AI power Revolutionizes EV Charging

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Emobi and Autocrypt have partnered to create the first US Plug & Charge ecosystem that will revolutionize electric vehicle (EV) charging with the help of artificial intelligence.

The companies developed a secure communication framework for EV charging stations, focusing on building a Public Key Infrastructure (PKI) using artificial intelligence and machine learning models to address common errors and data inconsistencies in traditional Plug & Charge systems.

According to Innovation News Network, a Plug & Charge ecosystem enables EV drivers to start charging at any station by simply plugging in their vehicle. Asymmetric encryption technology enables the chargers to automatically identify the EV and securely process the payment of the EV charging session. This first US Plug & Charge ecosystem ensures data security and compliance with the US government, unlike other services around the world. It also sets a new industry benchmark due to its intelligent error-handling system that efficiently addresses edge cases.

Emobi has worked closely with the US Department of Energy (DOE) Argonne National Laboratory throughout this collaboration in order to ensure that the findings from this ecosystem contribute to the National Charging Experience Consortium (which is funded by the Joint Office of Energy and Transportation of the United States).

Sean Cho, President of Autocrypt North America, explained: “Security in EV charging infrastructure enhances openness while providing better control… By combining our PKI technology with Emobi’s expertise in AI and machine learning, we are bringing a secure yet innovative Plug & Charge solution to market, creating an unrestricted charging environment that ensures convenience, precision, and security throughout the entire charging and payment processes.”

Emobi CEO Lin Sun Fa added that the focus of the collaboration was to enable EV automakers, charger operators, and e-mobility service providers to continue building their products without being hindered by edge cases and constantly evolving standards.