Porsche, how batteries for high-performance electric cars are created

Shorter charging times and greater range. This can be summarised as the evolution of the batteries fitted in the Porsche Taycan, the German brand's first EV model. Over the past five years, this has increased from an average of 400 kilometres to around 600 kilometres for electric vehicles in the sports/luxury segment (according to the Wltp cycle). Both generations of the Taycan impress with an above-average range. Forecasts indicate that saturation in this segment will be reached at around 800 kilometres by the end of the decade. In addition to range, driving dynamics, reduced journey times, long battery life, maximum safety and reduced CO2 emissions are crucial for Porsche. Further developments based on the 800-volt technology developed by Porsche ensure that the Taycan's maximum charging capacity has been increased from 270 kilowatts to 320 kilowatts for the new generation. This ensures faster charging times, resulting in shorter journey times. The maximum charging current has increased from 336 amps to 400 amps. The minimum starting temperature for fast charging has been reduced from 25 degrees Celsius to 15 degrees. In addition, the capacity of the traction battery has increased from 93.4 kWh in the first-generation Taycan to 105 kWh in the new Taycan. At the same time, the discharge current has increased from 860 amps to 1100 amps - a significant advantage for driving dynamics. Despite the increased capacity, the weight of the battery has decreased from 634 kilograms to 625 kilograms, which further enhances its agility.

The life expectancy of the traction battery is a key factor in determining the economy and reliability of an electric vehicle. Porsche is testing the energy storage systems of its electric sports cars by simulating a service life of at least 15 years and over 300,000 km. The initial capacity loss is already taken into account in the production process. In practice, every battery ages. The so-called 'State of Health' (SOH) decreases. In the first two to twelve months, the so-called 'initial decline' occurs. In this case, a lithium-ion cell loses about two to five per cent of its capacity. Porsche takes this physical effect into account. A newly manufactured battery therefore usually has an energy content higher than the declared gross capacity. In-house testing procedures significantly exceed customer usage profiles. The key to avoiding these effects and thus to battery longevity, in addition to sound cell chemistry, is intelligent battery management. To this end, Porsche has developed a control algorithm based on customer habits. "We know that customers choose a fast charging process in about 15 per cent of cases," says Carlos Alberto Cordova Tineo (Battery Cell Development + Fast Charging). Porsche goes much further in its stress tests and charges the battery with high currents in half of the cycles. The life expectancy tests also simulate varying ambient temperatures and dynamic driving profiles. Extreme conditions such as exposure to temperatures of 60 to 100 degrees Celsius are also tested. And not only for short periods: long-term storage at 60 degrees is also part of the test programme. High cycle frequencies simulate recharging processes over different distances, ranging from 160,000 to 300,000 kilometres.

Artificial intelligence is becoming increasingly important in vehicle development. For Porsche, data analysis using machine learning and artificial intelligence (AI) methods is a tool for mastering the wealth of information and contexts. It helps to obtain reliable information about the behaviour and interaction of components. The high-voltage battery is a complex system exposed to a wide range of external and internal influences. These influences are made visible to engineers through data analysis and the application of AI in relation to the effects on the energy system. The knowledge gained forms an essential basis for the development of ever better components and systems. AI supports developers in particular in identifying implausible behaviour within the battery. This allows algorithms to analyse the balancing behaviour of individual cells and the entire battery already during the development phase. Balancing refers to the charge balance between the cells of a battery module. Through intelligent and adapted system design, the ageing factors identified by the AI can be reduced in a targeted manner.

Knowing about a possible failure in advance. This concept is the starting point for the preventive anomaly scanning brought to the debut of the electric Macan. This method assesses the technical cause and relevance of any faults detected in the data. This ensures the long-term performance of the high-voltage system. In addition, results are generated for future product development. Preventive anomaly detection utilises detectors that use intelligent algorithms to extract, for example, a variation in battery behaviour from online data. Detected anomalies are analysed, deciphered and evaluated in the cloud.