SL-BMS ensures a margin of error below 5% 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. SL-BMS also minimizes maintenance costs and optimizes the use of both in-service and retired batteries.
Technology Breakthroughs and Features:
The first battery management system using a self-learning algorithm to provide correct readings of battery aging, remaining and restricted power for e-scooters.
Reduces range anxiety by transferring state of charge (SOC) into accurate remaining mileage and mileage with restricted power mode information.
Collects driving energy consumption data and uses a capacity estimation technique (Pat. No: US8253380, 8823325) for precise range estimation.
Increases utilization of battery capacity up to 50%, boosting driving range in EVs and reducing charging frequency.
Extends battery longevity by over 20% with cell balancing, charging, and discharging strategies.
Offers real-time battery health check, ensuring vehicle safety as well as saving time and resources for recycling of power batteries.
Technological Components and Specifications:
Model number: ITRI-SL-BMS-Escooter
Aging/remaining capacity error: < 5% (For NCM/NCA cell until retired)
Active/passive hybrid balancing hardware/control algorithm
Max. balancing current: 2A
Cell voltage difference: < 20mV
Retail Price (USD): $400-600/kWh (for mass production)
Applications:
Electric vehicles (EVs)
Retired power battery recycling
Large-scale energy storage systems
