Introduction
Battery systems lie at the heart of modern energy solutions, from electric vehicles to renewable energy storage. Accurately predicting their performance, longevity, and safety is essential for innovation and cost-efficiency.
While traditional simulation models rely on either empirical simplicity or complex electrochemical methods, TWAICE’s Physics-Informed Modeling framework bridges this gap by combining the best of both worlds — offering unmatched advantage in speed, precision, and actionable insights.
Last article we explained TWAICE Modeling Approach in detail. This article delves into the physics-informed aspects of TWAICE’s modeling approach with specialized features: OCV Aging, Degradation Modes, Swelling Force, and Anode Potential Models.
TWAICE Approach: Bridging the gap between empirical models and electrochemical approaches
By combining the practical simplicity of empirical models with the detailed fidelity of electrochemical approaches, TWAICE’s methodology enables accurate and computationally efficient models while retaining deep insights into battery behavior and degradation mechanisms.
TWAICE’s battery modeling framework uniquely combines:
Speed and simplicity of empirical aging models,
Extends to the electrode level to capture a more granular understanding of degradation mechanisms,
Predictive capabilities of state-of-the-art machine learning.
This advancement is further bolstered by specialized features that embody the physics-informed nature of our models. These features—OCV Aging, Degradation Modes, Swelling Force, and the newest one Anode Potential Model—enhance the physical and chemical accuracy of our models, setting a new standard in battery analytics.
Degradation Modes
TWAICE integrates degradation modes into its battery models to capture and differentiate the causes of capacity fade and power fade. By simulating factors like Loss of Lithium Inventory (LLI) and Loss of Active Material (LAM) at the anode and cathode, the models provide actionable insights into aging mechanisms. This empowers users to optimize battery designs, manage safety risks, and improve performance under diverse operating conditions.
OCV Aging
Integrating OCV aging into TWAICE’s battery models ensures that changes in the OCV curve over a cell’s lifetime are accurately captured. This enhances model precision for aged cells, improves electrothermal simulations, and optimizes tasks such as state estimation for SoC and SoH, ultimately driving better performance and reliability.
Swelling Force
TWAICE models swelling force to capture the impact of cell thickness changes due to aging and gas generation. By simulating the evolution of swelling force under various operational conditions, users can optimize pressure levels for battery modules. This ensures proper mechanical design, minimizes aging effects, and balances factors like excessive or insufficient pressure, ultimately improving performance and durability.
Anode Potential Model
TWAICE’s latest innovation, the Anode Potential Model, provides deeper insights into lithium plating and anode-level phenomena. By dynamically modeling anode potential with aging over lifetime of batteries, this feature enables engineers to design fast charging algorithms avoiding lithium plating, which can lead to capacity loss and safety risks.
Importance in Real-World Applications
Optimizing Battery Design: By leveraging electrode-level data and predictive analytics, TWAICE’s models help refine system designs to maximize performance and longevity.
Extending Battery Life: TWAICE’s advanced simulations enable tailored usage strategies that minimize degradation, ensuring prolonged and reliable operation.
Enhancing Safety: Through precise modeling of swelling forces and degradation modes, potential safety risks are identified and mitigated, protecting both users and systems.
Fast charging profiles optimization: Anode Potential Model enables engineers to design and optimize safe fast charging profiles to limits.
Reducing Costs and Time to Market: With accurate and actionable predictions, manufacturers can streamline development processes, reduce reliance on costly physical testing, and accelerate innovation cycles.
Conclusion
TWAICE’s Physics-Informed Modeling and specialized features are revolutionizing battery simulation. By combining empirical simplicity with electrochemical precision, these tools empower stakeholders to design safer, more reliable, and longer-lasting batteries—ensuring a sustainable and efficient future for battery systems.
Contact us today to learn how TWAICE can accelerate your development cycle and help design batteries more efficiently from the start.