Embracing AI at Porsche
London, June 05, 2025 , (Oilandgaspress) –––Artificial intelligence (AI) is becoming increasingly important in vehicle development. It has become an indispensable tool, especially for complex systems in a network, such as the battery-electric energy storage system.
The increasing number of highly developed sensors provides a volume of data that could no longer be processed with conventional software. For Porsche, using machine learning and AI for data analysis is helpful for understanding huge amounts of information and varying contexts. Using these tools helps to provide reliable insights into component behaviour and interaction.
AI in battery development
A high-voltage battery is a complex system that is exposed to a wide range of external and internal influences. These influences are made visible by Porsche’s engineers through data analysis and the use of AI in connection with the effects on the energy system. The knowledge gained in this way is an essential basis for developing ever-better components and systems for Porsche customers.
AI supports developers in particular in detecting implausible behaviour within a battery. This allows the algorithms to analyse the balancing behaviour of individual cells and the entire battery as early as the development stage. Balancing refers to the charge balance between the cells of a battery module. If the values deviate from the expected state, the data allows faster conclusions to be drawn about the causes and underlying processes. At the same time, the data quality in the development process is improved, so that later findings from customer vehicles are even more reliable.
In addition to the known main drivers of battery ageing, modern analysis methods can also be used to identify other influences. Through the coupled application of state-of- the-art data-analysis methods and physicochemical models, forecasts and analyses of the ageing of high-voltage batteries in the customer fleet can be created. With the understanding of the various ageing influences on the basis of data analyses, the system developers work on the further optimisation of the operating strategy. All optimisation criteria such as range, charging time, system performance, weight, durability and consumption are worked out.
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