ARMxy BL370 + Edge AI industrial IoT gateway: supports 30+ industrial protocols, <50ms latency, 1TOPS NPU for edge AI, cuts 60%+ maintenance costs, enables intelligent device interconnection.
Case Details
In the new energy storage industry, efficient energy management directly affects operational safety, battery lifespan, and investment returns. Traditional energy storage systems face core challenges such as low energy utilization, short battery cycle life, difficult remote maintenance, and disjointed data. This solution, based on the
ARMxy BL350 industrial-grade embedded computer and IgH EtherCAT master station technology, builds an intelligent energy storage EMS (Energy Management System) integrating real-time data acquisition, battery health monitoring, intelligent energy scheduling, and remote operation and maintenance. By adopting a lithium battery SOC/SOH accurate estimation algorithm, it achieves ±3% energy scheduling precision and extends battery cycle life by 15%-25%. Combined with BLIoTLink, BLRAT, and Node-Red core tools, the solution ultimately reduces energy waste by 10%-18%, cuts on-site maintenance costs by over 60%, and realizes full-life-cycle intelligent management of energy storage systems.
- Low Energy Utilization: Lack of real-time optimization of charging/discharging strategies, leading to ineffective use of grid peak-valley price differences.
- Short Battery Lifespan: Unbalanced charging/discharging and inadequate thermal management cause accelerated battery degradation.
- Difficult Remote Maintenance: Disperse deployment of energy storage stations requires frequent on-site debugging, resulting in high labor costs.
- Disjointed Data: Isolated operation data from grid, battery, and load systems, making it impossible to implement global optimization.
The ARMxy BL350 + Edge Computing combination delivers four core values for energy storage EMS:
- Hard Real-Time Response: Equipped with Linux-RT kernel and EtherCAT industrial Ethernet, ensuring millisecond-level synchronization of battery data and control commands.
- High-Reliability Operation: Industrial-grade design with -40~85℃ wide temperature range and IP30 protection, adapting to harsh outdoor environments.
- Intelligent Algorithm Empowerment: Integrated SOC/SOH accurate estimation and peak-valley arbitrage algorithms, maximizing energy utilization efficiency.
- Multi-Protocol Interconnection: Supports Modbus, IEC104, MQTT protocols, seamlessly connecting to grid dispatching systems and cloud platforms.
Adopting a "cloud-edge-device" three-tier collaborative architecture:
- Device Layer: Battery management system (BMS), charging/discharging controller, temperature sensor, grid meter, collecting battery status and energy flow data.
- Edge Layer: ARMxy BL350 as the core controller, undertaking real-time data processing, algorithm calculation, and charging/discharging strategy execution.
- Cloud Layer: Realizing remote monitoring, data analysis, strategy iteration, and fault early warning.
- Battery Health Monitoring: Based on Kalman filter algorithm, accurately estimating SOC (State of Charge) and SOH (State of Health) to avoid overcharging/overdischarging.
- Intelligent Energy Scheduling: Combining grid peak-valley prices and battery status, automatically adjusting charging/discharging power and timing.
- Real-Time Data Transmission: Relying on EtherCAT and MQTT protocols, realizing low-latency transmission of battery and energy data.
- Remote Operation and Maintenance: Through BLRAT tool, realizing remote debugging of parameters, fault diagnosis, and system upgrades.
- Main Controller: ARMxy BL352B (3×10/100M Ethernet ports, supporting EtherCAT ring network, 2 Y-board slots)
- Core Board: SOM352 (TI AM6254, 4×Cortex-A53, 1GB DDR4, 8GB eMMC)
- Peripheral Configuration: BMS communication module, charging/discharging controller, temperature/humidity sensor, three-phase electric energy meter
- Expansion Module: Y31 AI module (for battery current/voltage data collection), Y63 RS485 module (for connecting BMS), Y51 RTD module (for battery temperature monitoring)
- Precise Scheduling: ±3% energy scheduling precision, maximizing economic benefits through peak-valley arbitrage.
- Battery Protection: Scientific charging/discharging strategy and thermal management, extending battery cycle life by 15%-25%.
- Cost Reduction: 24/7 unattended operation, reducing on-site maintenance costs by over 60%.
- Flexible Expansion: Compatible with lithium-ion, flow battery systems, supporting capacity expansion without system reconstruction.
This solution is suitable for:
- Industrial and commercial energy storage systems (factory, data center)
- User-side energy storage stations (residential community, office building)
- Renewable energy supporting energy storage (solar, wind power matching)
- Grid-side energy storage (peak shaving, frequency modulation)
- Emergency backup energy storage systems
The
ARMxy BL350 + Edge Computing energy storage EMS solves the core pain points of traditional energy storage systems through hardware reliability, algorithm intelligence, and software ecosystem integration. The solution not only realizes intelligent scheduling and battery protection but also provides data support for operational optimization through full-life-cycle monitoring. It is an important technical support for energy storage enterprises to improve operational efficiency, reduce costs, and ensure safety, and a key path to build a smart energy ecosystem.
