Why physics-based models can optimise fast charging
(The Engineer) Fast charging is one of the most important challenges facing the electric vehicle industry today. Drivers want the convenience of charging their cars as quickly as refuelling a petrol vehicle, but increasing charging speeds introduces risks that can damage the battery or shorten its lifespan. In my view, the key to solving this challenge lies in better understanding what is actually happening inside the battery during charging — and that is where physics-based models come in.
Traditional battery management systems rely heavily on simplified models or fixed charging rules. These methods typically monitor external measurements such as voltage, current and temperature, and use predefined limits to determine how quickly a battery can safely charge. While this approach is simple and reliable, it is also highly conservative. To avoid damaging the battery, manufacturers often restrict charging performance far below the battery’s true capabilities.
Physics-based models offer a different approach. Instead of relying purely on external measurements, they attempt to simulate the underlying electrochemical processes inside the battery itself. These models describe how lithium ions move through the electrodes and electrolyte, how heat is generated during charging, and how different reactions influence performance and degradation. By capturing these internal processes, physics-based models provide a far deeper understanding of how a battery behaves in real time.
This level of insight is particularly important for fast charging. Charging a lithium-ion battery too quickly can cause lithium plating — a phenomenon where lithium metal deposits on the anode instead of intercalating into it. Lithium plating accelerates battery degradation and can eventually lead to safety issues. Because this process occurs inside the battery, it cannot be directly measured by sensors. However, physics-based models can estimate the internal conditions that lead to lithium plating and adjust charging behaviour accordingly.
With this information, charging algorithms can dynamically optimise the charging current throughout the entire charging process. Instead of applying a single fixed charging profile, the system continuously adapts the charging strategy based on the predicted internal state of the battery. This allows the battery to charge faster when conditions are safe and to slow down when risks begin to appear. The result is a more efficient balance between charging speed, battery health and safety.
Another advantage of physics-based models is their ability to handle the complex interactions that occur during fast charging. Battery performance depends on multiple factors, including temperature, state of charge and battery age. These factors influence each other in complicated ways, making it difficult for simplified models to capture the full behaviour of the system. Physics-based models incorporate electrochemical, thermal and mechanical processes, allowing engineers to design charging strategies that consider these interactions simultaneously.
Ultimately, improving fast charging is not just about increasing power at charging stations. It requires smarter control of the battery itself. By using physics-based models to understand what is happening inside the battery, we can safely push batteries closer to their real limits and unlock significantly faster charging performance.
As electric vehicles become more widespread, software and modelling will play an increasingly important role in battery innovation. Advances in battery chemistry will continue, but intelligent battery management will be just as critical. Physics-based models provide the foundation for that future — enabling charging systems that are faster, safer and more efficient.