulation in-house immediately. Instead, focus on sending the work out to consultants or opting for a blended approach, as discussed above. Once your engineer has the time or you have the resources to hire, then the decision to bring the software in-house can be re-evaluated.

If you bring simulation in-house without a dedicated simulation engineer or an engineer who will not go through training, you run the risk of falling into a trap of garbage in, garbage out. This is because when someone is running a simulation tool and is unsure of the knobs that can be turned and how they influence the results, there is a high risk that simulation data will be unreliable. This is part of the reason why the blend between hiring consultants and bringing the software in-house can be so useful, as it optimizes the time to produce results for your first projects, while steadily bringing your engineers up to speed on how to leverage simulation during the design process.

Lastly, if you are still unsure whether you need to bring simulation in-house, hire it out, or utilize a blend of the two, Rand Simulation personnel are here to answer your questions and help you make the best decision from both an engineering and business perspective.