4 Ways Simulation Can Accelerate Fuel Cell Development

In today’s fast-paced fuel cell industry, reducing time to market is both a strategic imperative and a competitive advantage. This 45-minute webinar will explore how system-level simulation is transforming the product development cycle — enabling engineering teams to virtually test and refine components, configurations, and control strategies long before physical prototypes are built.

Join this session to discover how a modern, advanced simulation platform can empower organizations to address critical challenges such as water and thermal management and long-term degradation. Learn how this technology is helping companies accelerate innovation, improve performance, and bring next-generation fuel cell systems to market with greater speed and confidence. An audience Q&A session will follow the technical presentation.

Join Jake How, our domain expert, along with Amanda Hosey, editor at SAE Media Group on September 08th, 2025, at 09:00 AM U.S. EDT to gain insights into how GT-SUITE is revolutionizing fuel cell development

 

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Soar to New Heights: Simulation-driven Design for Safety in Electrified Aircraft Systems

• Study potential drivers and scenarios of catastrophic safety events such as battery thermal runaway
• Analyze highly transient power-draw events like takeoff and landing with turbulent air wakes and the effect on aged battery state of charge, inverter-motor interactions, and more
• Investigate potentially catastrophic events like a motor failure in an eVTOL aircraft and its impact on other systems such as thermal management, other motors that will now have a higher power demand, etc.
• Explore the design and failure space effectively ahead of planning testing protocols
• Train fault-detection algorithms to the identify root cause of abnormal behaviors

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Techno-Economic Microgrid Modeling Workflow built on GT-SUITE

The growing complexity of energy systems demands smarter, faster, and more insightful microgrid design. Whether it’s enhancing energy resilience, integrating renewables, or optimizing costs, the key lies in a simulation platform that blends physical accuracy with economic intelligence—right from the concept stage.

In this webinar, we explore a cutting-edge, techno-economic microgrid modeling workflow built on GT-SUITE. The session will demonstrate how advanced system simulation can drive data-backed decisions for both technical feasibility and financial viability.

Our discussion will cover:

• ⚡ Actionable Techno-Economic Metrics: Real-time insights into ROI, CAGR, OPEX, CAPEX, LCOE, NPV, TCO, BEP, Renewable fraction, Emissions, Power-Split, Islanding and more… for data-driven decision-making
• 🌦️ Realistic Multi-Year Weather Modeling & Location-Specific Energy Insights: Integrated NASA POWER API enables high-resolution solar and wind data across multiple years—tailored to any latitude/longitude for reliable energy planning
• 🧠 Multiphysics & Multi-Fidelity Flexibility: Model subsystems using map-based/empirical, ROM or detailed physics-based approaches—scalable to your needs.
• 🧩 Modular Fidelity Switching: Easily toggle between low and high-fidelity models to balance simulation speed and accuracy.
• 🔋 Extensive Component Library: Includes validated and ready-to-use database of DG and battery (Li-Ion) for rapid prototyping at early stage in absence of data.
• 💡 Custom Logic Support: Customizable rule-based controls, including dynamic ToU (Time-of-Use) tariff modeling, incentive modeling (e.g., X2G – Microgrid-to-Grid, Vehicle-to-Grid, etc.), and policy-driven scenario planning. Energy Arbitrage logic – buy low (grid), sell/use high (storage), maximizing economic benefit. Power split optimization using Equivalent Consumption Minimization Strategy (ECMS).
• 📉 Optimization & Design Sizing: Optimize component sizing for minimum cost and maximum performance. Evaluate variability analysis for financial uncertainties.
• 📈 Visualization-Ready Outputs: Energy Flow Sankey Diagrams, Cumulative Energy Pie Charts for energy mix and Scenario Comparison with Radar/Spider Plots for visual decision-making and much more out-of-the-box.
• ⏱️ Lightning-Fast Simulations: Run long-term (multi-year) performance and aging simulations in just few minutes. Can also leverage distributed computing for large DOE.
• 🌐 Interactive Web Interface: GT-Play integration for interactive demos, stakeholder engagement, and remote evaluations – accessible anytime, from anywhere.
• 🤖 Full Workflow Automation: GT-Automations enables seamless preprocessing, model setup, execution, and results reporting – avoiding human errors.
• 🎯 Who Should Attend: Microgrid developers, energy consultants, CAEs, R&D teams, utilities, sustainability leaders, and planning managers seeking holistic techno-economic microgrid insights.

Join Ujjwal Chopra, our domain expert, on June 11th, 2025, at 15:00 (IST) to gain insights into how GT-SUITE is revolutionizing microgrid simulation with speed, accuracy, and economic intelligence

 

>>>>>Watch Recording<<<<<

How to Overcome Mechanical Challenges in Lithium-Ion Batteries with Multiphysics Simulation

The demands for higher energy density, longer cycle life, and faster charging in the automotive industry, are the pillars of Li-ion and beyond battery research. Interestingly, each of these pillars is closely linked to mechanical stress evolution in electrode materials.

Topic: How to Overcome Mechanical Challenges in Lithium-Ion Batteries with Multiphysics Simulation

Time: 09:00 AM EDT | 15:00 PM CET| 6:30 PM IST

This 45-minute webinar will demonstrate how advanced multiphysics simulation — that integrates electrochemical, mechanical, and thermal domains — can be leveraged to model and predict stress evolution and distribution across scales from individual, active material particles to the cell and module levels. This multiscale modeling approach enables a deeper understanding of physic degradation mechanisms, helps identify the root causes of mechanical failure, and supports decisions for designing more robust battery systems. An audience Q&A session will follow the technical presentation.

Speaker: Rohan Bokil, Staff Application Engineer

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How integrated system simulation is revolutionising vessel power generation & propulsion efficiency

Save the date for an engaging and insightful webinar “How Integrated System Simulation is Revolutionizing Vessel Power Generation and Propulsion Efficiency on LNG Carriers and Other Vessel Types” by Gamma Technologies and CLEOS, hosted by Riviera Maritime Media!

Date: May 15, 2025

Time: 14:00 BST | 15:00 CET | 09:00 AM EDT | 6:30 PM IST

Join us as we discuss

• The role of the digital thread in simulation.
• Integrated, physics-based modeling for maritime applications.
• An LNG carrier efficiency optimisation case study.
• Virtual commissioning benefits for vessel system performance.
• Optimising control strategies to enhance power generation efficiency.
• Sustainable solutions for vessel propulsion

Panellists:
George Pontikakos, Development Engineer, CLEOS
Dr. Haitham Mezher, EU Sales Director, Gamma Technologies GmbH, Germany
Michael Zagun, Application Lead for Mobility Systems and Integration, Gamma Technologies

 

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Live Online Training: GT-FEMAG E-Motor Design & Analysis

Gamma Technologies invites you to a comprehensive live online training session focused on the fundamentals of electric motor modeling. This two-day program is designed for engineers and technical specialists looking to enhance their understanding of electric motor design, analysis, and system integration using GT-FEMAG.

Participants will gain a practical introduction to electric machine modeling, with a strong emphasis on optimizing electromagnetic, thermal, and mechanical performance for e-motor projects. The course combines theoretical foundations with real-world applications to ensure a productive and engaging learning experience.

Dates: June 4-5, 2025
Format: Live, Online
Duration: 7 hours (spread across two days)

Key Topics Covered:

• Introduction to GT-FEMAG
• From Boundary Conditions to Motor Design
• Electric Motor Design Fundamentals
• Electric Motor Performance Analysis
• Comparative Study: IPM vs. EESM
• System-Level Integration Considerations
• IPM Design Optimization Techniques
• Challenge Session: BEV Motor Optimization

Why Attend?

• Learn directly from Gamma Technologies’ experienced professionals.
• Develop foundational skills in electric motor modeling.
• Apply best practices for optimizing motor designs for real-world applications.
• Participate in interactive sessions designed to reinforce key concepts.

 

Price: $1.000 

>>>>>Register for the live training<<<<<

Design and Optimization of Screw Machines in GT-SUITE using GT-SCORG

With the ever-increasing demands for improvements in screw machine performance and efficiency, engineers must optimize their designs. When selecting a design, it is important to consider not only the thermodynamic performance of the machine, but also the performance of the entire compressor system, including bearings, silencers, electric motors, and other components. 

GT-SUITE, a leading multi-physics simulation software, offers a one-stop, integrated software solution for screw compressor integrated multi-physics.

Join Doug Petrik from Gamma Technologies and world-renowned screw machine expert, Professor Ahmed Kovacevic from PDM Analysis, on May 20, 2025 to learn about: 

• Challenges faced during screw machine design 
• How to leverage GT-SUITE with GT-SCORG for rapid screw machine development 
• Screw machine multi-physics, including friction, NVH, and thermal management 
• Case studies using GT-SUITE for screw machine design and optimization

 

>>>>>Watch Recording<<<<<

Development of an HiL rig for the brand-new V16 Bugatti Tourbillon engine

Join Gamma Technologies for an Exclusive Look at the HiL Development of the New V16 Bugatti Tourbillon Engine

Hybrid powertrains are redefining performance in the hypercar segment—combining zero-emission driving with extreme engine capabilities. But with this innovation comes complexity, especially in control system development. As the number of degrees of freedom increases, so does the need for advanced tools to validate, calibrate, and refine control strategies. 

In this webinar, Bugatti-Rimac’s Science and Model Integration Manager, Giulio Boccardo, and GammaTech Engineering’s Luca Cambriglia will showcase how a GT-SUITE real-time engine model was developed and integrated into a modular Hardware-in-the-Loop (HiL) testing platform for the groundbreaking V16 Bugatti Tourbillon engine. From physical model reduction to real-time deployment on a dSPACE SCALEXIO system, you’ll get an inside look at how predictive simulation enables faster, safer, and more precise ECU development.

What You’ll Learn:

• How the GT-SUITE V16 Tourbillon engine model was reduced for real-time simulation and adapted into 4- and 8-cylinder configurations
• The integration process with a full-vehicle Simulink model and deployment on a dSPACE SCALEXIO HiL simulator
• Performance insights from closed-loop HiL testing and the benefits of using a physically predictive engine model for ECU validation

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A Guide to Electrified Aircraft Systems Sizing: ePowertrain, TMS, and ECS Analysis

This 45-minute webinar will introduce a physics-driven approach to simulate electric airplane systems — specifically looking at full-electric setups with several power supplies — which allows for the dimensioning and preliminary design of ePowertrain, thermal, and hydrogen subsystems to enhance performance across different mission profiles and environmental conditions. The session will explore advanced simulation software’s ability to analyze how various parameters affect system behavior.

The program will dive into the approach including changing the setup of batteries, the features of fuel cell stacks, and the key parameters of the e-Powertrain thermal management system (TMS). Finally, attendees will learn how the modeling capabilities of the environmental control systems (ECS) are presented and integrated into the full aircraft model.

Key performance indicators examined:

Powerplant’s ability to meet immediate power demands, considering restrictions of batteries and fuel cells
Reduction of the amount of energy consumed under the specified operational circumstances
Regulating temperatures of the ePowertrain components and within the cabin
Evaluation of thermal comfort of the passengers

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Bridging Physics and Machine Learning: NVH Optimization in the Early Stages of Electric Motor Design

The electric motor is a key source of noise in an electric powertrain. Effective Noise, Vibration, and Harshness (NVH) management requires advanced and integrated simulation techniques to identify and mitigate noise and vibration early in the design process. This ensures that electric motors not only deliver optimal performance but also enhance the driving experience with smooth and quiet operation.

In this webinar, we explore how the integration of physics-based simulations and machine learning can optimize NVH at the early stages of electric motor design. Our discussion would be covering the following

• A Complete Integrated Multiphysics Simulation: Electromagnetic analysis of e-motors with consideration of spatial harmonics, inverter design including switching frequency, and vibroacoustic analysis at microphone location.
• Use of Machine Learning: Utilizing GT-SUITE`s in-built Machine Learning Assistant for performing Pre-CAE approach for NVH consideration in early motor design.
• Industrial Use-Case: Highlighting a real-world case study which showcases significant reduction of design cycle time for e-NVH analysis using GT-SUITE.

📅 Join Vinit Kumar and Nakul Joshi on April 16, 2025, at 15:00 IST to gain insights into cutting-edge methodologies that bridge physics and machine learning, advancing electric motor design.

>>>>>Watch The Recording<<<<<

Rising Star GT Brazil Webinar – Complete Vehicle Thermal Management

On Tuesday, April 29th, at 9 AM BST, Gamma Technologies’ Brazil and Rising Star’s own Marcus Bittar will give a live webinar on “Complete Vehicle Thermal Management”

Link to watch and register

• Learn how to streamline the design process of thermal management systems for electric vehicles, optimizing their efficiency and range
• Leverage virtual testing and HiL simulations to validate thermal management solutions without physical hardware.
• Discover how virtualizing vehicle design and testing streamlines decision-making, cuts costs, and speeds up development.

Please note that the webinar will be hosted in Portuguese.

Rising Star GT Brazil Webinar – Machine Learning for Multi-physics Automotive Simulation

On Tuesday, April 8th, at 9 AM BST, Gamma Technologies’ Brazil and Rising Star’s own Marcus Bittar will give a live webinar on “Machine Learning for Multi-physics Automotive Simulation”

Link to watch and register

This webinar will delve into how machine learning enhances battery modeling and vehicle system simulations, enabling faster, more accurate predictions and improved system optimization. Please note that the webinar will be hosted in Portuguese.

1D and 3D Integrated Design of a Compressor for a Fuel Cell Powered Heavy Duty Truck

Decarbonisation of heavy-duty vehicles has an important impact on reducing emissions. More specifically, in the United States, medium and heavy-duty trucks are responsible for 23% of total CO2 emissions at present. Furthermore, the annual road freight traffic is expected to grow by 54% by 2050. The recent growth in lithium-ion battery use in Light Duty Vehicles (LDV) has resulted in reductions of battery costs. However, for Medium and Heavy Duty (MDV and HDV) applications, fuel cells offer important advantages in terms of energy density and refuelling time, which makes this technology more attractive for these classes of vehicles. Recent US Department Of Energy targets for Class 8 long haul trucks highlight the importance of even longer driving ranges and increased efficiency demands for fuel cell systems. To this end, it is important to design and optimize the components of a fuel cell system not in isolation. Components, such as the compressor, must be evaluated as part of the integrated system, under real-driving conditions, thus capturing the strong co-dependencies among subsystems and the intricacies of real-life operation.

This joint webinar by Advanced Design Technology and Gamma Technologies presents a novel methodology that uses a system-level simulation platform (GT-SUITE) to create a complete vehicle model and simulate the performance of a fuel cell powered truck in order to obtain the key compressor operating points (together with the resulting residence time spent on each point based on real driving conditions). The key compressor operating points are then fed into TURBOdesign Suite’s meanline compressor design optimization code which uses a map prediction model for a range of compressor speeds, impeller diameters, hub diameters and axial length ratios to find the optimum settings that meet the same weighting factor obtained from real driving conditions.

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This initial flow path and design conditions obtained from the mean line design optimization are then used by a 3D Inverse design method (TURBOdesign1) to generate an initial 3D impeller geometry. Automatic optimization is then used to optimize the impeller geometry. The casing is also designed by using a unique inverse design method (TURBOdesign Volute) and the performance of the resulting stage is computed by using a 3D CFD simulation package. Furthermore, the structural integrity of the compressor is analysed with a 3D structural analysis software package. The resulting full stage compressor map is then fed into the system-level model and the impact of the new design on the energy consumption over the actual real-life driving scenario is assessed and analysed. The methodology highlights the importance of rigorous simulation as a means for improving component performance and system efficiency, while reducing time-to-market and thus development costs.

Rising Star GT Brazil Webinar – Using a Holistic Approach for Integrated Optimization of Electric Powertrains

On Tuesday, March 19th, at 9 AM BST, Gamma Technologies’ Brazil and Rising Star’s own Marcus Bittar will give a live webinar on “Using a Holistic Approach for Integrated Optimization of Electric Powertrains.”

Link to watch and register

Learn more about the simulation methodology for exploring the design space of batteries, motors, and inverters within electric powertrains! You’ll not only learn about these components and their component-level trade-offs, but you’ll also learn about their complex effects on system-level performance.

Rapid and Automated Simulation Platform for Engine Models to Manage Complexity and Lower Costs

Presenters:

Alessandro Zanelli | WinGD, Pre-Sales Manager, Integrated Energy Solutions

Emanuele Servetto | GammaTech Engineering (expert services division of Gamma Technologies), Senior Manager, Engineering Services and Operations

Time:

14:00 CET (Berlin/Paris) | 09:00 EDT (New York City)

>>>>>Register for the webinar<<<<<

Leveraging Simulation for Net Zero Emissions in Conventional and e-Fueled Combustion Systems

The transportation sector faces unprecedented challenges in achieving net zero emissions targets due to continuously rising environmental concerns. This 45-minute webinar explores computer-aided engineering (CAE) solutions for the intelligent design of innovative, eco-friendly systems for achieving net zero emissions. This program will propose a framework for optimized design of emissions mitigation technologies — by integrating high-fidelity, multi-physics digital twins — applicable for all types of powertrains including exhaust aftertreatment of conventional and e-fueled combustion systems, CO2 capture and utilization, and SOx emissions reduction. This is webinar is hosted by SAE.

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Costas Kotoulas, Ph.D.
Senior Staff Application Engineer
Gamma Technologies

Dr. Costas Kotoulas serves as a Senior Staff Application Engineer for Reactive Flow Systems at Gamma Technologies. He has more than 13 years of experience in exhaust aftertreatment innovation. Costas holds a Ph.D. in chemical engineering from Aristotle University of Thessaloniki and master in economics from University of Macedonia, Greece.

 

Dominik Artukovic
Staff Application Engineer
Gamma Technologies

Dominik Artukovic is a Staff Application Engineer for Reactive Flow Systems at Gamma Technologies. He holds a master’s degree in process engineering from the University of Stuttgart.

Menelaos Zafeiridis
Senior Staff Application Engineer
Gamma Technologies

Menelaos Zafeiridis serves as a Staff Application Engineer for Reactive Flow Systems at Gamma Technologies. He holds a master’s degree in mechanical engineering from Aristotle University of Thessaloniki.

GT-SUITE For Increased Robustness of Fault Detection

In this webinar, presented by Gamma Technologies’ own Nils Framke (Principal Engineer, Product & Apps Strategy) talks about the advancements in fault detection and predictive maintenance for complex physical systems in the era of Industry 4.0.

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With the vast amount of data available today, there is a growing potential to effectively predict and prevent issues in industrial machinery. Multi-physics simulation models of reciprocating compressors as part of Digital Twin Environments have advanced significantly, thus allowing for the quick and easy generation of synthetic training datasets and specific labelled anomalous datasets simulating real-world faults.

Nils talks about a well-known commercial multi-physics simulation software, GT-SUITE, that is used to model an industrial reciprocating compressor system with various domains including bearings, valves, compressor shaft mechanics, NVH, lubrication, and gas flow dynamics. The model is exercised with variability of typical physical parameters to simulate real-world operation of well-running, non-faulty reciprocating compressor systems and generate “no-fault” virtual input datasets. Faults are then intentionally introduced within the digital twin system to simulate real-world anomalies manifested via behavioral changes in signals of typical sensor data (e.g., compressed gas pressure) present in actual compressor systems. Supervised learning techniques are applied to train and optimize machine learning models for fault detection. The trained models can be deployed in real-world scenarios with online real-time monitoring to detect potential failures and identify fault causes. This can help with predictive maintenance of compressor systems, reduce unscheduled downtime, and thereby decrease the economic impact from loss of production.

The promise of such technology is demonstrated as the ability to reproduce and prevent faults without actually creating them on a real machine, which would risk severely damaging these large and expensive machines.

Overall, this webinar will demonstrate the promise of technology in reproducing and preventing faults without risking damage to expensive machinery.

Multi-Physics Integration of Mechanical Systems

A common trend observable across multiple industries is increasing system complexity coupled with tighter performance and efficiency demands. Meeting these requirements and exceeding customer expectations requires a reevaluation of long-standing processes and in certain cases, a shift from stand-alone design and simulation. To achieve the optimal product and avoid costly iteration loops, complex interactions between various physics domains need to be understood and accounted for as early as possible in the design process. As the leading multi-physics system simulation tool, GT-SUITE offers streamlined capabilities to easily couple multiple domains in one model. This webinar will showcase some of the available options of integrating mechanical system models with other domains within GT-SUITE.

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Topics covered include integration of mechanical models with GT-POWER, scroll compressor fluid-structure-interaction, and electrochemical-mechanical battery swelling. This webinar was presented live by Gamma Technologies’ own Ashwin Henry (Application Engineer, Mechanical Systems) as well as Marcel Schmädicke (Applications Engineering Manager, Mechanical Systems) in another live session.

Testing Heat Pump System Retrofitting in GT-SUITE

In this webinar, presented Gamma Technologies’ own Arne Heinrich (Senior Application Engineer, Thermal Fluid Systems), a heat pump with propane is presented as designed using GT-SUITE, based on an existing system with R410A. An attempt is made to preserve the majority of the existing components.

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Driven by regulatory requirements, alternatives to classic refrigerants must be found. Propane is a promising alternative for running a heat pump. This can be seen, among other things, in the fact that at the beginning of this year the European scientific community spoke out in favour of propane in a position paper, as well as last year’s breakthrough by the Frauenhofer Institute to develop a propane-based heat pump with a load of less than 150g and a heat output of 12.8kW.

Multi-Physics Simulation For Electrolysis and H2 Development

In order to fully transition to a carbon-neutral society, large amounts of hydrogen will be needed. This entails the need to develop sustainable ways to produce, store, and dispense hydrogen to meet the demands of a constantly growing market. Especially in industries such as steel manufacturing or chemical processes, the transition to hydrogen is crucial for achieving carbon neutrality. Additionally, considering the potential demand from transportation sectors, especially heavy-duty, marine, or aerospace, the required amount of hydrogen is orders of magnitude higher than what is currently produced. Electrolysis is the only genuinely green method of producing hydrogen. Understanding the entire system from the stack to the system level requires integrated multi-physics simulation.

This webinar will highlight the capabilities of GT-SUITE in this area. Additionally, applications in other aspects of the necessary hydrogen infrastructure, such as fueling stations and storage, will be showcased.

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This webinar is presented by Gamma Technologies’ own Thomas Vevaud (Senior Application Engineer, Reactive Flow Systems).

Automated Optimization of Two-Phase Compressor System in GT-SUITE

In this webinar, presented by Gamma Technologies’ own Nils Framke (Principal Engineer, Product & Apps Strategy) talks about how in heat pump systems operating with high-pressure ratios and extended environmental conditions, vapor injection compressor systems are used to increase the system coefficient of performance (COP) and lower the operating expenditure.

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Such systems consist of a two-stage throttling process in which injection gas for the compressor is provided via an internal heat exchanger or a flash tank. To maximize COP further, such heat pump systems offer multiple opportunities for optimization ranging from matching of an existing compressor to a specific heat pump system over compressor design modifications to expansion control strategies.

Exploring the large design space that can be available to improve the overall system performance is only feasible utilizing simulation considering economic constraints. Often simulation tools focusing only on the macroscopic system performance are steady state and driven by empirical correlations and measurement data or focus on the compressor unit only. This approach however neglects possible dynamic system and compressor interactions that could lead to performance diminish.

This holistic system optimization methodology can be implemented in the commercial simulation software GT-SUITE. In this study, a transient capable, detailed 1D scroll compressor model is integrated with a transient system model to demonstrate the capability of simulation methodology for the optimization of vapor injection heat pump systems. The developed model is compared to currently available empirical models to investigate the benefits of the proposed methodology.

Mastering Thermal Runaway in Virtual Development

In this webinar, presented by Gamma Technologies’ Yogesh Nalam (Senior Application Engineer, Thermal Fluid Systems), we will explore two different battery cooling methods, cold plate and immersion cooling, and address the challenges of thermal runaway through numerical simulations.

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Thermal runaway is a complex 3D multi-physics issue that demands significant computational resources. Hence, we aim for both accuracy and speed in our solutions. A synergetic 1D-3D modeling approach is implemented to reduce the simulation time. Pseudo-two-dimensional (P2D) electrochemical battery models along with chemical kinetics model derived from Arrhenius equations are used and coupled to the thermal and flow domain to predict three different phases of thermal runaway, namely, initiation, ignition, and propagation. Chemical reactions causing thermal runaway, including heat generation and venting gas phenomena, are incorporated into GT-AutoLion, a battery simulation tool in GT-SUITE. In certain extreme conditions, thermal runaway triggered in one cell can spread to others, depending on the cooling method. Cold plate cooling tends to propagate thermal runaway, while immersion cooling contains it. In summary, the presented simulation strategy was found to be effective in choosing and designing the right cooling concept from the safety point of view.

Fuel Cell Fault Simulation and Detection for OBD using Real-Time Digital Twins

Watch the webinar “Fuel Cell Fault Simulation and Detection for On Board Diagnostics using Real-Time Digital Twins ” presented by Gamma Technologies’ own Christian Altenhofen and Pantelis Dimitrakopoulos.

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About the webinar: The modern automotive industry is facing challenges of ever-increasing complexity in the electrified powertrain era. On-board diagnostic (OBD) systems must be thoroughly validated and calibrated through many iterations to function effectively and meet the regulation standards. Their development and design process is more complex when prototype hardware is not available, and therefore virtual testing is a prominent solution, including Model-in-the-loop (MIL), Software-in-the-loop (SIL), and Hardware-in-the-loop (HIL) simulations. Virtual prototype testing, relying on real-time simulation models, is necessary to design and test new era’s OBD systems quickly and on a large scale. The new fuel cell powertrain involves new and previously unexplored failure modes. To make the system robust, simulations are required to identify different failures. Thus, it is imperative to build simulation models that can reliably reproduce failures of components like the compressor, recirculation pump, humidifier, or cooling systems. As OBD regulations become more stringent and advanced, it is challenging to keep pace and perform comprehensive testing in real-world environments. In such scenarios, MIL, SIL, and HIL testing become more prevalent. MIL and SIL testing provide a quick way for control engineers to develop new strategies at the system level to adhere to new OBD regulations. On the other hand, simulating high-fidelity physics-based Real-Time plant models on HIL systems allows engineers to perform fault insertion tests on the software and leave the lab environment with a certain degree of guarantee that the software would perform well in real-world conditions. This webinar will present the necessary fuel cell model developments to reproduce relevant failure modes, which in turn can be detected by a control model developed in Simulink. Then the viability of this approach will be demonstrated by showing MIL and HIL test results.

Function Development with Thermal Management Plant Models

This webinar, presented by Gamma Technologies’ own Sagar Kulkarni (Senior Engineer, Application Engineering | Thermal Management), investigates methods aimed at streamlining complex thermal management models of battery electric vehicles (BEVs). A high-fidelity model of a BEV is used, featuring detailed thermal representations of components and several cooling, chiller, and AC circuits. The focus is on reducing runtime while finding the right compromise with accuracy and predictivity.

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From an initial high fidelity model that runs significantly slower than real-time, multiple guided approaches were applied to facilitate a robust reduced order modeling approach. First by transitioning from 3D to 1D thermal modeling for the motor and coolant plate and then simplifying flow systems; the runtime is reduced to faster than real-time. This fast-running model maintains accuracy while making it suitable for HiL testing.

Finally, by implementing a unique parallel threading approach and splitting the integrated model into parallel sub-models running on multiple cores, real-time execution on HiL systems is achieved. This approach enables efficient testing and validation of thermal management systems without compromising accuracy.

In conclusion, this study highlights the successful development of a fast-running model for complete vehicle thermal management. It simplifies complex models, accelerates runtime, and enables HiL testing, offering a cost-effective and accurate approach for xEV development.

Leveraging Marine Propulsion System Through Multi-Physics Simulation

This webinar, presented by Gamma Technologies’ own Michael Zagun (Staff Application Engineer, Mobility & System Integration) and Thomas Vevaud (Senior Application Engineer, Reactive Flow Systems), highlights the multi-objective optimization of a fuel-cell powered in-harbor tugboat propulsion under selected duty cycle and weather conditions.

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The dynamic and forward-facing multi-physics simulation model integrates a physics-based fuel cell/balance of plant (BOP) model and an electrical-equivalent energy storage (ESS) model offering realistic response dynamics. The optimal control solution, which is based on ECMS utilizes a kinematic backward-facing propulsion system model considering the system dynamics and constraints. The proposed modeling approach exploits the fuel-saving potential of each system design variant and thus offers significant design and workflow improvement.

ePowertrain Vehicle & Controls Integration

In this webinar, presented by Gamma Technologies’ own Milan Cvetković (Senior Application Engineer, Mobility & System Integration) and Pantelis Dimitrakopoulos (Staff Application Engineer, Mobility Systems & Integration) explores the challenges and opportunities associated with the integration of a full e-Powertrain into a fuel cell truck, focusing on the seamless coordination of various components such as electric motors, batteries, inverters, and onboard control systems, featuring simulation tools GT-FEMAG, GT-AutoLion as well as GT-PowerForge respectively.

Key considerations include optimizing energy efficiency, enhancing vehicle performance, ensuring safety, and addressing regulatory requirements. Effective integration involves not only the physical placement of components within the vehicle but also the development of sophisticated control algorithms that manage power distribution, torque delivery, regenerative braking, and other critical functions.

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Key aspects of this webinar include:

• Overview of E-Powertrain
• Integration Challenges
• Vehicle Dynamics and Performance
• Control Strategies
• Safety and Reliability

Machine Learning for Fast, Integrated Battery Modeling

In this webinar, presented by Gamma Technologies’ own Massimiliano Mastrogiorgio (Senior Application Engineer, Electrical Systems • Battery Systems), we discuss machine learning techniques to develop efficient and comprehensive battery models, including thermal aspects. We will showcase how machine learning algorithms are employed to capture complex battery behaviors quickly and integrate them into vehicle system models. Yet undoubtedly fast and accurate battery models are important for various applications such as electric vehicles, renewable energy storage, and portable electronics. Additionally, it may highlight the potential benefits of integrating machine learning into battery modeling processes, such as improved prediction accuracy, reduced computational time, and enhanced system optimization capabilities.

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Key Aspects are:

• Accuracy: Highlighting how machine learning techniques can enhance the accuracy of battery models by capturing complex behaviors and dynamics
• Flexibility: Discussing the flexibility offered by machine learning approaches, which can adapt to different battery chemistries, operating conditions, and applications
• Scalability: Addressing the scalability of machine learning-based battery models, enabling them to handle large datasets and complex systems efficiently
• Real-time Capability: Emphasizing the ability of machine learning models to provide real-time predictions and insights, enabling rapid decision-making and control in dynamic operating environments

In a nutshell: Machine learning enables fast, accurate, and adaptable battery modeling solutions that are well-suited for real-world applications across various industries.

Achieving Sustainable HVACR Innovation with Simulation

The HVACR industry is undergoing a transformation. With evolving regulations, increasing competition, shorter design cycles, and the need to minimize costly and time-consuming physical testing, Copeland turned to advanced simulation technology to meet these challenges head-on.

Discover how scroll compressor mechanical modulation and HVACR system optimization are driving sustainable HVACR solutions through cutting-edge simulation, guided by the expertise of Copeland and Gamma Technologies.

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Key Insights: (more…)

Using Simulation for Real-Time Predictive Battery Modeling for State Estimation and Control

Lithium-ion batteries (LIBs) play a vital role in the advancement of electric vehicles and sustainable energy solutions. They are favored over other secondary energy storage systems due to their high energy density, long cycle life, high nominal voltage, and low self-discharge rate. However, the latency of LIBs’ internal states makes it difficult to predict their performance and ensure they are being operated safely. Fortunately, battery management systems (BMS) can use battery models to predict the internal states of a battery. This webinar explores:

• How to manage trade-offs between accuracy and computational costs for battery management systems (BMS)

• How a digital twin framework can capture the accuracy of high-fidelity electrochemical models while meeting the computational constraints imposed by the BMS

• How this can be achieved using a lower-fidelity model in real-time to accurately predict slower dynamics such as the state of health and more dynamic states such as voltage, temperature, and state of charge

Speakers:
Pantelis Dimitrakopoulos, Staff Application Engineer – Mobility Systems and Integration, Gamma Technologies
Nikhil Biju, Staff Application Engineer, Gamma Technologies

Machine Learning for Multi-Physics Automotive Simulation

Undoubtedly, fast and accurate battery models are crucial for various applications such as electric vehicles, renewable energy storage, and portable electronics. Machine learning techniques offer the ability to develop efficient and comprehensive models for automotive simulation including batteries and their thermal aspects. This 45-minute webinar explores how to use machine learning to develop these more efficient models as well as showcase how machine learning algorithms are employed to quickly capture complex behaviors and integrate them into vehicle system models. Additionally, the program will highlight the potential benefits of integrating machine learning into battery modeling processes such as improved prediction accuracy, reduced computational time, and enhanced system optimization capabilities. Topics include:

• How machine learning techniques are used to develop efficient, optimized vehicles

• How machine learning algorithms can capture complex battery behaviors quickly and integrate them into vehicle system models
• How integrating machine learning into engineering processes can lead to improved prediction accuracy, reduced computational time, and enhanced system optimization capabilities

Speaker: Massimiliano Mastrogiorgio, Senior Battery Application Engineer, Gamma Technologies

Using a Holistic Approach for Integrated Optimization of Electric Powertrains

Batteries, motors, and inverters make up the essential trio of any electric powertrain, and each of these has a significant impact on the cost, range, efficiency, and performance of an electrified vehicle. Too often, though, these components are designed and optimized separately, instead of being optimized together, as a system.

In this 45-minute Webinar, Gamma Technologies’ own Joe Wimmer (Senior Applications Engineering Manager, Electrical Systems) presented a methodology for exploring the design space of these components while understanding not only the component-level trade-offs, but also their complex effects on system-level performance.

NVH Prediction in Electric Powertrains: Considering Inverter and Motor Spatial Harmonics

Much time and consideration from automotive engineers goes into analysis of noise, vibration, and harshness (NVH) since consumers expect their vehicles to provide as quiet and smooth a ride as possible. Modern technological advancements provide a multitude of opportunities to maximize design success in this area.

In this 30-minute Webinar, Gamma Technologies’ own Greg Fialek (Applications Engineering Director, Mechanical Systems) and Joe Wimmer (Team Lead, Electrical Applications) demonstrated a multi-physics workflow for capturing the NVH coming from electric powertrains. This included electromagnetic, electrical, mechanical, and acoustic modeling to capture the effects of spatial harmonics of the traction motor, harmonics of the inverter and its controls, and bearing and housing design on acoustic performance of electric powertrains.

Combining 1D and 3D Multi-Physics Modeling Methods for Thermal Runaway Propagation Analysis

Thermal runaway propagation is a key safety challenge when designing a battery system, but studying thermal runaway events at the pack-level has historically heavily relied on expensive pack-level experimental tests using prototype batteries or 3D CAE analyses. Because the cost of a single test in either scenario is very high, both options allow for only a handful of scenarios to realistically be studied. Empirically driven heat predictions do not account for the history of cells leading to their thermal runaway events. In this 60-minute Webinar, attendees will learn how to build a predictive model for thermal runaway propagation using the new capabilities of advanced simulation tools.

Topics include:
🔋 Electrochemical modeling of battery cells
🔋 Thermal runaway reactions in individual cells
🔋 3D finite element thermal simulation
🔋 Integrated modeling for runaway propagation

Accelerating Maritime Electrification through Battery Digital Twin Simulation Solutions

This webinar was organized and hosted in cooperation with the Maritime Battery Forum, Gamma Technologies and Toshiba to introduce the concept of a digital twin model of Toshiba’s SCiB cell. The model is based on a GT-AutoLion electrochemical physics predictive solution, and it’s shown how it can be integrated into the GT-SUITE’s multiphysics system simulation platform. The possibility of evaluating the cell performance during a typical operating day of a battery electric harbor tugboat will be highlighted including recurring fast charging events.

Some of the highlights include;

•Introduction to Toshiba SCIB cell digital twin electrochemistry physics predictive model

•Introduction to GT-SUITE and GT-AutoLion

•Multiphysics system integration and battery performance investigation

•How Multiphysics systems simulation can help accelerate the development of maritime batteries application

Building a Lithium-Ion Cell Electrochemical Model Using GT-SUITE

Advanced electrochemical modelling and simulation of Li-ion cells can substantially benefit in the design of a battery cell/pack for EV and stationary applications. Creating a highly accurate virtual cell that incorporates complex electro-chemical phenomena for performance, ageing, and safety studies of battery cells/packs can be challenging.

Attendees joined us for this interactive webinar to learn how to build a cell model from scratch or reverse engineer a cell using the least amount of cell testing data possible to model li-ion cell behavior under various operational conditions. During the live Q&A session, attendees also asked questions.

Key Discussion Points:

• How to build an electrochemical cell model if you are cell manufacturer?
• How to reverse engineer a li-ion cell if you are an OEM who procures cells from a supplier?
• What are the best practices of cell reverse engineering?
• What data one requires for cell reverse engineering?
• How this virtual cell can be useful in designing a battery pack for various applications?

Addressing Challenges of Fuel Cell and Electrolyzer Development using System Simulation

Addressing the Challenges of H2 ICE using System Simulation

Gamma Technologies had organized a webinar on, “Addressing the challenges of H2 ICE using system simulation” on 30th Nov 2022 at 3 to 4 pm IST. Our experts, Mr. Kai Gaukel, from our Stuttgart office and Mr. Hitesh Chaudhari from our India office, presented the solution we provide to the challenges faced by engineers working in the hydrogen ecosystem for internal combustion engines [ICE]. Our experts discussed the robust solution for port H2 injection and direct H2 injection engine configurations, lean combustion systems, dual fuel (diesel+H2) configurations, predictive combustion modeling, laminar flame speed and knock models, and others. We also gave highlights on fuel cell electric vehicle [FEV] simulation and discuss some of the user case studies on H2 ICE from our recent US and European GT Technical Conferences [GTTC] held this last month.

Hydrogen is gaining traction for internal combustion engines and electrification systems. OEMs are working on the development of the right solutions to reduce the carbon footprint of the existing ICE ecosystem. Dr. Sunil Pandey  and  Mr. Sai Kiran A.  from  Ashok Leyland co-presented the use of system simulations for H2 ICE development for heavy duty vehicles. We also had some time reserved for a Q&A session with our experts.

Topics included:

• Challenges with hydrogen ICE simulation 
• Solutions offered by Gamma Technologies
• Overview of use cases from recent US and European events
• Case study by industry on H2 ICE simulation

Unlocking the Next Generation of High-Performance Battery Systems

Driving the Design and System Interaction of Pumps and Compressors with Integrated 1D/3D Simulations

Implementing Virtual Engine Calibration to Speed Up your Development Process

Accelerating Electrified Aircraft Development with Multi-Physics Simulation

Balancing Range and Occupant Thermal Comfort for Mass Transit Applications

The relationship between vehicle range and occupant comfort is an important consideration for EVs. Effective HVAC controllers are critical for maintaining the optimum occupant comfort while preserving vehicle range. Maintaining occupant comfort is more challenging for commercial vehicles; where the vehicle is large and has many occupancy configurations. Watch this video to learn how you can accurately simulate this tradeoff using a coupled transient simulation with TAITherm and GT-SUITE.

Turbocharger System Integration with AxSTREAM and GT-POWER

In many engine boosting applications, a third-party turbocharger needs to be integrated into a powertrain and the respective GT-POWER engine models. The challenge is that turbocharger map data is not always available for all scenarios and maps are often extrapolated/interpolated to provide usable inputs into engine system models. These assumptions often lead to unreliable off-design performance predictions from data that is not supplied by the vendors. But what if you could generate any performance map for a turbocharger from the existing wheel or re-generate geometry if you do not have any wheel geometry available?

In this seminar, attendees learn how to reverse engineer any turbocharger from existing geometry and predict its performance at any operating point using AxSTREAM. Attendees are walked through the steps of how to extract blade profile information and produce complete performance maps for a given machine at off-design points. We also show how you can re-generate and explore flow path geometry options if you do not have wheel geometry available and create performance maps that better satisfy your engine model requirements. Finally, we show how the performance maps generated from AxSTREAM can be directly integrated into GT-POWER for complete engine modeling. By the end of the seminar, attendees will have a strong understanding of how to: reverse engineer a turbocharger; predict performance maps for use in system simulations; and evaluate the effects of design modifications to the blade geometry on the performance map.

This seminar shows a live demonstration of the workflows in AxSTREAM and GT-POWER to perform turbocharger integration.

This session will include:

• Reverse engineering of turbochargers from existing geometry (CAD or measured)
• Reconstructed blade geometry from preliminary design solver (NO input geometry required!)
• Performance Map predictions
• Integration of generated performance maps in GT-POWER
• Design modifications to achieve desired performance maps
• 1-month trial license for the software used in this workshop. Restrictions apply. Contact [email protected] for details

Improving xEV Thermal Management System Design by Utilizing AC and Cabin Simulation in GT-SUITE

In this webinar, the optimization of a xEV  thermal management system design will be presented, with the focus on utilizing AC and cabin simulation within GT-SUITE. The motivation is to show the impact of the optimization not only on the AC system and the cabin itself, but also to look at the big picture: how will the changes to the AC system effect the xEV´s total range, SOC and human comfort? A dedicated example will be presented during the webinar showcasing a full xEV built within GT-SUITE. Additionally the potential of optimization of such models will be shown.

Topics included:

• Brief introduction to the model building workflow in GT-SUITE
• Demonstration of a full xEV example model
• Full tour through Case Setup and DOE Setup

How to Perform Battery Aging Analysis with GT-AutoLion

Simulation provides an excellent method to gain insight into battery aging. In this webinar, you will learn how to utilize GT-AutoLion and GT-SUITE to predict battery degradation. We walk through multiple examples to provide information on a wide variety of use cases.

Topics include:

• Extrapolating beyond measured data
• Predicting how batteries will degrade in the real-world scenarios by integrating physics-based aging models with other systems
• Predicting the performance of an aged battery
• Understanding the influence of charging strategies on battery degradation
• Virtual calibration of charging controls

GT-SUITE for Hydrogen Mobility: Storage, Fuel Cell Systems, Combustion & Vehicles

Hydrogen is emerging as a promising fuel due to its light weight, ability to be produced by renewable energy, and lack of emissions. It can be used to power a fuel cell in various transportation applications (electric vehicles, marine, aerospace) or power generation applications and as combustion fuel for reciprocating engines and turbines.

In this webinar, you will learn how GT-SUITE can be applied to design, analyze, and validate various hydrogen systems. Topics include:

• Designing a hydrogen station and storage systems to ensure quick and thermally stable tank filling
  Calibrating a predictive fuel cell stack model for accurate, transient simulation
• Designing fuel cell system components and controls to optimize performance and range for an EV application
• Predictively modeling hydrogen combustion in an engine model
• Integrating propulsion systems in a vehicle model for optimization of power management strategies and fuel consumption

Key Considerations to Understand and Maximize Battery Life

Across many industries, more and more companies are utilizing batteries as the primary source of energy for their products. When designing these products, one of the most important tasks is predicting and maximizing battery life to inform decisions on product warranty and create added value for customers.

In this webinar, you’ll learn about the key factors to predict and maximize battery life. Topics include:

• Reducing testing time and cost with simulation
• The benefits of physics-based battery modeling
• Predicting performance of a new and aged battery cell
• Integration with other systems to understand their impact on each other, such as the influence of thermal management on battery life and the influence of battery power on thermal management
• Utilizing simulation to predict range, performance, heat rejection, etc.
• The influence of charging strategies on battery life

Predicting Vehicle Behavior in Real Life Scenarios with GT-RealDrive

Custom Python Scripting with GT-Automation

GT-SUITE Model Setup and Post-Processing Tips

This 30-minute webinar is filled with useful tips for efficient model setup and post-processing.

Topics include:

• Case setup tips, including how to create super parameters
• Output setup options
• Advanced setup options
• Post processing map modes for better data visualization
• Using result files for data management
• Python scripting with GT-Automation
• Macros for improved data handling