Press release
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december 24, 2020 - ITRI
ITRI's SL-BMS Fact Sheet
Self-Learning Battery Management System (SL-BMS)
At all-digital CES 2021, #ITRI is presenting the 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 (EV) batteries. 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
SLBMS
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