Taiwan’s Industrial Technology Research Institute (ITRI) has announced that it will present its Self-Learning Battery Management System (SL-BMS), which uses self-learning algorithms to monitor, regulate and accurately calculate in real-time the energy consumption and remaining capacity of electric vehicle batteries at CES 2021.

ITRI says its SL-BMS ensures a margin of error below 5 percent in calculating energy consumption and range estimation; its accuracy can help reduce range anxiety, the fear that an electric vehicle won't have sufficient charge to reach its destination. The SL-BMS also minimises maintenance costs and optimises the use of both in-service and retired batteries.

Founded in 1931, the Industrial Technology Research Institute (ITRI) is one of the leading technology R&D institutions aiming to innovate a better future for society and has played a vital role in transforming Taiwan’s industries from labour-intensive into innovation-driven. To address market needs and global trends, it has launched its 2030 technology strategy and roadmap focussing on innovation development in smart living, quality health and sustainable environment. Over the years, ITRI is dedicated to incubating startups and spinoffs.

The institute claims the SL-BMS is the first battery management system using a self-learning algorithm to provide correct readings of battery aging, remaining and restricted power for e-scooters. It helps reduce range anxiety by transferring state of charge (SOC) into accurate remaining mileage and mileage with restricted power mode information. The BMS collects driving energy consumption data and uses a capacity estimation technique for precise range estimation. Furthermore it increases utilisation of battery capacity up to 50 percent, boosting driving range in EVs and reducing charging frequency. This also helps in extending battery longevity by over 20 percent with cell balancing, charging, and discharging strategies. The SL-BMS offers real-time battery health check, ensuring vehicle safety as well as saving time and resources for recycling of power batteries.