Fast charging has become a design target in electric vehicle (EV) engineering. However, the amount of current a pack can safely accept changes with temperature and battery condition.
Dania Ghantous, Co-founder & VP of Technology, Qnovo
Cold slows lithium transport into the anode and increases the risk of plating, while heat accelerates side reactions that reduce cycle life. Those limits continue to shift as the battery ages, so the most appropriate charging profile can change over time.
In this interview, Dania Ghantous, co-founder and VP of technology at Qnovo, discusses how adaptive charging uses real-time battery measurements to adjust current as conditions change.
She also explains where charging control ends and thermal management takes over, how chemistry and cell format affect the strategy, and what battery management system (BMS) engineers need to consider when integrating adaptive charging into a production vehicle.
Here’s what she had to say…
Why do high and low temperatures accelerate charging-related degradation, and what’s happening at the cell level in each case?
Temperature does not degrade batteries in one simple way. Cold and heat both make charging harder, but the degradation mechanisms are very different. The simple rule is this: cold charging is mostly an anode kinetics problem while hot charging is mostly a cathode stability problem.
At low temperature, the cell becomes kinetically constrained. Lithium ions move more slowly through the electrolyte and intercalate more slowly into the graphite anode. If the charging current is higher than what the anode can safely accept, lithium can deposit on the graphite surface instead of inserting into it. That’s lithium plating. It consumes cyclable lithium, increases impedance, reduces capacity and, in severe cases, can create safety events.
At high temperatures, the opposite happens. Ion transport is easier, but the cell is more chemically reactive. Side reactions accelerate, such as solid electrolyte interphase (SEI) growth, electrolyte oxidation, gas generation and cathode degradation. The damage is especially aggressive when high temperature is combined with high voltage because the cell is sitting in the most reactive part of its operating window.
That’s why operating between 25° to 35° C matters. It’s simply the temperature range where transport, kinetics and chemical stability are better balanced. The cell is warm enough to avoid plating risk but not so hot that parasitic reactions dominate. Charging degradation is lowest when the battery operates in that stable electrochemical window that is not too cold, not too hot and not pushed as if temperature does not matter.
What battery measurements or operating conditions does an adaptive charging system use to adjust the charging profile in real time?
Adaptive charging uses the battery’s response to charging and combines the measurement with battery models to infer what is happening electrochemically in real-time inside the cell. The goal is not simply to see where the battery’s health is today but to predict where it’s heading if you keep charging it the same way and take proactive corrective actions.
That turns charging into a control and optimization exercise. The algorithm continuously evaluates temperature, state of charge (SOC), current, voltage response, cell health and aging history, then decides how close the battery is to undesirable operating regions, such as lithium plating or accelerated side reactions. It can then “close the loop” by pushing current when the cell can tolerate it and backing off when the electrochemical margin begins to shrink.
This is a key point. Batteries are not static devices and they do not age in a perfectly predictable way. Charging them with the same fixed profile every time may be convenient, but it does not account for how the cell changes over time. Adaptive charging adjusts and updates models to aging conditions. It keeps diagnosing the battery’s health, updating the risk boundary and adjusting the charging strategy as the battery ages.
How does an adaptive approach balance charging speed against cell health across a wide operating temperature range?
An adaptive charging system doesn’t treat charging speed and battery health independently. A healthy battery under favorable conditions can charge faster and vice versa. It continuously diagnoses health and balances these tradeoffs in real time. The real question for the adaptive charging system centers around how much current a battery accepts under specific conditions before degradation starts to accelerate.
Adaptive charging adjusts current as battery temperature and condition change, helping balance charging speed with cell health. (All images: Qnovo)
Temperature moves that boundary around. At low temperature, the limiting risk is lithium plating because the anode cannot accept lithium fast enough. At high temperature, ion transport may be easier but the penalty shifts to accelerated side reactions. The stress mechanisms change as a function of temperature therefore the charging response has to change with it.
In other words, adaptive charging keeps searching for the highest current the cell can tolerate in that moment without causing health issues. When the battery is in a favorable temperature window, it can charge faster. When the cell is cold, hot, aged, imbalanced or thermally stressed, the algorithm has to back off. That’s the principle the approach is built on.
How much of the degradation problem can be addressed through charging control, and where does thermal management have to carry the load instead?
Charging control and thermal management solve different parts of the degradation problem. Charging control determines how hard the cell is pushed. Thermal management determines the conditions in which that happens. Both matter but they are not substitutes for each other.
Most charging damage is electrochemical. Lithium plating, impedance growth and mechanical stress are driven by whether the cell can accept the current being applied. Temperature influences how these mechanisms occur.
This is where charging control does its work. It reduces these stress factors by adjusting the charging current based on the battery’s real-time response, temperature, state-of-charge, health and history. But charging control cannot fix a bad operating environment.
If the pack is too cold, the anode kinetics are still slow. If it’s too hot, parasitic reactions still accelerate. Thermal management has to create a usable window where the electrochemistry is well behaved enough for adaptive charging to operate effectively inside that window. In other words, adaptive charging manages the battery’s electrochemical stress while thermal management manages the operating envelope.
How do cell chemistry and format change the approach, and what matters most when a strategy moves from one chemistry to another?
The principles of adaptive charging transfer across chemistries and cell formats. The differences are in the limits or parameters that define each chemistry, format and system constraints.
When you move from one chemistry to another, the goal is not to copy the same current and voltage profile. The goal is to preserve the same electrochemical risk margin. In other words, the goal is to minimize degradation mechanisms under different operating and environmental conditions. Keep in mind that batteries do not respond to charging profiles. They respond to local conditions inside the cell, such as concentration gradients, temperature and aging state.
Chemistry changes which failure modes dominate. One chemistry may be limited by lithium plating at low temperatures. Another may be more sensitive to SEI growth, gas generation, cathode degradation or mechanical stress. Furthermore, even when the risk is the same, for example lithium plating, the onset conditions and safe operating margins can be very different.
Format matters too. Cylindrical, pouch and prismatic cells do not distribute heat, current or mechanical stress in the same way. Combining this with the pack architecture adds another layer of constraints: cooling path, sensor placement, cell spacing, electrical layout and thermal gradients. Therefore, the charging control strategy has to be tuned to the cell and to the system that cell actually lives in.
What test conditions and baselines make degradation claims comparable across studies?
Degradation claims are easy to make and hard to compare. A number like 30% faster charging or 50% longer life does not mean much unless you know what it was measured against. The better question is whether the battery delivered the same life, safety and performance while being pushed under more demanding charging conditions.
An EV charging display shows the estimated time to 80% state of charge, reflecting how charging decisions can adapt to battery condition and operating limits.
To compare studies fairly, the test has to control the variables that actually drive aging: cell chemistry, format, temperature, SOC window, voltage limit, charge and discharge rates, rest periods, thermal behavior, sample size, aging metric and end-of-life definition. If those are not aligned, you are not comparing algorithms. You are comparing test conditions.
Every comparison has a baseline to compare against. An adaptive fast-charge strategy aims to deliver the same cycle life as a slower baseline under the same conditions, which is a meaningful result. That means achieving the same degradation while giving the user a faster charging experience.
That’s the benchmark that engineers should care about: preserving the cycle life and safety of slow charging while delivering the convenience of fast charging.
What should EV battery and BMS engineers consider when integrating adaptive charging, and where do the practical constraints show up?
Adaptive charging has to be designed into the vehicle system. The cell, pack, thermal system, charger, sensors and software must all support the decision the algorithm is trying to make. The algorithm can be smart but it’s only as good as the information the vehicle platform provides it.
The practical constraints are usually not from the adaptive charging logic itself. The algorithm must be designed to run efficiently within the limited memory and compute footprint of a production BMS. The real integration work is making sure the surrounding systems can provide reliable inputs and act on the decisions in real time.
This includes:
- Thermal management
- Sensor accuracy
- Measurement error
- BMS data quality
- Communication interfaces
- Memory limits
- OEM software requirements
A battery may be able to accept more charge, but if the cooling system cannot remove the heat or the sensors introduce too much uncertainty and lack the memory and compute headroom to run the model reliably, the charging strategy has to protect the cell and adjust accordingly.
There’s also a mindset shift for BMS teams. Battery management has traditionally relied on fixed charge maps that are calibrated, validated and then held relatively static. Adaptive charging asks the BMS to accept a more dynamic and intelligent control approach that is still deterministic, bounded and validated, but able to update decisions based on the battery’s real-time condition instead of following the same map under every condition.
That’s why successful integration of adaptive charging is about coordinating the cell, BMS, thermal system, charger and vehicle software in real-time. The practical constraints almost always appear at those interfaces and not in the charging algorithm itself.
Filed Under: Featured Contributions, Q&As