It offers EV fleets 94 per cent to 96 per cent accuracy on performance metrics whilst providing valuable insights into battery usage patterns
Intangles Lab has launched its Ambient Cognitive artificial technology (AI) for Electric Vehicles (EVs). The suite of algorithms has been specifically developed to tackle range anxiety, a significant obstacle in large-scale EV adoption for the commercial vehicle industry.
According to a study published by SAE International, EVs have been found to deliver 12.5 per cent below their advertised range. The study also revealed that only 17 per cent of the tested EVs exceeded their estimated range.
As per SAE recommendations, EVs are allowed an adjustment factor of 0.7 or higher, which means that the real-world range can be up to 30 per cent lower than the calculated range. Inconsistent State-of-Charge measurements and unreliable Distance To Empty (DTE) readings have long plagued EV fleets, leading to ad hoc charging sessions, which cause unexpected disruptions and inefficiencies.
Intangles' platform provides a comprehensive solution by assimilating weather predictions, and forecasts around motor performance and vehicle dynamics while compensating for battery degradation over time.
"Our models can reach accuracies of 94 per cent to 96 per cent across varying driving conditions, thus supplementing range projections on vehicle Human Machine Interfaces (HMI)," said Intangles co-founder and head of analytics Aman Singh. "Our technology will help accelerate EV adoption by addressing one of the biggest concerns among fleet operators - range anxiety."
Accounting for varying driving conditions across diverse geographies and different periods of the day, Intangles' AI models perform multi-parametric forecasting across various variables, including motor torque, vehicle speed, ambient temperature guiding cell chemistry and sunset-sunrise trends, which influence the use of HVAC and lighting. This approach enables consistently accurate range predictions across dynamic driving ecosystems. Fleets can now plan their routes and deploy charging infrastructure more effectively.
“The technology has been designed to cater to various EV platforms, ranging from last-mile mobility three-wheelers to heavy commercial vehicles. Our platform can potentially benefit various segments, including e-commerce, last-mile logistics, long-distance freight and passenger transport. Our focus is to provide a comprehensive and reliable solution that can optimize range estimation for EVs, reduce charging downtime, and improve overall energy efficiency for the consumer,” said Intangles co-founder and CEO Anup Patil.
Since its inception in 2016, the start-up has been attempting to transform how organizations do business by leveraging its proprietary Digital Twin technology. Working with physics-based analytics and machine learning to simulate the real-world environment into a virtual world, it provides real-time and predictive insights, augmented with a large repository of repair strategies and recommendations. It lets operators in the mobility space monitor, benchmark and conduct predictive maintenance of assets in order to enhance their overall uptime & profitability.