Synergizing Transfer Learning and Multi-Agent Systems for Thermal Parametrization in Induction Traction Motors
Fozia Mehboob,
Anas Fattouh,
Smruti Sahoo
Abstract:This paper presents an innovative multi-agent, data-driven reinforcement learning (RL) approach to develop and utilize the thermal equivalent network model that represents the motor's thermal dynamics. A multi-agent reinforcement learning is designed and trained to adjust the model parameters using data from several motor driving cycles. To ensure the incoming driving cycle matches the historical data before employing the pre-trained RL agents, offline statistical analysis and clustering techniques ar… Show more
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