GT-AutoLion

From real-time battery modeling to micro-scale level design, GT-AutoLion offers a comprehensive suite of solutions to meet diverse battery simulation requirements—all within a unified simulation environment. Whether you need high-fidelity electrochemical modeling or fast predictive tools, our technology adapts to your specific needs.

On top of the Pseudo-2D model, GT-AutoLion also includes a swelling model capable of predicting stress, strain, and pressure in a cell as active material expands during lithiation.  Finally, every installation includes a comprehensive electrochemical materials database, reducing the burden for laboratory testing of electrochemical properties.

GT-AutoLion can be used to predict how various Li-ion chemistries and cell designs will perform before they are prototyped or even available for testing.  With GT-AutoLion, a Li-ion battery’s performance can be predicted under any load, including constant current (voltage drop and temperature rise shown to the left) and more dynamic loads.

GT recognizes that Li-ion cells and batteries must function within broader systems. To support this, GT-AutoLion seamlessly integrates with GT’s system-level, battery pack, and Simulink models, allowing performance analysis in an integrated environment. A built-in battery characterization toolbox simplifies exporting electrical-equivalent models, while GT’s Design of Experiments, Design Optimizer, and distributed computing accelerates parameter identification and calibration. Additionally, encrypted models enable secure sharing among suppliers and OEMs.

BATTERY MANAGEMENT SYSTEM CALIBRATION & VERIFICATION

GT-AutoLion empowers engineers to design smarter, more efficient BMS algorithms for State of Charge (SOC) estimation, State of Health (SOH) tracking, thermal management, cell balancing, and cell protection. Its variety of simulation solutions provide deep insights into real-world battery behavior, enabling predictive control strategies  and optimized fast charging strategies to enhance performance, extend battery lifespan, and improve safety.

Moreover, GT-AutoLion & GT-SUITE offer the possibility to validate controller design by leveraging cell and pack battery models in Model-in-the-Loop (MiL), Software-in-the-loop (SiL) simulations, and Hardware-in-the-loop (HiL) simulations.

GT-AutoLion helps predict how Lithium-ion cells of any chemistry will degrade in any use case, including calendar aging, cycle aging, and mixed aging scenarios.  GT-AutoLion includes an extensive list of available Li-ion degradation mechanisms, including active material isolation, SEI and cathodic film growth, electrolyte dry-out, and Lithium-plating (validation and visualization of these models shown to the left).  These mechanisms enable users to predict not only capacity fade, but also resistance growth of a Li-ion cell as it ages.  These models can be used to reduce testing time and cost, predict how batteries age in real-world scenarios, predict how aged batteries affect system performance, and calibrate and optimize fast charging strategies.