How will artificial intelligence revolutionize electric cars?

The automotive sector is becoming a valuable organization, thanks to innovative advancements in electric autonomous vehicles.

This is according to a report by Frontiers in Future Transportation, a company that studies the possibilities for the evolution of future transportation frameworks.

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Artificial intelligence is essential to this evolution. “The safety and simplicity of AI-based innovation and the reasonableness of purpose, use, benefits, and limitations of AI frameworks are critical to meeting trustworthiness,” says The report.

Major EV manufacturers have different approaches to AI integration.
The main producer of electric vehicles is Tesla, now the market leader with a 15% share of the cake, followed by the Volkswagen group and SGMW (SGMW is a joint venture between General Motors and 2 Chinese companies), with 13.2% and 11.5% respectively according to an article published by The Washington Post.

China is now the largest car market in the world
Tesla enjoys strong markets in China, the United States and Europe, given the number of vehicles sold. Chinese manufacturers are in turn starting to be more aggressive, especially in the local market, the largest car market in the world, according to Canalys.

SGMW quickly acquired a large market share thanks to the explosion of sales in China of their new electric vehicle capable of driving at a maximum speed of 60 MPH (100 km/h). The vehicle was released in 2020 with an entry-level model at 29,000 Yuan (or less than €4,000), quickly becoming a top seller for frugal Chinese customers.

The Chinese government has injected no less than 400 billion yuan (about 51 billion euros) to help its electric vehicle industry, including subsidies for innovative work, charge exclusions and funding for charging stations. So far, Chinese brands haven’t made much headway outside of China, The Washington Post report says.

Strategic artificial intelligence for battery maintenance and innovation
The appearance of AI has upset the biological system of electric vehicles, especially in the field of battery improvement.

Simulated intelligence is particularly imperative for maintaining and checking the batteries of electric cars, which differ widely in their range. The Tesla Model S can travel 570 km, while the battery of a Renault Zoe discharges after 200 km, according to the report. Charging times also differ. A Tesla may require 1h15 minutes for a full charge, for example

“Batteries are very complex elements, whether in terms of synthesis, electricity or programming”, “However, examining the information can help us understand them better: how they are used, how they are influenced by the driver, how they are affected by the different parts of the vehicle. said Volkswagen Group Research & Development Director.

Machine learning models help in battery life cycle management. By blending cutting-edge electronics with the Internet of Things, data science and predictive intelligence can anticipate battery life, and identify degradation failures and their causes. Shamil Ara Mairon, the CEO of Energy Group, a company that applies intelligent battery analysis to improve the performance of lithium-ion batteries, explains that battery life data includes performance, state of load, stress related to rapid acceleration and deceleration, temperature and number of load cycles.

At the recent Artificial Intelligence Day, Tesla’s head of artificial intelligence presented the work being done to develop vehicle computer vision. The two fundamental problems that Tesla is working on in its computer vision engineering are short-lived obstacles (e.g., vehicles that are at busy intersections and block Autopilot’s perspective as it passes in front) and signs or markings that show a certain distance from the consolidation of the paths.

To help solve these problems, he described the work that Tesla engineers are doing on a repeating spatial organization, in which various parts of the module monitor various parts of the street and structure a line based on space and time. This provides a store of information that the model can refer to when trying to make predictions in the field, which prompted the artificial intelligence team to create a video game simulating real-life situations to help the car make the right decisions.