A hierarchical hybrid thermal control strategy for electric vehicle motors based on ADRC and TD3

Electric vehicle motors operating under high power density generate substantial heat, posing significant challenges to temperature regulation accuracy and cooling energy efficiency. Conventional thermal management strategies often struggle to achieve robust performance under highly dynamic and uncertain operating conditions. This paper proposes a hybrid thermal control strategy integrating active disturbance rejection control (ADRC) and Twin Delayed Deep Deterministic Policy Gradient (TD3) within a hierarchical architecture. A multi-heat-source coupled motor thermal model is established to capture complex thermal dynamics of stator, rotor, and cooling subsystems. The lower-layer ADRC ensures fast temperature tracking and disturbance suppression through an extended state observer, while the upper-layer TD3 optimizes cooling energy consumption by learning long-term policies. An adaptive coordination mechanism balances real-time regulation and energy efficiency optimization. Hardware-in-the-loop experiments are conducted on a 150 kW permanent magnet synchronous motor under standard driving cycles and extreme conditions. Results demonstrate that the proposed strategy reduces temperature control RMSE to 1.47 °C and cooling energy consumption by 31.9% compared with conventional PID control, while maintaining strong robustness under ±30% parameter perturbations. These findings indicate that the ADRC–TD3 hybrid strategy provides an effective solution for intelligent thermal management of electric vehicle motors.