Category: commercial vehicle

Soldier overseeing military drone while data streams in the background|Mapping of predicted anode potential|Virtual sensor estimating lithium plating|Virtual sensor estimating lithium plating risk in real time

Simulating Lithium–Sulfur Batteries for UAV Missions with GT-AutoLionSulfur

As industries push for lighter and more energy-efficient solutions, lithium–sulfur (Li–S) batteries are gaining increasing attention. Their appeal is clear: they offer the potential for much higher energy per weight than conventional lithium-ion batteries while using sulfur, an abundant and low-cost material. But while the promise is real, so are the challenges. Unlike lithium-ion batteries, […]

Read More
Electric Car EV charging station people charging in car port

Lithium Plating Detection: How Virtual Sensors Enable Smarter Fast Charging

Fast Charging Pushes Li-ion Batteries Toward a Hidden Risk Fast charging has become a defining requirement for modern electric vehicles and battery-powered systems. Users expect shorter charging times, consistent performance, and reliable operation under all conditions. For simulation, battery control, and engineering teams, this shift raises a shared challenge: predicting and managing internal battery risk […]

Read More
GT IS BLOG|Mild hybrid system model in GT-SUITE|||New pickup trucks on assembly line

When Agents Build the Model: Accelerating Digital Twins with GT Intelligence Studio

Why Building a Digital Twin Model Still Takes Too Long Our three-part series on physics-based digital twins followed a solar-charged, battery-powered Internet of Things (IoT) monitoring device. We covered the availability and battery-health questions that matter for operating it, how GT-SUITE and GT-AutoLion capture its physics and aging behavior, and how the model runs in […]

Read More
||Illustration of modularity|Geometry conversion of original CAD|furnace

Model Predictive Control with NARX Metamodels: Smarter Torque Requests for Fuel Cell Vehicles

As electrification expands across commercial fleets, engineers are rethinking power management to deliver efficiency, drivability, and robustness under real‑world conditions. By anticipating what the vehicle will need moments ahead, Model Predictive Control (MPC) reduces energy waste, smooths transients, and keeps the power source operating in its most efficient window. MPC paired with a dynamic, data-driven […]

Read More
Machine Deep learning algorithms

Combining Physics and Machine Learning to Predict Battery Aging with Confidence

Battery technology is evolving rapidly to meet the growing demands of electric vehicles, large-scale energy storage systems, and portable electronics. A major challenge lies in reliably predicting long-term battery performance within practical development timelines. Because batteries degrade gradually during both use and storage, conventional testing methods take a long time to produce accurate lifetime estimates. […]

Read More
Engineering Insights Blog|BMS|BMS|Tilt-Rotor Animation|Operational Window|VTOL|Simulation Result Summary Table|Flight Mission Profile|Simulation Results|Series Hybrid Tilt-Rotor Model Example in GT-SUITE|Comparison of steady and transient model response|IceFraction Animation|fuel cell bus|Schematic of water recirculation|System Workflow of a Series Hybrid Tilt-Rotor in GT-SUITE_01||Ice fraction near cathode catalyst layer||Routes Selected for System Level Simulation|2D flowfield in CAD

A Year of Engineering Insights: Our Top 7 Blogs You Shouldn’t Miss

From smarter thermal systems and next-generation batteries to digital twins, fuel cells, and advanced air mobility, we explored how engineering simulation is reshaping engineering decisions across industries. If you’re working at the intersection of innovation, performance, and efficiency, these seven blogs capture the most impactful ideas we shared in 2025, each addressing real-world engineering challenges […]

Read More
Virtual Calibration|BMS|BMS|Operational Window|Tilt-Rotor Animation|VTOL|Simulation Result Summary Table|Flight Mission Profile|Simulation Results|Series Hybrid Tilt-Rotor Model Example in GT-SUITE|IceFraction Animation|System Workflow of a Series Hybrid Tilt-Rotor in GT-SUITE_01|Comparison of steady and transient model response||fuel cell bus|Schematic of water recirculation|Ice fraction near cathode catalyst layer||Routes Selected for System Level Simulation|2D flowfield in CAD

Introduction to Virtual Calibration: A Smarter Approach to Powertrain Development

The Limitations of Conventional Calibration and Testing Testing and calibrating powertrains is crucial for product development yet traditionally requires years of work and millions in investment. Over time, requirements have expanded considerably to address regulatory compliance (OBD/emissions), customer expectations (efficiency), and manufacturer standards (reliability). Meeting these demands involves extensive physical testing through in-house facilities, on-road […]

Read More
Cutaway view of a Solid-State Battery module on black background. Next Generation Electric Vehicle Battery concept. Generic design. Isometric view. 3D rendering illustration.|fuel cell bus|IceFraction Animation|Schematic of water recirculation|Ice fraction near cathode catalyst layer|Comparison of steady and transient model response|2D flowfield in CAD

Solid-State Batteries: Why Virtual Modeling and Simulation are the Only Way Forward

Solid-State vs Lithium-Ion Batteries | What’s Driving the Shift The push for safer, longer-lasting, and higher-energy batteries is accelerating change across the energy storage industry. Solid-state batteries (SSB) are gaining attention as a promising solution to meet these growing demands. Unlike conventional lithium-ion batteries (LIB), which use flammable liquid electrolytes, SSB relies on solid materials, […]

Read More
fuel cell bus|||||Experimental validation of GT-AutoLion Na-ion battery model at different C-rates|Schematic view of Na-ion battery|Voltage vs. capacity for power-dense and energy-dense Li-Ion cells at different temperatures and C-rates|Multi-scale Modeling with Compular Labs and Gamma Technologies|Transport properties as a function of salt concentration|Schematic representation of the MD simulations|P2D model used in the GT-AutoLion tool|Molecular Dynamic Simulation|Digital Twin Simulation|Virtual Model using Digital Twin||Fault Detection on OBD_02||Data driven ML model|Engineers interacting with a virtual digital twin model on a tablet|Virtual model building|Data cleaning|Real time integration|||Digital Twin Image|Data collection|Cabin Comfort Model in GT-TAITherm|Digital Twin Orchestration Workflow|||||||||Figure 8. Simulation results of a single mission comparing two different battery designs. The Toshiba 20 Ah SCiBTM cells are arranged in 250S/170P (light grey) and 250S/142P (black).|||Table: Results of preliminary study on battery sizing for the tugboat application. Daily fuel consumption as a function of battery configuration.|||Toshiba GT-SUITE blog|Toshiba GT-AutoLion blog|||RDE AUTOMATION GIF|Unwrapped view of the RDE

Perfecting PEM Fuel Cell Water Management Strategies with GT-SUITE

The Rise of PEM Fuel Cell Technology in Mobility The origin of fuel cells dates back to the 19th century, but interest in the technology has surged over the past decade, especially within the mobility industry. This can be attributed to their ability to generate power without harmful emissions, similar to batteries, while also maintaining […]

Read More