Argonne National Laboratory represents the United States’ Department of Energy’s commitment to cooperative research and scientific discovery. Since its inception in 1946, Argonne has pioneered laboratory research and experimentation as the first national laboratory in the United States. While a significant amount of research in the decades following its founding centered around nuclear energy and applications, Argonne has transitioned from nuclear research to include additional energy sources and storage since the beginning of the 21st century. Now, Argonne constitutes a scientific community of leading researchers, with projects across a spectrum of computational, quantum, and interdisciplinary fields.
Among the contributors in this area are Dr. Joohan Kim and Dr. Riccardo Scarcelli. Their work on modeling spark discharge processes in spark-ignition (SI) engines was recently recognized by Argonne. Dr. Kim received a Postdoctoral Performance Award in the area of Engineering Research, along with ten other postdoctoral appointees whose contributions set a standard not only for the quality of their discoveries, but also for the ingenuity of their techniques and demonstrated leadership capabilities. According to Argonne, awardees’ works have upheld core values of scientific impact, integrity, respect, safety, and teamwork.
Within the highly competitive automotive industry, the need for innovation through design presents opportunities for new tools and technologies to be utilized. Regulations from governing entities seek to strike a balance between meeting climate goals through greater restrictions on CO2 emissions from automobiles, while relying on the transportation industry and automotives to fuel trade and commerce. With restrictions focused solely on reducing emissions, applications that meet these criteria without sacrificing capabilities stands out for both manufacturers and legislators alike.
Dr. Kim’s work highlights the need for predictive models which can optimize operational parameters for SI systems in order to maximize thermal efficiency gain and lower engine development costs. Creating these predictive models requires advanced simulation software capable of solving and coupling electromagnetic physics and fluid dynamics into a computational framework. When we asked about his use of simulations, Dr. Kim said, “high-fidelity simulations enable us to perform in-depth analysis of the spark-ignition process, including energy transfer, birth of flame kernel, and thermo-chemical properties; these would be difficult to obtain using experimental techniques only.” He went on to add that, “with a fundamental understanding of complex physics, we can develop predictive models that make simulation-based optimization robust and reliable.”
“VizSpark provided a fully-coupled framework between electromagnetic physics and fluid dynamics, and thereby we were able to diagnose the plasma properties occurring within tens of nanoseconds without many assumptions.”
Dr. Kim’s study utilized VizSpark simulations to accurately estimate electrical discharge shape, as well as temperature and pressure of plasma kernels, thus providing a set of robust initial and boundary conditions for studying flame kernel growth under engine-like conditions. He noted “VizSpark provided a fully-coupled framework between electromagnetic physics and fluid dynamics, and thereby we were able to diagnose the plasma properties occurring within tens of nanoseconds without many assumptions.”
VizSpark is a robust, industrial simulation tool for high-fidelity modeling of thermal (arc) plasmas. Additionally, VizSpark is fully parallelized and can be used to perform large, 3D simulations with complex geometries. Its comprehensive solvers and scalability make it ideal for solving real world engineering problems.
Interested in learning more about plasma flow simulations? Click here to take a look at our previous article. Feel free to follow us on Twitter and LinkedIn for more related news, or reach out to us directly at info@esgeetech.com.
The future of transportation seems to be increasingly electric. In its latest report on electric vehicles (EV), the International Energy Agency (IEA) highlights a 40% increase in EV demand despite a 16% dip in the global car sales. Moving towards electrified vehicles has also pushed a shift in the vehicle design where the mechanical components are being replaced with electronic-based automotive components. Relays play a critical role in such electrified systems.
A relay is a switch that is operated electrically and is used to control a high power circuit with a low power signal circuit. The most common type of relay is an electromechanical relay that consists of terminals for the signal and the terminals where the supply and load are connected. Upon receiving a signal, an electromagnetically operated armature closes or opens the gap between the supply and the load terminals. Traditional electromechanical relays dominate the market, over solid state relays, because of their advantages in a wide operating range of voltages and currents and the low cost to manufacture due to the simplicity in design. However, the main problem that affects the lifetime of electromechanical relays is arcing.
The primary undesirable effect of arcing is sudden load surge in a circuit. This delays the signal to the primary circuit breaker to isolate the load device, which may fail due to overcurrent. Further, arcing leads to high surface temperature which can erode the terminals and contactors or even weld the contactors to the terminals. Both of these undesirable phenomena cause a great deal of reliability and safety issues. The strength and duration of the arc have a significant impact on the safety of electric vehicles as well as on relay contactor erosion, therefore the lifetime of the relay.
Therefore, it is crucial to study the formation of arcs within relays and explore designs that suppress the arc formation. At Esgee Tech, we delve further into how this disengagement happens and what could be done to improve it further. An insight into these phenomena could allow faster mitigation of arcs and thus quicker response times.
Arc – The Most Energetic Type of Plasma Discharge
A gaseous medium that experiences a sufficiently high electric field results in ionization of the medium which causes the medium to become conductive. We call this an electrical discharge. The characteristics of an electrical discharge depends on the voltage and current as shown in the figure on the left. Discharges carrying large currents, such as illustrated in this blog post, are classified as arcs. Arc is self-sustaining, i.e., it does not require an external ionization source to maintain discharge – the internal electron and gaseous processes maintain structure of the arc.
The physics of arcs is very complex. Ambient pressure, ambient temperature, geometry of the electrodes, gas composition, electromagnetic fields, external circuit parameters and surface properties all dynamically affect the formation and quenching of arcs. Industrial designs of relays need to account for all of these tightly coupled phenomena.
Our engineers at Esgee Tech have developed VizSpark™, a robust and accurate thermalized plasma simulator. VizSpark™ allows coupling of reactive plasma mechanics, fluid dynamics, transient electromagnetics, radiative mechanisms, surface erosion physics, circuit dynamics and continuously morphing boundaries. VizSpark™ also supports complex 3D industrial geometries.
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Using VizSpark™ the industrial problem of understanding arcs and optimizing design and safety of EV relays can be effectively addressed at high fidelity.
EV Relay Computational Model and Results:
The electric vehicle relay geometry described in this blog comprises a stationary anode (left terminal), a stationary ground (right terminal) and a movable contactor that disengages to break the circuit. The circuit coupled with this domain is a 220 V DC supply via a load resistor as shown in the figure below. The gas composition in the relay is hydrogen which is kept at a pressure of 1 bar and 300 K. An external magnetic field of 1T is imposed in the z-direction (into the screen).
VizSpark™ captures breakdown of arc between the electrodes accurately as shown in the illustration below. Initially, about 35A flows through the arc, upon ignition. The Arc stretches outwards due to Lorentz force generated by the interaction of the arc with the external magnetic field. The total resistance of the arc increases as it stretches. This decreases the current and cools down the arc as temperature decreases due to reduction in joule heating. The partially extinguished arc reignites several times, around 400 µs, before finally extinguishing, in a phenomenon called restrike. VizSpark™ accurately simulates the stretching of the arc and formation of a new filament during restrikes. This is seen as a “saw-tooth” waveform in both transient voltage and current graphs.
As the gap between the contactor and terminals increases, the conditions are unfavorable for restrikes and fewer restrikes are seen in the later stages of the simulation. The potential across the gap increases to 220V and the current drops to 0A which marks a completely extinguished arc and the relay circuit is open.
Trade Studies with VizSpark™
A variety of methods can be applied to ensure faster quenching of the arc, which reduces the electrical cutoff time. A few techniques to extinguish the arc quickly are: stretching the arc through external magnetic fields, increasing the speed of the moving contactor, using gas mixtures that absorb electrons such as SF6, using gas mixtures with high thermal conductivities such as hydrogen, and using an arc chute/splitter plates to divide the main arc into smaller faster dissipating arcs. Further, use of external circuits such as snubber circuits which consist of a series configuration capacitor and resistor connected in parallel across the relay suppresses the spike in current as the voltage starts to fluctuate during arc quenching. All of these configurations can be simulated at fidelity using VizSpark™.
The computational model shown here is capable of incorporating comprehensive arc physics necessary to study quenching behavior in high-voltage EV relays. The model can be used to perform design/parametric studies on EV relays in reasonable computational time. Future work should involve detailed validation of the model with existing experimental data. Other avenues of research include incorporating eroded metal vapor, the inclusion of arc chute or splitter plates, and electrode deformation due to erosion.
We hope you are someone who is as fascinated about plasma flow simulations as we are, feel free to follow us at LinkedIn or reach out to us at info@esgeetech.com.
In the meantime, explore the following journal articles (do ask us for a free copy!):
Karpatne, A., Breden, D., and Raja, L., “Simulation of Arc Quenching in Hermetically Sealed Electric Vehicle Relays,” SAE Int. J. Passeng. Cars – Electron. Electr. Syst. 11(3):149-157, 2018, https://doi.org/10.4271/2018-01-0765.
N. Ben Jemaa, L. Doublet, L. Morin and D. Jeannot, “Break arc study for the new electrical level of 42 V in automotive applications,” Proceedings of the Forth-Seventh IEEE Holm Conference on Electrical Contacts (IEEE Cat. No.01CH37192), 2001, pp. 50-55, https://www.doi.org/10.1109/HOLM.2001.953189
R. Ma et al., “Investigation on Arc Behavior During Arc Motion in Air DC Circuit Breaker,” in IEEE Transactions on Plasma Science, vol. 41, no. 9, pp. 2551-2560, Sept. 2013, https://www.doi.org/10.1109/TPS.2013.2273832
This example demonstrates charge-up of initially charge-free dust particles as they move through a pin-corona plasma. Two sets of particles move through the corona with different initial velocities. The dust particles are subject to Lorentz forcing in the electric field and their resulting trajectories are compared. The macroscopic particle dynamics is modeled in VizGrain and coupled to a background plasma solution modeled in VizGlow.
The 2D planar pin geometry and mesh is shown in Figure 1. The pin is 5mm long with a base diameter of 3mm. The pin is modeled with a sharp tip. The geometry is discretized using a fully structured mesh with 79,050 cells. A voltage of -10kV is applied to the pin with a background gas of pure argon at 1atm.
Two sets of dust particles enter from the left boundary with an initial velocity in the horizontal direction. The dust particles have a mass of 1.4×1017 kg and a diameter of 300nm. The first set of particles has an initial, horizontal velocity of 150m/s. The second set of particles has an initial velocity of 50m/s. All particles are initially uncharged.
First, the background plasma and electric field is solved in VizGlow. Results from the plasma solution is shown in Figure 2.
The maximum electric potential is observed in the steady state solution around the pin geometry. The negative corona discharge is formed from the electron avalanche extending tip of the pin into the volume. The electron number density reaches a maximum of 3.6×1020 very close to pin tip. The electron temperature reaches a maximum of 33,500K or approximately 3eV.
Next, VizGrain is used to solve the dust particle motions over the background plasma. This uses a one-way coupling of the electrostatic potential and Lorentz forces with the dust particle dynamics. The resulting VizGrain solution is shown in the animation in Figure 3.
Figure 3. Dust particle trajectories through pin-corona discharge. First column of particles has an initial velocity of 150m/s. Second column of particles has an initial velocity of 50m/s.
Both sets of particles charge-up as they move to the right. Charge-up is caused by the flux of ions and electrons on the particle surface. The flux is a function of dust particle size, as well as the ion and electron number densities, masses, and temperatures. This flux is also dependent on the floating potential of particles, obtained from the VizGlow plasma solution.
The first set of particles, with an initial velocity of 150m/m, has sufficient momentum to pass through the corona as they charge-up. The second set of particles, with an initial velocity of 50m/s, does not have sufficient momentum to pass through the corona and are deflected as they charge-up in the corona.
This demonstrates the effects of dust particle charge-up and Lorentz forcing using a one-way coupled solution between VizGlow and VizGrain. VizGlow and VizGrain are both modules within the OverViz Simulation Suite. OverViz is an industrial multiphysics framework for performing hybrid plasma, fluid flow, electromagnetic, particle simulations. For more information, please contact us at info@esgeetech.com.
VizSpark is used to model a non-transferred direct current plasma torch in pure argon gas assuming axi-symmetry along the central axis. A steady state thermal plasma with temperatures from 15-20,000 Kelvin forms a supersonic, under expanded jet in the ambient region with visible Mach diamonds.
Plasma torches are devices that produce a steady thermal plasma jet. There are many applications for plasma torches including arc cutting, wielding, plasma spraying and waste treatment.
A plasma torch works by passing a high current between a working gas, typically an inert gas such as argon, helium, hydrogen or a mixture of inert gases. The high current arc heats the gas mixture to high temperatures (15-20,000 K) which then exits the device forming a jet of high temperature plasma. Plasma torches typically use direct-current (DC) power source applied through a central (hot) powered electrode. A plasma torch can either user a transferred arc, where the working material located outside the device acts as the anode, or a non-transferred arc where the anode is located inside the torch housing.
The simulation demonstrated here is for a direct-current, non-transferred arc using pure argon as the working gas.
Fig. 1 shows a typically plasma torch device as well as the domain and mesh for the simulation presented here. For this simulation, an axi-symmetric assumption was made to simplify the mesh and reduce the computational cost. The domain consists of a 2.5 mm radius tube that expands to a 5 mm. A 2.0 mm radius pin powered electrode is placed along the axis in the wider tube region. The walls of the tube act as the anode. Argon gas is fed into the tube from the bottom boundary at a total pressure of 3 bar, and the ambient outer region is kept at a pressure of 1 bar.
Fig. 2 shows the plasma temperature (top) and gas pressure (bottom) after a quasi-steady state has been reached. Gas temperatures exceed 20, 000 Kelvin inside the device while gas temperatures in the ambient jet are on the order of 15,000 Kelvin. The gas leaves the torch housing at supersonic flow velocities (4000 m/s) with pressures higher than the ambient. This results in an under expanded jet with Mach diamonds clearly visible in Fig.2 (middle) and Fig. 2 (bottom).
VizSpark software fully support parallel capabilities using a domain decomposition approach. Fig. 3 compares the mesh and resulting temperature for the same simulation conditions using 1 core (serial) and 48 cores (parallel). Note that the results between the serial and parallel simulation are identical between demonstrating that there is no loss in correctness when using parallel vs serial.
Fig. 4 is a plot of the simulation speedup (strong scaling) for the 80,000 cell plasma torch problem for processor counts varying between 1 and 48. 8 times speedup can be obtained for 24 cores and 16 times speedup is achieved when 48 cores are used.
VizSpark Plasma Modeling Software Package is part of the Overviz framework suite which provides an intuitive interface to set-up a project to be solved using VizSpark, manipulate multiple projects for parametric studies. VizSpark is provably fast, robust, and easy-to-use software and currently a leading industrial plasma simulation tool.
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This example demonstrates charge-up of initially charge-free dust particles as they move through a pin-corona plasma. Two sets of particles move through the corona with different initial velocities. The dust particles are subject to Lorentz forcing in the electric field and their resulting trajectories are compared. The macroscopic particle dynamics is modeled in VizGrain and coupled to a background plasma solution modeled in VizGlow.
