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 […]
A Difficult Balance for Data Centers As data centers push toward higher rack power densities and rapidly scaling AI workloads, liquid cooling has become essential for managing extreme thermal loads efficiently. Designing these next generation cooling systems is challenging – engineers must balance reliability, energy use, water consumption, and safety, all while navigating tight deployment […]
Data centers face an unprecedented thermal challenge that demands revolutionary approaches to cooling system design and control. As computational demands surge with AI workloads and high-performance computing applications, heat generation has increased dramatically with some next-generation systems producing heat fluxes many times higher than traditional data centers. This exponential growth in thermal loads is pushing […]
In the previous blog, we discussed how the underlying architecture of a battery management system (BMS) is very similar to our central nervous system. The BMS relies on sensors (sensory organs) to make real-time decisions to ensure safety and optimize performance of the battery pack. From a simulation perspective, this architecture provides the foundation for […]
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. […]
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 […]
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 […]
The Human Analogy: How BMS Brings Batteries to Life Imagine walking into your favorite bakery. Your eyes scan the variety of treats in the glassed casing. Your ears pick up the humming and whirring of the ovens. Your skin senses the warmth in the room. Your nose picks up the smells of freshly baked bread […]
