Using simulation to accurately predict physical behavior and advance personalized urban rapid transit

Navigating complex guideway networks

skyTran is a personal rapid transit system that is taking aim at the world of gridlocked traffic. skyTran was founded in 2011 and awarded a grant by the Research and Innovation Technology Administration, which is part of the United States Department of Transportation. Now a NASA Space Act company, skyTran is headquartered in Huntington Beach, California.

skyTran is a high-capacity, personal mass transit system. Its on-demand, personal occupancy vehicles allow riders and cargo to travel above the road at freeway speeds and beyond. Vehicles operate autonomously and use proprietary switching technology to safely navigate complex guideway networks direct-to-destination without the constraints of ground-based
corridors.

Passive magnetic levitation and propulsion

skyTran uses a modified and improved maglev variant called electrodynamic suspension based on coupled levitation and propulsion systems. skyTran’s propulsion system uses a drive motor with a magnetic rotor and aluminum stator. In contrast, the levitation system uses the electromagnets in the vehicle and their interaction with the steel guideways.

To develop this revolutionary transport system, the skyTran C-suite wanted to use the latest technology to ensure they could rapidly build a high-quality product within budget. They had a full-scale test rig but each test takes a lot of time to set up and costs a lot in both labor and materials. Additionally, it can be difficult to visualize what is happening in the physical system
while it is operating, necessitating adding sensors to try and gain more information that can influence the behavior of the system. So they wanted a simulation solution that could reduce the size of the test rig’s program and interrogate the test in new, faster and cheaper ways.

The high-speed challenge

What made this project particularly challenging was the high speed of the vehicles (about 100 miles per hour), which pushed the envelope on current modeling techniques. However, skytran chose Simcenter™ MAGNET™ software, which is part of the Siemens Xcelerator business platform of software, hardware and services, to help them confront this issue.

They recruited Iana Volvach, a magnetics finite element analysis (FEA) engineer, an expert in spintronics (the physics of nanomagnetic materials) as well as in the modeling and simulation of electromagnetic devices. Once she arrived at skyTran, Volvach set to work using Simcenter
MAGNET to help build simulation models for the levitation and propulsion systems.

“We can directly import the CAD model of the hardware into Simcenter MAGNET without doing any geometry modification or adjustments,” says Volvach. “This means the representation of each lamination is an exact representation. Simcenter MAGNET takes into account each layer of the lamination and each insulation between the laminations. This makes the probability of mistakes during modeling very low and it is also user friendly for beginners.

”In my case, I had a CAD model of the hardware test with a fixed amount of laminations of given thicknesses. I imported the CAD into Simcenter MAGNET and ran simulations.”

Volvach worked on a range of studies successfully, but optimizing the laminated steel proved to be a challenge. She knew
that she could reduce the effects of eddy
currents by slicing the material that made
up the core. So she began a rigorous vali-
dation process to ensure she would have
confidence in her models when she began
her experiments.

The disadvantage of eddy currents

Eddy currents are initiated by a magnet passing a steel rail. In magnetic levitation (maglev) vehicles, eddy currents induce electromagnetic drag and reduce the attraction force between the magnet and the rail. As a result, an increase in speed decreases the attraction force and
increases the drag force. Both effects are undesirable and are a key part of skytran’s research and development (R&D).

To reduce the negative effects of eddy currents, the circulating currents need to be minimized by increasing the resistance of the steel rail. This is done by forming the cores from laminated steel layers in a steel-laminate-steel sandwich.

The stacking of insulating and steel layers makes each lamination a separate electrical conductor but lets the magnetic flux pass through it. So compared to a solid/unlaminated steel rail, the laminated steel rail increases the resistance of the rail and reduces the drag force generated when the electromagnet’s speed of motion is increased. Electrodynamic suspension maglevs are still in their infancy. Therefore, optimizing the steel rails and their lamination is a key area of development to improve the system’s overall performance.

Volvach ran correlation tests in Simcenter MAGNET to compare experimental data with simulated tests. She found that results with solid (unlaminated) disk/cores aligned with lab and simulation results. However, when working with a laminated disk and core, she had trouble getting the same level of agreement between results. Volvach assumed she was making a mistake with the Simcenter MAGNET setup but wasn’t sure where the mistake was in the process.

Figure 1. Model setup using Simcenter MAGNET software.

Strategic adjustments

Volvach began by reading a Siemens knowledge base article (KBA) by a Siemens support engineer who is an expert in Simcenter MAGNET. The KBA was a study about anisotropy and the Simcenter MAGNET perfect electric insulator (PEI) boundary condition to approximate the thin layers of insulation between steel laminations.

The advice in the KBA, while appropriate for Volvach’s simulations, was not a perfect fit because she was using a small number of relatively thick steel plates to suppress eddy currents. In fact, she was trying to determine how few plates would be enough to suppress eddy currents and electromagnetic breaking within the company’s specifications. The Siemens support engineer prescribed a few strategic adjustments that Volvach could make to
maintain a favorable accuracy to speed trade-off in the simulations.

“I was really pleased with the Simcenter MAGNET results and I don’t know if I could have modeled what I needed with any other software,” says Volvach. “The particularly interesting thing we found is that we didn’t need nearly as many laminations as we expected, making our final design much simpler.”

Result validation

Both measurements and simulations were performed for the lift and drag forces as a function of the rail speed and for different air gaps, coil currents and steel material parameters (magnetic permeability and conductivity). Results showed that both the lift force and the drag force are dependent on all of the aforementioned parameters.

The measured and simulated data sets differed by 4 to 10 percent. The measured forces variously exceed the simulated ones due to human factors and material variability in physical tests.

“Given that materials always vary, there are errors due to physical measurements and the model is simplified to make modeling easier, we were very happy to have a difference between physical test and simulation of around 7 percent,” says Volvach.

Figure 2. Comparison of measured and simulated lift forces (a) and drag forces (b) as a function of
the rail speed for different air gap distances.

Simulating the future of mass transit

skyTran was able to develop a Simcenter MAGNET simulation model of electromagnetic devices in their maglev mass transit system, and they are confident this model accurately predicts the behavior of the maglev system. With this newfound confidence, skyTran can more rapidly move forward with developing new maglev concepts while reducing the costs they need to spend on physical prototyping and testing.

“When we use Simcenter MAGNET we quadruple the rate at which we develop, test and manufacture new parts compared to not using simulation at all,” says Volvach. “In terms of the cost, we can save a lot since we don’t buy the parts to create every single experiment and the test fixture for them. When modeling with Simcenter MAGNET we can reduce the development costs by 90 percent compared to when no simulation is used.”