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Lennart Hinrichs (Commercial Director of TWAICE Technologies GmbH) - Copyright Twaice

AI as a driver of the mobility transition?

Guest post – The mobility transition megatrend was overshadowed not least by reports of alleged battery fires. Even if the reports subsequently turned out to be incorrect, the uncertainty among companies and end consumers remains. The most recent results  Investigations by the RTWH Aachenthat the failure rate of electric vehicles is only between 0,9 and 1,2 per 10.000 vehicles, while there are 7,8 fire accidents with classic combustion engines. In addition to optimizing performance and costs, safety is also essential for a successful e-car strategy - AI offers new opportunities here.

Vehicles are increasingly connected and collect large amounts of data. The battery also has various sensors and control devices, so-called battery management systems (BMS), which not only ensure safe battery operation but also generate enormous amounts of data. With this data about electrical parameters such as current and voltage, thermal conditions such as outside and system temperatures as well as various status messages from the system, manufacturers and users of electric vehicles can find out a lot about the condition of the battery. And that is important because it allows quality defects to be discovered at an early stage and possible failures to be prevented.

While many people think of generative AI such as the popular ChatGPT program when it comes to the omnipresent topic of “artificial intelligence”, it plays a different, much larger role in industry because it offers many opportunities in data analysis and, for example, the optimization of batteries. This is where AI helps solve pressing challenges in battery development, reliability and safety. With the help of AI, more powerful battery systems can be developed and, among other things, battery overloads can be avoided.

Battery management system: benefits and limitations

Engineers from all manufacturers and suppliers are currently in a race to find the battery with the longest range, the fastest charging speed and the lowest cost. You either have to deal with the fact that there is either no data at all because the battery cells are too new, or there is so much data that manual evaluation is impossible. At the same time, issues such as safety and battery longevity must also be addressed, because even if vehicles are subject to extensive quality control, defects can creep into the battery or battery cell.

The battery management system (BMS) is a first step towards greater safety because it controls the battery and protects it from harmful operating conditions such as charging or discharging too quickly. But this system also has limits, as the primary task of the BMS is more to control the battery than to recognize long-term trends. It is more likely to respond to errors that occur at that specific moment, similar to how a sprinkler system can only extinguish the fire that is already burning, but cannot warn of its outbreak. This means that safety-critical effects would probably not be recognized by the BMS. Cloud-supported AI analytics, as also found in TWAICE's battery analysis software, offers a further protection mechanism that can detect and qualify abnormalities across the entire fleet, in the individual vehicle or even at the cell level and thus in good time before a failure Battery or, in the worst case scenario, a fire warns – in advance!

Although such fires are extremely rare, as the RTWH Aachen has once again proven in this year's studies, due to the chemical composition of a battery they are difficult or impossible to extinguish. That's why it's important to operate batteries as safely as possible.

Effects of battery aging

In addition to acute damage to the vehicle, electric cars also suffer from continuous wear and tear, known as battery aging. This depends on usage behavior and time as well as on environmental conditions. For example, frequent quick charging at low outside temperatures can cause damage to the battery if the battery is not sufficiently preheated. Data from the vehicle allows AI-supported systems to continuously monitor precisely these effects and carry out usage recommendations or technical interventions (e.g. better charging control). In this way, the battery can be protected in the long term and expensive battery repairs or replacements can be avoided. AI-supported systems not only ensure safer batteries, but also more sustainability.

According to the current study Electric cars already produce around 89% fewer CO2 emissions than combustion engines. If electric vehicles are charged with green electricity, their balance improves further. Two additional factors have a positive impact on sustainability: maximum battery life and its continued use in the energy sector. The service life can be achieved primarily through optimized design and use. These are largely determined by insights into the actual aging of the battery and which influences should be avoided. However, transparency about the battery status is also the basic requirement for further use beyond mobile applications, for example as a buffer storage at home or at fast charging stations. Only if the battery is suitable for continued operation for several years is it even worthwhile to remove it from the vehicle and convert it. A diagnosis of the current condition and a lifespan prognosis are therefore required.

AI is the key

Let's summarize: At the moment, not only is transport being electrified, but more and more data is also being produced. If this data is made available accordingly and used correctly, we will achieve a sustainable mobility transition without sacrificing comfort. The crux of the matter is artificial intelligence. Their systematic use extends the lifespan of batteries, reduces their costs, increases their safety and sustainability and thus makes electric cars cheaper, more reliable and more attractive.

About the author 

Lennart Hinrichs is VP Strategic Partnerships at battery analytics software provider TWAICE. Through the unique combination of in-depth battery knowledge and artificial intelligence on a scalable analytics platform, TWAICE generates actionable insights for the entire battery life cycle. The analytics platform not only enables TWAICE products, but also serves as the basis for customer and partner solutions from an entire ecosystem of market leaders that increase the lifespan, efficiency, safety and sustainability of the products that power tomorrow's economy. For more information, visit

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