Renault is making significant strides in integrating machine learning into its automotive technology. According to the company’s AI engineers, this initiative marks a crucial step toward autonomous driving, where vehicles will be capable of navigating to a nearby garage for maintenance without any human involvement. This advancement could revolutionize how people interact with their cars, shifting from active driving to passive travel.
Maggie Mhanna, a data scientist at Renault Digital, explained that the company is already gathering extensive data from electric vehicles. This includes tracking when specific parts need replacement and storing that information in separate databases. By combining these datasets, Renault aims to predict key maintenance events, such as battery replacements, with greater accuracy.
This development is part of a broader trend in the automotive industry. Think tank RethinkX highlighted in May that once fully autonomous vehicles are legalized, public adoption could surge within the next decade. In this future scenario, passengers may no longer need to drive, as vehicles will handle all aspects of travel, including identifying issues and heading to the nearest service center.
Renault Zoe, an electric vehicle from the brand, is one of the models being tested with AI systems designed to estimate when batteries or other components might require replacement. The goal is to enable proactive maintenance, reducing downtime and improving overall vehicle performance.
The Renault data system operates by collecting usage data from electric vehicles, including trip distances, battery temperatures during charging, external weather conditions, and power consumption levels. This data is then analyzed to identify patterns and determine the health of the battery.
By refining this data—calculating minimum, maximum, and average values—engineers can assess battery status more effectively. With this insight, predictive models can forecast potential failures up to a month in advance, allowing for timely interventions.
While electric vehicle batteries are known for their long lifespan, Tesla has demonstrated that some lab test vehicles can exceed 500,000 miles. This means Renault's research team must collect large volumes of data over extended periods to build reliable predictive models.
Overall, Renault's approach highlights the growing role of AI and big data in shaping the future of mobility, making vehicles smarter, safer, and more efficient.
Fiber Optic Box,Fiber Optics Box,Fiber Optic Boxes,Fiber Optic Junction Box
Cixi Dani Plastic Products Co.,Ltd , https://www.danifiberoptic.com