Model Predictive Control (MPC) is effective for real-time State of Power (SOP) estimation and power allocation because it uses a battery model to predict future battery behavior over a prediction horizon, optimizes control actions while considering constraints, and implements the first control action in each control cycle, enabling proactive and safe power management. MPC works by first using a mathematical model of the battery (e.g., an equivalent circuit model or an electrochemical model) to predict the battery's future behavior over a finite time horizon, called the prediction horizon. This model takes into account the battery's current state (e.g., SOC, temperature) and the expected operating conditions (e.g., load profile) to forecast how the battery's voltage, current, and temperature will evolve over time. Second, MPC formulates an optimization problem that minimizes a cos....
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