Imagine you are driving your electric vehicle on the highway and realize that you will soon need a charging station. You turn to the navigation app or a special e-charging application to find the nearest available charging station (ePOI). But is the information displayed really reliable? Is the charging station actually free? Are the prices correct? These questions were the focus of our tests.
Accurate live data on charging stations is crucial for drivers of electric vehicles. They must provide reliable information on prices, availability and usage status to enable efficient charging planning. To validate this data, Europe-wide field tests were carried out to enable a comprehensive analysis of live data quality.
Over a period of two weeks, three teams of two people each checked the live data from charging stations along defined routes in Germany, Switzerland, France, Italy, Spain and the Benelux countries. Random samples were taken at charging stations, the available data was compared with the actual conditions on site and all results were recorded in a structured database. The aim was to identify deviations and optimize system accuracy. In addition, it was checked how current price and availability data was displayed and updated in the applications in order to obtain a realistic assessment of the data quality.
E-charging apps are essential tools for electric vehicle drivers to quickly and easily find the nearest available charging station. They offer a wide range of information, including location, number of charging points, available charging capacity, prices and usage status. Many applications also integrate real-time data showing current occupancy and possible waiting times. Some even allow direct reservation or payment via the app. Our test evaluated the extent to which these functions work reliably and whether the information displayed corresponds to the actual conditions.
A detailed test structure made it possible to precisely record all relevant parameters. It was particularly important to differentiate between planned and actual availability and to validate the price information in real time. This involved documenting how quickly and reliably the information was updated in the applications and whether it matched the actual conditions on site.
Systematic categorization and analysis made it possible to identify recurring patterns in the data, which provided valuable insights for optimization measures. The test results were made available directly to the product managers so that many of the identified improvement potentials could be implemented immediately. The close collaboration between test teams and clients ensured that the live data was continuously improved to provide the OEM's end customers with even more precise and reliable charge planning.
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