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, […]
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 […]
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 […]
Most hybrid powertrain programmes commit to an architecture too early. A configuration that looks promising on paper can fall apart once you account for towing loads, payload constraints, and real-world drive cycles simultaneously. By that point, hardware has been ordered and timelines are fixed. FEV North America took a different approach. Working with a 4WD […]
The Challenge with E-Motor Thermal Simulation Thermal simulation of electric motors sits at the intersection of two competing demands: the need for spatial accuracy at the component level, and the speed required for system-level scenario exploration. High‑fidelity 3D Finite Element (FE) thermal models of electric machines are essential for predicting hotspot temperatures, validating cooling strategies, […]
Battery Management Systems (BMSs) play a critical role in ensuring lithium-ion battery packs operate safely, efficiently, and reliably across all operating conditions. As battery systems become more complex and application demands continue to increase, validating BMS algorithms has become significantly more challenging. Building on the previous blog’s overview of BMS architecture for lithium-ion batteries (LIBs), […]
Part 1 introduced the operational challenges associated with battery-powered IoT monitoring devices. Part 2 described how GT‑SUITE and GT‑AutoLion models capture the system physics and battery aging mechanisms. This final part explains how these models integrate into an IoT and cloud architecture, allowing each digital twin to operate as an automated, scalable component of the […]
In Part 1, we explored why solar-charged, battery-powered IoT monitoring devices require reliable prediction of availability, SOH, and RUL, and why telemetry, statistical methods, or machine learning alone are not sufficient. In this second part, we focus on the modeling foundation: how GT‑SUITE and GT‑AutoLion provide the physics‑based structure that allows each digital twin to […]
From asset monitoring stations in remote locations to industrial sensors tracking equipment health, many modern systems rely on small, self-powered IoT devices operating far from human reach. These devices are typically equipped with a solar panel, a battery, and a communication module. Their job is simple: collect data, stay powered, and reliably transmit information to […]
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 […]
