BatterMachine’s core technology applies machine learning algorithms via its BatMF framework to estimate critical battery states—State of Charge (SOC), State of Health (SOH), State of Function (SOF), and Remaining Useful Life (RUL)—and develop ASIL C/D compliant BMS software architectures to optimize performance, extend lifespan, and ensure safety in high-reliability environments.
Flagship product BatMF (Machine Learning Development Framework) enables accurate battery state estimation to optimize performance and extend lifespan. Additional offerings include specialized ASIL C/D BMS platform software architectures and ML-based applications for SOC, SOH, SOF, and RUL estimation, adaptable to electric vehicles, renewable energy storage, and industrial systems.
Since 2023, BatterMachine has been advancing its BatMF framework and BMS software architectures and collaborating with industry partners to test and validate its solutions in electric vehicle and grid-scale energy storage applications.
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