Monolith AI Partners with NIO for Battery Anomaly Detection
Monolith, a cutting-edge artificial intelligence (AI) software provider trusted by some of the world's most innovative engineering teams, has been selected by NIO, a leader in the premium smart EV market, to collaborate on AI-driven anomaly detection for NIO's EV batteries.
Battery monitoring in EVs
NIO, renowned for its approach in the EV industry, is pioneering battery swap technology. The innovation presents a unique opportunity for the company to gain unprecedented insights into its batteries' real-world daily usage. NIO can use its partnership with Monolith to use advanced AI-driven tools to enhance battery performance and reliability.
NIO plans to leverage Monolith's Anomaly Detector AI software to monitor real-time performance data collected from its EV batteries. NIO can compare test-bench results by analysing this data, ensuring that field data directly informs further battery verification and optimisation activities. It will enable engineers from both companies to detect abnormal behaviours in battery performance faster, using complex system relationships as the basis for comparison.
Partnership to deliver premium user experience
Commenting on the collaboration, Frank Kindermann, Head of Battery System Europe at NIO, highlighted the importance of this partnership in advancing battery performance monitoring:
"NIO's partnership with Monolith exemplifies our commitment to delivering a premium user experience. 98% of our users across the five key European markets opt for Battery as a Service (BaaS). BaaS allows European NIO users to flexibly charge or swap their batteries as needed, enhancing convenience and cost efficiency."
He further emphasised the significance of the joint venture, adding:
"By combining our expertise in battery performance with Monolith's advanced laboratory capabilities, we're setting new standards in battery monitoring, ensuring unparalleled efficiency and reinforcing NIO's dedication to innovation and quality."
AI-driven detection for real-time anomalies
Monolith's Anomaly Detector harnesses the power of deep-learning algorithms to rapidly identify anomalies in battery test data. The self-learning algorithms automate inspecting raw data to flag potential errors or abnormal behaviours, even across hundreds of testing channels. The AI-powered system allows engineers to rapidly spot irregularities, such as spontaneous discharge or thermal runaway, thus addressing battery issues before they pose a risk.
Dr Richard Ahlfeld, CEO and Founder of Monolith explained the value this brings to the EV industry:
"Monolith's deep-learning algorithms allow for automatic detection of battery issues, such as spontaneous discharge and thermal runaway, making it easier to analyse complex real-world data quickly. This capability not only saves time and resources but also enhances battery safety. As a leader in software-defined vehicles, NIO is the ideal partner to leverage this advanced technology, driving innovation in battery performance and safety."
Advancing battery technology with AI
The collaboration between NIO and Monolith goes beyond anomaly detection. Monolith's AI platform offers a range of sophisticated algorithms that reduce the need for extensive physical testing, simulations and manual analysis. Monolith's AI software can make immediate predictions by processing valuable engineering test data, allowing engineers to pinpoint areas where product optimisation and development are required.
The advanced AI-driven approach enables engineering teams to expedite the design cycle and reduce repetitive, time-consuming testing processes, ensuring faster, more efficient product development. The insights gained from these tests improve battery safety and performance and drive the industry forward in creating more reliable, high-performing EV batteries.
Make sure you check out the latest edition of EV Magazine and also sign up to our global conference series - Sustainability LIVE 2024.
EV Magazine is a BizClik brand.
