Two real impedance values at selected frequencies, plus state of charge and temperature, are mapped by random forests to laboratory impedance, charge/discharge, and relaxation curves, which then feed existing lab-trained battery health models.
Random forests, Machine learning, 45, 5-32 (2001)
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Machine learning bridging battery field data and laboratory data
Two real impedance values at selected frequencies, plus state of charge and temperature, are mapped by random forests to laboratory impedance, charge/discharge, and relaxation curves, which then feed existing lab-trained battery health models.